MASI – Mallinnus ja simulointi 2005-2009 -ohjelman loppuraportti
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MASI – Mallinnus ja simulointi 2005-2009 -ohjelman loppuraportti

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Tekesin MASI – Mallinnus ja simulointi 2005–2009 -ohjelmassa kehitettiin suomalaista mallinnuksen ja simuloinnin osaamista. MASIn loppuraportissa esitellään ohjelman tuloksia ja siihen ...

Tekesin MASI – Mallinnus ja simulointi 2005–2009 -ohjelmassa kehitettiin suomalaista mallinnuksen ja simuloinnin osaamista. MASIn loppuraportissa esitellään ohjelman tuloksia ja siihen osallistuneita projekteja.

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    MASI – Mallinnus ja simulointi 2005-2009 -ohjelman loppuraportti MASI – Mallinnus ja simulointi 2005-2009 -ohjelman loppuraportti Document Transcript

    • MASI ProgrammeTekes Programme Report 3/2010 2005–2009Final Report Niina Holviala (ed.)
    • Niina Holviala (ed.) VTT Technical Research Centre of FinlandMASI Programme 2005–2009 Final Report Tekes Programme Report 3/2010 Helsinki 2010 3
    • Tekes, the Finnish Funding Agency for Technology and Innovation Tekes is the main public funding organisation for research and development (R&D) in Finland. Tekes funds industrial projects as well as projects in research organisations, and especially promotes innovative, risk-intensive projects. Tekes offers partners from abroad a gateway to the key technology players in Finland. Tekes programmes – Tekes´ choices for the greatest impact of R&D funding Tekes uses programmes to allocate its financing, networking and expert services to areas that are important for business and society. Programmes are launched in areas of application and technology that are in line with the focus areas in Tekes’ strategy. Tekes programmes have been contributing to changes in the Finnish innovation environment for twenty years. Copyright Tekes 2010. All rights reserved. This publication includes materials protected under copyright law, the copyright for which is held by Tekes or a third party. The materials appearing in publications may not be used for commercial purposes. The contents of publications are the opinion of the writers and do not represent the official position of Tekes. Tekes bears no responsibility for any possible damages arising from their use. The original source must be mentioned when quoting from the materials. ISSN 1797-7347 ISBN 978-952-457-498-3 Page layout DTPage Oy Printed by Libris Oy, Helsinki 20104
    • ForewordThe modelling and simulation of objects and phenomena have a long history, espe-cially with regard to experimental modelling. In developing and learning new things,humanity has faced a need to try to identify the right direction and choices by cal-culating and trialling in advance, as accurately as possible, the object or phenome-non under study. Modelling and simulation offer an opportunity to explore the un-known, and to clarify matters that could not otherwise be measured or evaluated.They might also be compared to a compass helping to orient us in the fog of igno-rance towards the right target and destination. The development of numeric methods, and particularly the rapid developmentin the information technology sector in recent decades, have created ever better,more versatile and quicker possibilities for exploring the unknown. These possibili-ties are utilised ever more extensively in various industrial sectors and research insti-tutes, in Finland and in other countries. For some time now, Finland has been at thevery cutting edge in many areas of modelling and simulation. In 2005, Tekes’ MASI programme was launched to support the developmentof the Finnish modelling and simulation sector and to promote the utilisation in in-dustry of the sector’s tools and methods. The central aims of the programme wereidentified as the aggregation of phenomena models into wider and more integrat-ed models, more extensive implementation and utilisation of the sector’s tools andmethods in the business of small and medium-sized companies especially, and thedevelopment and strengthening of the range of services offered by the sector. Theaim of this was to effect renewal across Finnish industry and business, and to lift thecompetitiveness of both. Tekes, the Finnish Funding Agency for Technology and Innovation has al-ready participated in the development and funding of the Finnish simulation sec-tor through numerous technology programmes and separate funding schemes. Ex-amples of Tekes programmes that preceded the MASI programme include the LIEK-KI 2 – Combustion and Gasification Research Programme 1993–1998, the Compu-tational Fluid Dynamics Technology Programme 1995–1999, and CODE – Modellingof Combustion Processes 1999–2002. The MASI programme can be seen as the con-tinuation of, and most recent link in, this chain of programmes. MASI has been moreexpansive in nature than its predecessors, however, and with it Tekes has sought awider impact on the modelling and simulation field in Finland. The programme’s expansive nature and its targeting at several different areas ofindustry and business also meant that the programme’s target group and the con-tent of the projects covered a rather wide and comprehensive area of Finnish mod- 5
    • elling and simulation expertise. In addition to annual seminars, several mini-seminars and other events were held during the programme, for which the target group was chosen by further narrowing down the factors that linked projects. This achieved the desired networking across projects of a similar type and representing the same sector. The MASI programme was the focus of great interest and demand from both companies and research institutes from the moment it was launched. In financial terms the programme was also realised on a wider scale than originally planned. A further indication of the importance and development activity of the Finnish mod- elling and simulation sector is the direction of some of the sector’s funding demand during the final years of the MASI programme into other Tekes programmes, such as the Digital Product Process programme, the Academy of Finland’s Research Pro- gramme in Computational Science, and the Strategic Centres for Science, Technol- ogy and Innovation launched during the programme. As the MASI programme concludes, it is time to turn our gazes to the future and ponder what comes next. The expertise developed during the course of the programme should be carried forward for the benefit of Finnish business and soci- ety. Development work in the sector and cultivation of expertise will certainly con- tinue in Tekes’ other programmes, in the Academy of Finland’s programmes, and in the Strategic Centres for Science, Technology and Innovation. For its part, the programme has furthered the development of a multidiscipli- nary outlook and operational model in Finland, and promoted a culture of co-op- eration both within Finland and internationally. One notes improvements in Finn- ish expertise in many different areas of modelling and simulation. Utilisation of the expertise developed in the projects and the results of the projects has had, and will continue to have, a significant impact on Finnish society and business more broadly. Tekes sincerely thanks all of the people, companies, research bodies and other partners involved in planning and realising the MASI programme. Tekes would like to say thank you very much to the members of the Steering group, and to its chair- man Harri Turpeinen, for directing the programme. We would like to offer our par- ticularly warm thanks to Pekka Taskinen, who co-ordinated the programme with im- agination and efficiency, and to his supporting staff at VTT Technical Research Cen- tre of Finland. Helsinki, April 2010 Tekes6
    • ContentsForeword ............................................................................................................................................................................51 At the conclusion of the MASI programme .................................................................................9 General description ............................................................................................................................................9 Areas of emphasis and funding for the programme..................................................................10 The programme’s trajectory and results.............................................................................................11 Observations made during the course of the programme ...................................................142 Research projects .......................................................................................................................................... 17 Multiobjective optimization and multidisciplinary decision support – MASIT01 ....17 Symbiosis between plant and computational models (SIMBIOT) – MASIT02............20 Inverse problems and reliability of modelling – MASIT03 ......................................................22 Multiphase chemistry in process simulation (VISTA) – MASIT04 ........................................25 Statistical phenomena in virtual design of machines (MARTSI) – MASIT05.................29 Modelling and simulation of coupled problems in mechanics and electrical engineering – MASIT06...........................................................................................................33 Modeling and simulation of dissolved and colloidal substance flows in TMP- and DIP-processes – MASIT07 ................................................................................................36 Scientific computing and optimization in multidisciplinary applications (SCOMA) – MASIT08 ........................................................................................................................................38 Automated generation of 3D topographic visualisations – MASIT09 .............................42 Improvement of evacuation safety in large buildings by the combined simulation of fire and human behaviour – MASIT10..................................................................45 Modelling and simulation of manufacturing systems for value networks (MS2Value) – MASIT12 ...................................................................................................................................48 In silico models of disease pathogenesis and therapy (TRANSCENDO) – MASIT13 ...52 From discrete to continuous models for multiphase flows – MASIT14 ..........................55 Virtual engineering in design, training and completion of demanding maintenance work tasks (VIRVO) – MASIT15...................................................................................59 Modelling changing needs of consumers (KULTA) – MASIT16 & MASIT36 ..................62 Combining multiblock and CFD modelling (LOVI) – MASIT17 ............................................66 Utilisation of simulation in industrial design and resulting business opportunities (SISU) – MASIT18...............................................................................................................70 7
    • Multi-scale flow modelling (MUSCA) – MASIT19 ..........................................................................73 Nonlinear temporal and spatial forecasting: modeling and uncertainty analysis (NoTeS) – MASIT20 ........................................................................................................................78 Genuinely three-dimensional user interfaces in product design and animation (HandsOn) – MASIT21 ...........................................................................................................83 Developing chemometrics with the tools of information sciences (CHESS) – MASIT23 ......................................................................................................................86 Modelling and simulation in software engineering (MoSSE) – MASIT24 ......................90 Innovative simulation method of multi-phase chemistry (InnoSim) – MASIT25 .....93 Development of the 3D power plant simulator – MASIT27 ..................................................95 Flow physics and modelling (FLOPHY) – MASIT28......................................................................97 Modelling interfacial partitioning in multi-phase systems (INTER) – MASIT29 ....... 102 Ice-structure interaction modelling and simulation (STRUTSI) – MASIT30 ............... 105 Automatic testing of control systems in the integration phase of intelligent mobile machines (TINAT) – MASIT31 ...................................................................... 110 Design and modeling of printable electronics applications (DEMOprint) – MASIT32............................................................................................................................. 113 Industrial application of PhaseField modelling (PhaseField) – MASIT33..................... 116 Qualitative methods in virtual design of machines (KVALIVE) – MASIT34 ................. 120 Combining simulation and optimisation with building draft and HVAC planning – MASIT35 ....................................................................................................................... 123 Annexes 1 The projects of the MASI programme................................................................................... 126 2 MASI steering group ........................................................................................................................ 137 Tekes Programme Reports in English ................................................................................................... 1388
    • 1 At the conclusion of the MASI programmeGeneral description Other factors in the changing op- In connection with the prepa- erational environment are illustrated in rations, a series of seminars were ar-Background and preparation for figure 1. ranged in which representatives of thethe programme In connection with the prelim- industrial and research communitiesTekes began to investigate the state inary investigation, interviews were were able to express their opinions onand needs of the modelling and sim- conducted with a wide range of rep- the programme’s key areas, as well asulation sector in Finland in 2004 with resentatives from Finnish industry and its orientation and emphases. On thea view to launching a national devel- research, and their opinions on the basis of its preparations in 2004, Tekesopment programme. The driving forc- programme’s necessity and relevance launched the Modelling and Simula-es behind the investigation included were surveyed. The investigation illus- tion Technology Programme (MASI) atthe considerable development of infor- trated the pressing need for a devel- the beginning of 2005. It was decidedmation and communication technolo- opment programme for the model- that the MASI programme would takegy and the resulting possibilities, tight- ling and simulation sector in Finland, so place over five years (2005–2009) wither global competition, and pressures to Tekes decided to begin preparations to an estimated total budget of 92 millionsave in consumption of energy and raw that end. euros, whereof Tekes’ contribution wasmaterials. estimated at half. Aims of the programmeFigure 1. Acting forces in the operational environment at the beginning of the MASI The key aims of the MASI programmeprogramme. were: • The widespread implementation in industry of modelling and sim- ulation • Innovation of modelling and sim- ulation processes • The creation of new commercial opportunities With its MASI programme, Tekes sought more diverse and more widespread use of modelling and simulation in Finnish industry. The strategic aim of the pro- gramme was to promote interdiscipli- narity and international co-operation, as well as networking between compa- nies and research bodies. 9
    • The goal was more rapid techno- 3. Development of services and busi- Timeline, scope and funding logical development in the range and ness processes: such as develop- As far as Tekes was involved, the pro- application of tools and methods. In ment of service and business ex- gramme was situated within a funding terms of the tools and methods of mod- pertise, use of modelling in deci- framework in order to define and lim- elling and simulation, a move in the di- sion making and in support of busi- it specific goals on the one hand, and rection of more extensive and com- ness management, addition of busi- the programme’s size on the other. For prehensive models was sought. The ness expertise, scenario calculation the programme’s whole five-year peri- aim was to combine various phenom- at various phases of the value chain, od a total budget around the 92 mil- ena-based models into a larger whole. and new methods from business lion euro mark was aimed for, where- This way they could be used to pro- studies for tangibly realising the of Tekes’ proportion would be an esti- duce more extensive and comprehen- benefits of modelling initiatives. mated 46 million euros. MASI success- sive solutions to the various problems 4. The use and productisation of fully achieved its overall aim, and even and processes in which the phenomena modelling in the simulation sec- surprised with the high demand for en- are expressed. Another aim was to ag- tor, utilisation of visualisation, crea- terprise projects. Final total funding for gregate phenomena-level, system-level tion of modelling services, market- the programme amounted to 98.3 mil- and decision making models, so that the ing, support for use, questions of re- lion euros. During the course of the knowledge of different sectors could be sponsibility and IPR issues. programme funding was allocated to more broadly utilised in problem solv- 104 company initiatives with a total ing and decision making. It was hoped A general criterion of the programme volume of 72.3 million euros, whereof that the co-operation offered by the was the attempt to create holistic re- Tekes’ funding contribution amounted MASI programme would result in syner- search endeavours which would pave to 31.8 million euros (43.9%). In terms of getic benefits and the results’ adoption the way for a stronger international po- public research, the programme fund- in Finnish business life. sition and improve the conditions for ed a total 35 projects, each of which, as the emergence of new expertise and joint ventures, were divided into sever- Areas of emphasis and co-operation. al subprojects. The total volume of re- funding for the programme Areas of emphasis The following areas of emphasis Figure 2. Distribution of funding to various projects according to size of enterprise, were chosen as premises for the pro- and Tekes’ funding shares for enterprise and public research projects. gramme’s preparation: 1. Models of phenomena and their combination: such as new models of phenomena, connecting of new and old models (reaction kinet- ics, biotechnology, materials, heat transfer, currents, stochastic meth- ods etc.) and co-ordination of phe- nomena levels. 2. Methods and tools of modelling: such as optimisation, data analysis, SOM, validation, programming, math- ematics, measurements, 4-D (time de- pendence), the model’s life span, visu- alisation and animation.10
    • Figure 3. Funding shares of different industries. Tekes’ funding covered 44% of the The programme’s trajectorytotal 72.3-million-euro volume of enterprise projects. and results The programme’s direction and project choices Funding share of enterprise projects in MASI programme Years 2005–2009, 72 million euros The steering group made up of business representatives provided direction on the programme’s emphases of content, 11,7 M international aspects, business needs, Energy and environment industries and perspectives in terms of various Mechanical engineering industries lines of business. It also proposed meas- 31,8 M Forest and chemical industries 13,1 M ures for realising the project. The steer- Telecommunication and electronics ing group took part in determining se- Other industry sectors lection criteria for research projects and Tekes share of funding deciding project selection policies in 7,6 M connection with funding applications. 7,3 M A programme team made up of0,8 M Tekes experts was charged with sup- porting the programme manager in funding decisions, selection of practical measures, and monitoring of projects. Asearch projects amounted to 26 million public research co-operation in- project manager and a project co-ordi-euros, with Tekes contributing 21.2 mil- itiatives were launched, whose nator nominated by Tekes implement-lion euros (81.5%). Figure 2 shows the steering groups were required to ed the practical measures determineddistribution of funding to large-scale include representatives of enter- by the steering group within the frame-enterprises (60 projects), small and me- prises, work of the co-ordination project.dium sized enterprises (44 projects), • utilisation of the results of researchand the proportions made up by pub- projects was promoted, as was the Enterprise fundinglic research (36 projects). The shares of emergence of companies offering At the beginning of the programmeTekes funding allocated to enterprises services in the new sector, in January 2005, an application roundand public projects are presented sep- • small and medium sized enterpris- directed at enterprises was opened.arately in the graph. Funding shares on es in particular were encouraged Thereafter enterprises had the oppor-an industry-specific basis are presented to broaden their expertise and to tunity to apply for funding for the en-in figure 3. adopt modelling and simulation tire duration of the programme. In en- methods and tools in their devel- terprise projects, the aim was to devel-Steps in the programme’s opment work, op modelling and simulation applica-realisation • seminars, workshops and net- tions, and to encourage implementa-In order to realise the aims of the pro- working events were arranged. tion of research results and new meth-gramme ods to meet the needs of business life.• product development initiatives A steering group comprising representa- were launched with companies tives from business life was established Research funding offering or utilising modelling and to direct the programme, and its task was Two research application rounds were simulation services, to issue guidance on the programme’s arranged for public research projects• wide-ranging and interdisciplinary strategic emphases and policies. in 2005 and 2007. Demand for fund- 11
    • ing was extremely high, which meant and further the spread of modelling ex- workshops were arranged to consider that only around 15% of project appli- pertise between different experts and particular issues in modelling and sim- cations were approved funding in the enterprises. During the course of the ulation. Training in project leadership first round. Research projects from the programme the emphasis was on pro- was arranged for the individuals re- first round were launched at the begin- moting commodification and exploita- sponsible for projects, alongside an in- ning of 2006. tion of research results and co-opera- troduction to Tekes practices, consid- Before the second application tion between enterprises. eration of the best approaches for uti- round, an interim evaluation of the pro- lising results, and specialist communi- gramme was carried out in the form of Seminars, workshops and events cations training with a view to making a web survey in order to adjust the em- Activities during the programme com- distribution of information more effi- phases of ongoing funding. The devel- prised activities internal to projects, cient. opment of instruments needed in busi- and joint programme activities. Re- Various functions and events were ness decision making was added to search projects operated and assem- arranged within the framework of the the programme’s list of priorities. The bled according to their own timelines. co-ordination project as follows: research round was carried out in two Work proceeded under the guidance phases. Applicants for ongoing funding of management groups and project Five annual seminars were given the opportunity to present leaders, in accordance with project • Opening seminar: Helsinki 2005 their aims for follow-up projects and re- plans and co-operation agreements. • Jyväskylä 2006 port results from the first phase to the Projects independently arranged in- • Tampere 2007 programme’s steering group and Tekes’ ternal workshops and reporting of re- • Vantaa 2008 programme team. In order to perfect sults in the form of an extended man- • Concluding seminar: Helsinki 2010 the programme, a further application agement group meeting, for example. round was established in which inten- They served as a productive forum for Eight subject seminars tions for new projects could be de- exchange of information and discus- • Validation 2006 clared. As a result of this intentions sion among business and researchers. • Multiobjective Optimization 2006 round, the second round for research The events were generally directed at • Global Optimization 2007 applications proper saw funding grant- parties who were involved in the initi- • Data, information and knowledge ed to around half of applicants. The ative. In many projects, active personal in chemical technology 2008 projects were launched at the begin- contacts between business representa- • Simulations for industry – Sim∫ind ning of 2008. tives and researchers played a key role 2008 In addition to Tekes’ ordinary fund- and clearly furthered exploitation of re- • Measurements and modelling 2008 ing conditions for research projects, sults later on. • Modelling and Simulation in projects were required to meet the pro- International co-operation took Finland and in USA 2009 gramme-specific conditions of at least place both within research projects • Virtual Reality and Remote three parties to research as well as re- and in the form of events organised by Operation Day 2009 alisation of an international dimension the programme and trips. during the period of the project. The The programme promoted inter- Four workshops projects were required to form a steer- action between bodies operating in • The state of computational fluid ing group comprising experts from in- the sector, and offered projects joint dynamics in Finland 2007 terested enterprises together with rep- events for exchanging up-to-date in- • Utilisation of modelling and resentatives from research bodies. The formation. The annual seminars were simulation 2007 purpose of these additional require- among the programme’s major events. • Interim evaluation 2007 ments was to increase the breadth of Around 160–220 individuals partici- • Future need for forums in the co-operation, promote innovative re- pated in the events. In addition to the modelling and simulation sults by combining areas of expertise, annual seminars, various seminars and sector 201012
    • Six project manager days were announced in the form of news- gramme. As one form, participation in• Tekes’ international activities 2005 paper advertisements and pro- different interest areas’ events was tri-• Project manager days 2005, 2006 gramme leaflets as well as Tekes news- alled in the form of briefings. Subjects & 2008 letters. Information related to the pro- were selected with the event organ-• Communications training 2007 gramme was distributed with the help isers. This opportunity for “precision of website, by sending newsletters presentations” of projects was market-Two area seminars and by publishing news magazines. ed to different parties, such as associ-• Tekes’ international activities and The web pages featured seminar pres- ations and enterprise representatives MASI, Pori 2005 entations, yearbooks and descriptions in meetings of the research projects’• Modelling in process industry, of research projects. The programme’s management teams. Lappeenranta 2006 mailing list stretched to over a thou- sand contacts. Subjects were market- Results and achievements of theThree fair pavilions and presentations ed to the press in the form of press programme• Technology Fair, Jyväskylä 2006 releases. In terms of the research By its very nature, the MASI programme• AIChE Annual Conference, Phila- projects, annual reports constituted was an extremely variegated entity delphia, USA 2008 a more detailed source of informa- producing expertise and expertise-in-• Subcontracting Fair, Tampere 2009 tion on the projects’ aims and achieve- tensive tools. As a result of the nature ments. The annual reports were pub- of the programme, tangible resultsActivities reflected the cross-sector na- lished in both printed form as part of and new achievements are distributedture of the programme. Each party was Tekes’ report series, and in pdf form on widely, and observation of benefits willinterested in quite detailed questions the MASI homepage online. take place over a longer interval. Mod-and expertise related to their own In connection with the annual elling and simulation are often ongo-needs. In the more general subject ar- seminars, projects were offered the op- ing processes for enterprises, result-eas interest focused on the key ques- portunity of a single oral presentation ing in constant development. The on-tions of modelling and simulation, and poster presentation each year. At going transfer of results into enterpris-such as validation, verification, validity the opening and concluding seminars, es’ expertise and elements of their op-of data and its representative render- the programme’s projects and sector’s erational systems makes measurementing, optimisation and – in some sec- enterprises were offered the opportu- of quantitative results almost impossi-tors – measurement and comprehen- nity to participate with their own stand ble. Qualitative results may be consid-sion of phenomena. Visualisation, vir- in small-scale fairs. Within the frame- ered instead.tual environments and presentation work of the project’s co-ordination,of results were all further subjects of participation in fairs took place three Programme activitiescommon interest. Around 40–60 ex- times in the form of an independent During the course of the MASI pro-perts typically participated in the pavilion presenting MASI. Enterprises gramme, several new patterns of co-seminar events, and around 20 per- and commercially interesting research operation emerged among various re-sons took part in the workshops and projects were offered the opportunity search groups, and between researchtraining events. Detailed needs were to present their products and expertise groups and enterprises at the nationalhandled in the projects’ own semi- at fair seminars. The research projects level. International co-operation alsonars, and they were also taken care of were responsible for the publication of increased. Behind the networking be-in connection with the projects’ eve- projects’ scientific results and for disser- tween various actors lay in part Tekes’ryday activities. tation works. requirement for research projects in Various strategies for commu- terms of their size, international co-op-Communications nicating the possibilities and results eration and enterprise participation.Funding application rounds and con- of modelling and simulation were The seminars, trips and other eventstent descriptions for the programmes brainstormed and trialled in the pro- organised as part of the programme 13
    • made meetings possible, and thereby The projects carried out by enter- Observations made the emergence of new contacts and prises in the MASI programme can be during the course of patterns of co-operation. With the help divided into development projects by the programme of the programme activities, it was pos- enterprises offering modelling services, sible to distribute information about and on the other hand projects by en- Investigations concerning general questions related to the sector, terprises utilising the services and ex- the sector and to inspect the trends in the devel- pertise in their own business. In both During the course of the programme, opment of operations. groups significant progress took place the views of researchers were heard in both the development of tools and and business representatives were in- Research projects methods and in relation to their utilisa- terviewed. The investigations carried The results of the research projects car- tion. According to the larger enterpris- out and the views of persons repre- ried out in the programme will be uti- es, more efficient, tailored applications senting the sector emphasised the lised by Finnish business life and enter- were adopted. In some projects re- MASI programme’s current relevance prises in phases, by way of the enter- search was carried out on adjusting the and its role in developing the Finn- prises’ own projects. The timespan for new methods to business, and infor- ish innovation environment. There are the utilisation of the results of research mation was applied to development of a number of particularities, but a few projects is 5–10 years on average. Never- holistic systems. Interest focused on, for matters have been singled out below. theless, a significant number of concrete example, service concepts, remote op- The MASI programme had an in- examples of enterprises’ utilisation of the erations and solutions for subcontract- vestigation carried out under the lead- results of research projects could already ing arrangements, as well as command ership of VTT Technical Research Cen- be seen during the programme. Prom- of the international market and optimi- tre of Finland’s research professor Ol- ising results and new finds reported by sation of one’s own processes. li Ventä, which evaluated the state of several business representatives indi- One aim of the MASI programme modelling and simulation in the key cate utilisation of modelling and simula- was the increased utilisation of model- fields of Finnish business. The investi- tion, as does the independent continu- ling and simulation, and their extend- gation mapped future challenges and ation of research projects by enterprises ed use as an everyday tool in Finnish in- perceived opportunities. following the programme. The research dustry and business irrespective of the During the MASI programme, the projects have found in their projects size of the enterprise. A large number USA’s National Science Foundation car- new focuses of development, which are of Finnish SMEs were indeed involved, ried out an investigation into the state funded through Strategic Centres for both in funding and following pub- of modelling and simulation in the Science, Technology and Innovation lic research projects, and in participat- United States and worldwide. The in- initiatives or as part of other national ing in activities with their own research vestigation group, led by professor Sha- programmes. This will guarantee that and development projects. Although ron Glotzer, visited several countries in research expertise in modelling and from a funding and numerical perspec- Asia and Europe. The results of the in- simulation continues to develop after tive, participation by SMEs was over- vestigation led to the January 2009 the programme, too. shadowed by the contribution of large- MASI seminar “Modelling and Simula- scale enterprises, the programme did tion in Finland and in USA”. The investi- Enterprise projects much to pave the way for the manifes- gation states, for example, that in future One of the programme’s key aims was to tation of its results in SMEs on a much modelling and simulation may come to create new business and services for the wider scale in coming years. Thus, the cover almost all areas of human activi- sector. One example of the realisation results in relation to SMEs were posi- ty, it will be cheaply available to all, and of this aim is the emergence during the tive, and several new enterprises inter- it will become an easy and efficient tool programme of new enterprises offering ested in utilising the innovations were set for all places. In other words, eco- modelling and simulation services. involved in the project. nomic competition will tighten as a re-14
    • Figure 4. Some of the MASI participants at AIChE conference.sult of the development of modelling ly on modelling and simulation exper- prepare for increased investment inand simulation. tise. Consequently, engineering scienc- the sector in future. New areas of rap- Modelling and simulation exper- es will also largely be built in future on id development include open sourcetise is especially sorely needed to re- modelling and simulation. Mathemat- service, economical parallel proces-solve the major challenges and com- ical modelling and computational sci- sors, visualisation devices, 3D devel-plex systems facing humanity, such as ences lay behind the development and opment, information exchange plat-climate change, production of alterna- expertise. forms for software, massive, fast-con-tive energies, environmental issues and According to VTT’s investigation, nection networks, etc. The possibilitiesdisease control. This expertise will offer in our key areas of industry we lie near offered by technological developmentabundant opportunities to those en- the very top, and in some areas we ac- for improving algorithm developmentterprises who are involved in the devel- tually lead. However, the operational and programming engineering willopment, and who are able to adopt the environment is constantly changing certainly offer a national competitivenew implements. Key areas of research, and with increasing speed. Although advantage to those countries that in-such as biology and medicine, ma- in individual sectors Finnish exper- vest in it. On the other hand, success-terial technologies and social scienc- tise lies at the very top in internation- ful modelling and simulation expertisees, as well as natural sciences, also re- al comparison, we still have reason to and its application are always based on 15
    • world-class expertise in each area of Training and creation of expertise Perhaps it would be worth con- application. On the basis of the investi- Many key issues emerged from the in- sidering a suitable requirement level gation, each area of application has no vestigation led by professor Glotzer, without expecting everything desira- shortage of challenging targets, which one of the most important of which ble in a “single package”. In future it will is why development needs on the one was the quality of modelling and simu- be worth paying greater attention to hand and opportunities on the oth- lation training in the United States and modelling and simulation expertise, its er are substantial. How we succeed in worldwide. According to the investiga- role and place in the Finnish education future depends solely on joint invest- tion, not enough experts are trained to system. From whence will enterprises ments and the activeness and exper- meet the requirements of the model- recruit their experts, how will they carry tise of enterprises. ling and simulation sector. The same out their own training in these subject situation can be seen in Finland. In areas, and how will development take Concern in discussions about many areas Finland leads the way in place? An operational culture increas- ongoing funding expertise, but the group of experts is ingly focused on subcontracting may On the basis of contacts, concern was nevertheless too narrow to spread the weaken understanding within enter- noted about the sustainability of re- benefits of modelling and simulation prises of the possibilities of modelling search funding in the sector following extensively enough across the indus- and simulation, and decrease commu- conclusion of the programme. Fund- trial and research sectors. The in-depth nication between actors which is based ing has been clearly directed towards knowledge demanded in the sector on needs. How to ensure the develop- the subject area in some Strategic Cen- was seen as a major problem. Exper- ment of expertise in enterprises already tres for Science, Technology and Inno- tise in modelling and simulation alone offering services, and preserve enter- vation programmes (Forest Cluster and is not sufficient, rather, comprehensive prises’ operational ability in the small FIMEC), but there is still reason to draw knowledge is needed of each special- domestic market? In enterprises’ strat- attention to funding of generic topics ist area. In thermodynamics or chem- egy and operational design, it is worth in the modelling and simulation sector. istry, for example, one needs strong considering modelling and simulation They may be excluded from funding expertise in the sector’s processes, as expertise and the future competitive when making choices based on short- well as preferably strong expertise in edge achieved with its help. term results or sector-specific criteria. the area of programming. When social Care should also be taken to maintain skills, language skills and other more communication between the academ- general business-related knowledge ic community and enterprises with re- is added to the list of employee crite- gard to issues in modelling and simula- ria, it is only natural that top-level ex- tion. This should be taken into account perts are rare. when developing a new higher educa- tion system.16
    • 2 Research projectsMultiobjective optimization and multidisciplinary decision support – MASIT01Objectives in nonlinear multiobjective optimiza- support (JYU, HSE, TUT). Even thoughStrategic, operative as well as decision tion and multiple criteria decision mak- each of these research units did havemaking in general necessitates taking ing. Because the interests of these re- its own goals they all did share much inseveral conflicting criteria simultane- search units are highly overlapping it common. The objective of this projectously into account. When dealing with has been convenient to share experi- was to find areas where knowledge cancomplex problems this requires appro- ences and do research in tight collabo- be shared in such a way that researchpriate decision support tools. By multi- ration. Each research unit has lots of ex- in each unit was supported by the oth-objective optimization, we mean find- perience and knowledge related to op- er units. For example, application cen-ing the best solution in the presence of timization, modelling and applications tred research units (UKU, TKK, TUT) of-several conflicting criteria. Tools of mul- and, thus, all these strengths have been fered valuable real world problems andtiobjective optimization enable con- combined in the project. inspiration to units that were workingsidering complex problems and inter- The core of the research has been with more general methods and toolsdependencies in them as entirenesses built around computationally demand- (HSE, JYU). On the other hand, thesewithout artificial simplifications. ing multiobjective optimization and general methods and tools were used Interactive multiobjective optimi- multiple criteria decision making. The to solve application problems.zation methods provide a decision mak- central goal of this project was to de- In addition to cooperative re-er a possibility to learn about the inter- velop new decision support approach- search, the aim of the project was inrelationships between the criteria and es and multiobjective optimization sharing of the obtained knowledge re-direct the solution according to her/his methods designed especially for com- lated to multiobjective optimization inpreferences. Unfortunately, commercial putationally challenging nonlinear and general. In this way, the companies in-optimization software packages con- mixed integer problems. In all develop- volved were given a great opportuni-tain no such methods. Practical expe- ment, the focus has been on methods ty to learn how multiopjective optimi-rience has shown a need for computa- and tools that are as application inde- zation methods can be utilized to im-tionally efficient methods in both non- pendent as possible. This makes it pos- prove their individual goals and appli-linear and mixed-integer problems with sible to extend the results of this project cation specific processes.multiple objectives. to a variety of other application branch- This project did consist of five re- es of multiobjective optimization. Resultssearch units at the University of Jyväsky- Research in this project was related The main results of the project are newlä (JYU), Helsinki School of Economics to real world applications in the fields methods and approaches that are doc-(HSE), Helsinki University of Technolo- of energy (TKK, UKU), mechanics (TUT), umented in over 40 publications rang-gy (TKK), Tampere University of Tech- and radiotherapy (UKU), and, on the ing from scientific articles and pro-nology (TUT) and University of Kuo- other hand, to software tools (JYU) and ceedings papers to technical reportspio (UKU). These units share an interest general purpose methods for decision and other scientific publications. Dur- 17
    • ing the project, research units also pro- doctoral dissertation titled “Reference optimization problems that are signifi- duced three doctoral and two other ac- point based decision support tools for cant to the companies. This co-opera- ademic degrees. The results of the re- interactive multiobjective optimization” tion, where actual design problems are search were presented in over 40 pres- describes the results obtained. solved, shall continue after this project. entations given in different internation- Two doctoral dissertations with ti- At UKU, for the first time, an in- al and national conferences or semi- tles “A systematic procedure for analy- teractive multiobjective optimization nars. In what follows, we shortly high- sis and design of energy systems” and method was employed in radiotherapy light some main results and related col- “Modelling biomass-fuelled small-scale treatment planning model based on laboration. CHP plants for process synthesis opti- Boltzmann Transport Equations (BTE). In At JYU, a new intelligent decision misation” describe the results obtained addition, interactive multiobjective op- support system (based on the inter- at TKK. In addition to these, also a new timization was used also to internal ra- active NIMBUS method and its imple- method for heat exchanger network diotherapy, brachytherapy, and our ap- mentations IND-NIMBUS and WWW- synthesis was developed. Together with proach was tested with clinical exam- NIMBUS produced in earlier projects) JY and HSE a tool that integrates IND- ples (at Kuopio University Hospital). In were developed and applied to appli- NIMBUS-software and GAMS-modelling both cases results are highly promising. cation areas of UKU and HUT. This new system was developed. With this tool, This research was made in collaboration system design was extended with de- GAMS can be used to solve multiobjec- with JY and HSE. Furthermore, UKU de- cision support tools developed in col- tive optimization problems interactive- rived depth-averaged flow and ener- laboration with HSE. The decision sup- ly. The method was used in synthesis of gy equations for plate heat exchanger port system developed at JYU did play heat exchanger network problems. Ad- modelling. These are used to optimize a crucial role in the project, because it ditionally, the method was used with different plate geometries using single offered an interface which did make multiple objectives to optimize oxyfu- and multiobjective optimization. After possible to utilize the developed meth- el power plant concepts. optimization, the most interesting ge- ods in solving the application problems. At TUT, a general algorithm for ometries can be investigated with more In addition, JYU did also lots of meth- finding the Pareto optimal solutions of accurate 3D modelling and experimen- od development and international re- multiobjective mixed integer problems tal measurements. search collaboration which had a great was developed. The algorithm was ver- impact on research made in the other ified by solving a number of mathe- Publications research units. matical test problems having distinct Summary of essential publications At HSE, the emphasis was on gen- properties. Furthermore, structural de- Eskelinen, P. 2008. Reference point based eral method development in tight col- sign applications associated with truss decision support tools for interactive laboration with JYU and internation- optimization were formulated and multiobjective optimization, Doctoral al researchers. As an example, meth- solved by the algorithm. The results dissertation, A-334, Helsinki School of ods based on trade-off information from the preliminary testing provided Economics, Helsinki. were studied with JYU and related to ideas for enhancing the algorithm fur- Eskelinen, P., Miettinen, K., Klamroth, K. this, experiences were exchanged with ther to make it computationally more & Hakanen, J. Pareto Navitagor for UKU. Also a new innovative interactive effective. During the algorithm devel- Interactive Nonlinear Multiobjective method was developed where the de- opment, experiences were exchanged Optimization, OR Spectrum, to appear. cision maker is allowed to navigate in with JYU and TKK. As the knowledge on Klamroth, K. & Miettinen, K. 2008. the Pareto optimal solution set of a mul- computational algorithms for mixed in- Integrating Approximation and tiobjective optimization problem and teger problems has gradually increased, Interactive Decision Making in explore potential solution alternatives. co-operation with some of the indus- Multicriteria Optimization, Operations A version of this method was integrated trial partners of the project has been Research, 56(1), 222-234. into the IND-NIMBUS environment. The started by identifying and formulating18
    • Lyytikäinen, M., Hämäläinen, T. & HDR Brachytherapy, Reports of • SWECO Marine Oy Hämäläinen, J. A fast modelling tool the Department of Mathematical • Patria Aerostructures Oy for plate heat exchangers based Inaformation Technology, Series B, • Wärtsilä Finland Oy on depth-averaged equations, Scientific Computing, No. B 14/2008, • Fortum Oyj International Journal of Heat and Mass University of Jyväskylä, Jyväskylä. • Kuopio University Hospital Transfer, to appear. Savola, T. 2007. Modelling Biomass-Fuelled • Metso Power OyMela, K. 2006. Algoritmi Small-Scale CHP Plants for Process • M-real Oyj, Andritz Oy monitavoitteisen epälineaarisen Synthesiss Optimisation, Doctoral • Foster Wheeler Energia Oy sekalukuoptimointitehtävän Dissertation, TKK Dissertations 75, • PA Consulting Group Oy, ratkaisemiseksi. Diplomityö, Espoo. • Varian Medical Systems Finland Oy Tampereen teknillinen yliopisto, Tveit, T.-M. 2006. A systematic procedure Tampere. for analysis and design of energy Contact informationMela K., Koski J. & Silvennoinen, R. systems. TKK Dissertations 27, Helsinki Kaisa Miettinen 2007. Algorithm for generating the University of Technology, Espoo. University of Jyväskylä Pareto optimal set of multiobjective Tel. +358 50 373 2247 nonlinear mixed-integer optimization Project volume kaisa.miettinen@jyu.fi problems. In Proceedings of 3rd AIAA For time perioid 1.8.2005–31.12.2008 http://venda.uku.fi/research/paperphysics/ Multidisciplinary Design Optimization the total funding has been 1 149 325 € hyvatietaa/ Specialist Conference. Honolulu, USA. where Tekes share has been 1 038 000 €Ojalehto, V. 2008. Näkökulmia monitavoiteoptimoinnin NIMBUS- Project participants menetelmän eri toteutuksiin, pro • University of Jyväskylä gradu -tutkielma, Jyväskylän yliopisto, • Helsinki University of Technology Jyväskylä. • Helsinki School of EconomicsRuotsalainen, H., Miettinen, K., Palmgren, • Tampere University of Technology J.-E. & Lahtinen, T. 2008. Interactive • University of Kuopio Multiobjective Optimization for • Danfoss Oy 19
    • Symbiosis between plant and computational models (Simbiot) – MASIT02 Abstract International cooperation Halmevaara, K. & Hyötyniemi, H. The aim of the Simbiot project is to • August 2005: A two-day plant Dynaamisten simulointimallien find a plant model and software com- modelling seminar on the ISO parametrien virittäminen data- ponent based approach to compu- 15926 standard. pohjaisilla tilastollisilla menetelmillä. tational models in process industry. • October 2005: The project Automaatiopäivät 2007. Suomen The approach should work for mod- assisted the Automation Society automaatioseura, 2007. (in Finnish) els in different levels of details. Integra- in organising an OPC Theme Day. Halmevaara, K. & Hyötyniemi, H. Managing tion with plant modelling means that • October 2006: The 2006 OPC UA Complexity in Large Scale Control the computational models will be in- theme day. Systems. Proceedings of the 1st IFAC tegrated part of the other information • November 2006: A one day Workshop on Applications of Large model of the plant i.e. they can be ini- seminar on the current status of Scale Industrial Systems (ALSIS). tialized from the information model of plant model standardisation. Helsinki – Stocholm, 30–31 August the plant and they can produce results 2006. to the same information model. Soft- In November 2005 and in December Halmevaara, K. & Hyötyniemi, H. ware components are used in order to 2006 the project organised an industri- Simulointiavusteinen prosessien achieve modular and extensible frame- al workshop on multi-scale modelling. suorituskyvyn optimointi – Iterative work. Different levels of details are ana- The project has participated in the Regression Tuning. Automaatiopäivät lysed and methods for multiscale/mul- standardisation work of the data trans- 2005, Suomen automaatioseura, 2005. tiphysics modelling are defined. The fer models of the Standardisation Cen- (in Finnish) main result of the project is an open on- tre for the Process Industry. Halmevaara, K. & Hyötyniemi, H. Tuning tology based modelling and simulation of multi-parameter systems using environment where information con- Publications multivariate regression and numerical tent can be modeled using a relational Halmevaara, K. & Hyötyniemi, H. 2005. optimization methods. Proceedings graph based data model (RDF) and sim- Performance Optimization of Large of the 6th International Conference ulation engines and components can Control Systems – Case study on a on Intelligent Processing and be integrated to the same environment. Continuous Pulp Digester. Proceedings Manufacturing of Materials (IPMM). The project was divided into six of the 15th IFAC World Congress, Salerno, Italy, 25–29 June 2007. work packages: Prague. Huhtanen, R., Hänninen, M. & Pättikangas, • Environment for development Halmevaara, K. & Hyötyniemi, H. T. 2007. Coupling of Computational and use of virtual models (WP 1) Application of Elastic Intuitions to Fluid Dynamics Codes with System • Linking of the companion model Process Engineering. Proceedings of Codes: A Case Study, VTT Research solver to the environment (WP 2) the 9th Scandinavian AI Conference Report VTT-R-00742-07. Espoo, • Iterative Regression Tuning (SCAI). Espoo, 25–27 October 2006. Finland, 13 p. method (IRT) (WP 3) Halmevaara, K. & Hyötyniemi, H. Data- Karhela, T. & Kuikka, S. Prosessilaitoksen • CFD and structural analysis (WP 4) based Parameter Optimization elinkaarenaikaisen tiedonhallinnan • Application of phase field of Dynamic Simulation Models. palvelukehys (Framework for process approach to industrial flow Proceedings of the 47th Scandinavian industry plant’s life-cycle information calculation (WP5) Conference on Simulation and handling). Automaatiopäivät 2005, • WP6 for project administration Modelling (SIMS). Helsinki, 28–29 Suomen automaatioseura, 2005. and coordination September 2006. (in Finnish)20
    • Laurila, T., Tong, C., Huopaniemi, I., Villberg, A. 2007. Design Challenges of Project participants Majaniemi, S. & Ala-Nissila, T. 2005. an Ontology based Modelling and • VTT Technical Research Centre of Dynamics and Kinetic Roughening of Simulation Environment. Master’s Finland (semantic models, large scale Interfaces in Two-Dimensional Forced Thesis, HUT. process simulation, CFD-modelling and Wetting, Eur. Phys. J. B 46, p. 553–561. Villberg, A., Lehtonen, T., Kondelin, K. simulation)Lehtomäki, M. 2007. Dynaamisen & Karhela, T. Applying Semantic • Helsinki University of Technology simulaattorin parametrien Modelling Techniques in Large Scale (optimization, multi variable methods, datapohjainen virittäminen käyttäen Process Simulation. IFAC Workshop on statistical mechanics, phase-field rekursiivista lineaarista mallinnusta. Applications of Large Scale Industrial models) Diplomityö, HUT. (in Finnish) Systems (ALSIS). Helsinki – Stocholm,Pättikangas, T., Manninen, M., Ilvonen, M., 30–31 August 2006. Contact information Huhtanen, R. & Luukkainen, M. 2006. Tommi Karhela Symbiosis Between Computational Project time scale VTT Technical Research Centre of Finland Fluid Dynamics and Plant Models. 1.1.2005–31.12.2006 Tel. +358 40 582 2274 VTT Research Report VTT-R-08582-06, tommi.karhela@vtt.fi Espoo, Finland, 32 p. Project volumeSaukkonen, M. 2006. Hydrodynamic Tekes, VTT, Fortum Nuclear Services, Modeling of Two-Phase Flows under Jaakko Pöyry, Intergraph Finland. Non-Equilibrium Conditions. Master’s Total funding 686 000 €, Thesis, TKK. Tekes share 500 000 €Villberg, A. & Karhela, T. Solving Matrix Equations in Large Scale Dynamic Simulation of Flow Networks. Mathmod 2006. The 5th International Conference on Mathematical Modelling. February 2006, Vienna, Austria. 21
    • Inverse problems and reliability of modelling – MASIT03 Background Results of the projection is unknown. From the The accuracy of modelling is always MCMC applications: estimating pa- theoretical point of view it has been limited. This is due to the idealiza- rameters and noise. Lappeenran- studied under which conditions the tions in the model itself, and due to ta University of Technology. The re- projection orientations are uniquely re- errors in measurement that are need- search in the Lappeenranta University coverable from ideal noiseless projec- ed to calibrate the model against re- of Technology group focuses on nov- tions. The practical question is how to al data. A proper estimation of the im- el methods in computational statistics, recover them given a set of noisy pro- pact of noisy data is most often ham- and promotes the use of them in prac- jection images from a real experiment. pered by the fact that the phenomena tical industrial applications. For a safe in- A new method of recovering the pro- studied are nonlinear, while the stand- terpretation of modelling results, the er- jection orientations has been proposed. ard statistical theory employed only is ror bounds of the predictions should be A similar method has been considered valid for linear models. Medical imag- determined. For nonlinear models, this in a simpler case, with dimensionality ing, industrial flows or remote sensing only recently has become possible with reduced by one, i.e. with two dimen- provide some typical application areas the advent of new statistical sampling sional objects and one dimensional of inverse problems. Recognizing and methods, especially the MCMC (Markov projection. In this simpler case a nec- solving an inverse problem is a radically chain Monte Carlo) methods. We stud- essary and sufficient condition under broader topic than standard parameter ied adaptive methods by which, under which the projection orientations can fitting, particularly since the problems given a priori knowledge, the error var- be recovered from the geometric mo- are typically ill-posed. iance may be estimated by sampling it ments of the images has been proven. together with the unknown parameter This result considerably strengthens the Objectives vector of a model. The methods have previously published results. Recently, new computational tools applied to industrial applications on Process tomography and mod- have emerged in this field, but they various fields, as suggested by the col- elling of approximation errors. Uni- have not yet been transferred to com- laborating and funding companies: log versity of Eastern Finland, Kuopio mon use. This project aimed to improve tomography, numerical modelling, de- campus. The focus of the research has this situation on a number of industrial- sign and optimization of heat exchang- been on modelling and compensation ly important applications. A special fo- ers, forest inventory by laser scanning. of approximation errors and on com- cus is on quantitative estimation of un- Several ongoing PhD studies continue putational methods related to tomo- certainties of prediction, due to both this work after the MASI project, many graphic imaging. The approximation modelling errors and noisy data. funded by the interested companies. error methods were applied to several Reconstruction of virus struc- linear and nonlinear test cases, for ex- Project implementation ture from cryo electron images. Uni- ample, dealing with errors due to nu- The project was carried out as co-op- versity of Helsinki. The purpose of the merical discretization and/or uncer- eration of five different universities and project was to develop methods to re- tainties caused by unknown parame- the Finnish Meteorological Institute. construct the scattering density func- ters in the model. We have also stud- Each of the research groups has suc- tion of a virus particle given data from a ied the modelling of approximation er- cessfully developed novel approaches cryo electron microscope experiment. rors due to the truncation of computa- in their planned tasks. Because the orientation of the virus par- tional domain in an application relat- ticle on the stage of the microscope is ed to electrical geophysical tomogra- unknown, it follows that the orientation phy. As a result, the dimension of the22
    • inverse problem can be reduced if the These coordinates can be determined ware for simulating the radar responsesapproximation error resulting from the by available imaging methods. Anoth- corresponding to arbitrary modulationdomain truncation is modelled and tak- er line of research has been the study of patterns. The planned radar echo sim-en into account in data processing. Re- Gaussian beams, which are waves that ulator has been completed. The simu-cently we have studied the use of sta- are always concentrated around one lator can be used for studying nov-tistical and approximation error meth- point in space. Such waves could, for el radar modulation and analysis prin-ods in a “source inversion” problem in example, be acoustic, electromagnetic, ciples. The goal has been to study thewhich the objective is to characterize or seismic. An attractive feature of Gaus- performance of the SMPRF modulationthe source of some (possible hazard- sian beams is that the equations gov- principle. This is currently being workedous) substance based on remote sens- erning their propagation are much sim- on together with Eigenor Oy. The newing measurements at different time in- pler than the full wave equation: Gaus- methods allow simultaneous measure-stants. In the field of process tomogra- sian beams propagate along charac- ment of all ionospheric regions, spacephy the focus of research has been on teristic curves. The second subproject debris, and meteor head echoes.electrical impedance tomography (EIT). was modelling of complex kinetics sys- MCMC methods for model se-We have studied non-stationary three- tems. The first target has been simula- lection. Finnish Meteorological In-dimensional imaging, optimization of tion of metabolic processes in the hu- stitute. Finnish Meteorological Institutecurrent injection patterns, estimation man body. The main accomplishment studied sampling methods (Reversibleof velocity fields and the use of a nov- of this subproject is the release of the Jump MCMC) that help to select be-el electrode configuration. The objec- simulation tool called Metabolica. tween different modelling options. Thetive has been to develop on-line data Linear inverse problem solver, methodology was successfully appliedprocessing methods for industrial tom- weather radar simulation software. to remote sensing satellite data pro-ographic applications. Sodankylä Geophysical Observato- duced by the GOMOS instrument on- Wave equation, complex kinet- ry. FLIPS (Fortran Linear Inverse Prob- board ENVISAT satellite. GOMOS pro-ics systems. Helsinki University of lem Solver) is a Fortran95 module de- duces concentration profiles for vari-Technology. The research has con- veloped to solve large (especially over ous gases in the atmosphere by inver-centrated on two topics: direct and in- determined) statistical linear inverse sion of the measured occultation data.verse problems for the wave equation problems. FLIPS was from the start de- The problem of model selection is toand modelling of complex kinetics sys- veloped to be able to handle large scale determine to which extent various gas-tems. A new algorithm was developed problems, so extra attention was paid es may be inverted and how the aero-that focuses the energy of a wave using to the memory management and low sol should be modelled. All the modelsiteration of measurements. Such tech- memory footprint. It is possible to feed are approximations that depend on thenique can be used, e.g., to heat up an the data into FLIPS piece-by-piece to assumed particle size distributions, vol-object by generating a heat source lo- keep the memory consumption as low cano activity etc., which are unknowncated at a point inside the object. The as possible. Another feature of FLIPS in- beforehand. The final result includes thealgorithm has many potential appli- clude the possibility to marginalize un- model uncertainty and several accept-cations. For example, one could use it knowns or add new unknowns at any ed models can be averaged to produceto heat a cancer, while leaving the sur- point of the operation, and the ability more realistic model predictions. Arounding tissue unharmed. The main to delete data that was already fed into computer code that implements RJM-advantage of this algorithm is that it the system. FLIPS is currently used in the CMC was created during the project.does not require much information new EISCAT data analysis system for find- It essentially depends on the adaptiveabout the properties of materials inside ing the ionospheric plasma parameters MCMC methodology that has been de-the object: To focus the wave to a point from the incoherent scatter radar meas- veloped together with the LUT groupone only needs to specify the geodes- urements. The goal of weather radar before, and extends that methodologyic coordinates for that particular point. simulation software is to develop soft- to the model selection problem. 23
    • Figure 1. Automatic forest segmentation by laser derived features. Laine, M. & Tamminen, J. 2008. Aerosol model selection and uncertainty modelling by adaptive MCMC technique, Atmospheric Chemistry and Physics, 8(24), pages 7697–7707. Seppänen, A., Voutilainen, A. & Kaipio, J.P. 2009. State estimation in process tomography – reconstruction of velocity fields using EIT, Inverse Problems 25:085009. Virtanen, I. I., Vierinen, J. & Lehtinen M.S. 2009. Phase coded aperiodic transmission sequences. Annales Geophysicae. Project time scale 1.1.2008–31.12.2009 Project volume Total 681 774 €, Tekes share 562 000 € Project participants • Lappeenranta University of Technology Commercial impact, Dissemination most precise method available. The LUT • Finnish Meteorological Institute Several of the methods developed in group featured on the main TV news of • University of Helsinki the project have been taken to indus- YLE just before the Copenhagen Cli- • Helsinki University of Technology trial or operational use, for example in mate Conference with this theme. • University of Eastern Finland, applications in remote sensing, chem- Kuopio Campus ical engineering, engineering mechan- International cooperation • University of Oulu ics or virtual design of machines As an The project participants belong to the • Sodankylä Geophysical Observatory example, MASIT03 has had a significant Centre of Excellence in Inverse Problems, impact on the development of for- Academy of Finland, with extensive na- Contact information est inventory services at Arbonaut Ltd. tional and international collaboration. Heikki Haario Through algorithms originally invented Lappeenranta University of Technology in this project, Arbonaut has become Most essential publications Tel. +358 400 814 092 the market leader in operational for- Dahl, M. F., Kirpichnikova, A. & Lassas, M. heikki.haario@lut.fi est inventory in Finland, and is about to 2009. Focusing waves in unknown www.lut.fi/mafy assume that same position in Sweden media by modified time reversal in the course of 2010. Apart from for- iteration, SIAM Journal on Control and est inventory for timber sourcing, an- Optimization, 48:839–858. other application of the same meth- Ketola, J. & Lamberg, L. An algorithm ods has emerged in the fight against for recovering unknown projection climate change. The Sparse Bayesian orientations and shifts in 3-D method for measuring forest biomass tomography. (to be published in developed in MASIT03 is currently the Inverse Problems and Imaging)24
    • Multiphase chemistry in process simulation – MASIT04Objectives Methods ResultsThe goal of the VISTA project was to im- Generic methods for coupling the ther- Generalprove performance in both metals and modynamic multi-phase approach with In the VISTA project Åbo Akademi Uni-materials processing, in power produc- computational fluid dynamics (CFD), re- versity, TKK, University of Oulu and VTTtion and paper manufacturing by im- actor and process simulations were de- have jointly developed new advancedplementing generic free energy meth- veloped. Force balance and Gibbs free methods to utilize rigorous multi-phaseods into process simulators. The specif- energy minimisation techniques were chemistry in industrial process models.ic applications included solid-gas dep- used together with flow simulation to The models provide improved perform-osition models in heat recovery boilers, predict multi-variant operation win- ance in both metals and materials man-casting and processing of steel and al- dows for high-temperature process- ufacturing, in power production and pa-loys, reactions in gasification and flash es. Multi-phase reactors in flow condi- per manufacturing technology. The par-conditions and simulation of aqueous tions were calculated by using the con- ticular applications are listed as follows:process chemistry and fibre suspen- strained free energy method. Interfac- • predictor model for flash smeltersions. The project was targeted to im- es and databases for the use of multi- heat recovery boiler depositionsprove present simulation programs component streams in process flow- • nitrogen/argon switch control forwith new algorithms and data as well sheet simulation were developed. steel converteras to create entirely new commercialsoftware products.Figure 1. Use of multi-phase Gibbs energy models in advanced process simulation. 25
    • • inclusion trajectory predictor for Figure 3. Particle trajectories with chemical composition in flash smelter heat recovery steel-making boiler. • multi-phase chemical balance & pH simulator for forest industry • release and dissolution of gases in boiler water and desalination • black liquor flash gun simulation and boiling point elevation predictor • new software products for commercial and engineering use Scientific and technical progress In addition to the practical industrial ap- plications, a number of methodical ad- vances have been developed, which combine various physical and chem- ical phenomena into industrial ‘multi- physics’ process models. These include use of coupled thermochemical parti- tion of inclusion trajectories in bloom data can be incorporated to a visual cle growth and CFD models combined casting of steel with and without elec- ‘virtual reality’ animation, which can be with a physical fouling model, calcula- tromagnetic stirring, a combined ther- used to support decision-making both modynamic and CFD model for nitro- in process design, technology market- gen/argon blow in steel converters, ing and plant management. Figure 2. Calculated particle paths coupling bubble growth and nozzle In VISTA project, two software with electromagnetic stirring (right) flow modelling for splashplate spray of products for such commercial uses, viz. in the bloom caster and without black liquor and combination of mul- AFROK for rotary kilns and CheMac for electromagnetic stirring (left). tiphase chemistry to flowsheeting boil- pulp washing and bleaching has been er/evaporators. created. In addition, the ICA model, In several applications the minimi- which combines multi-phase thermo- sation of Gibbs free energy was used for dynamics with simulation of steel solid- the multi-phase equilibrium chemistry ification is in a semi-commercial stage and thermodynamics. An entirely new of development. New unit operations approach using immaterial constraints with advanced features have been in- in the free energy minimisation was in- cluded in the flowsheet routines Apros troduced. The advantage of thermody- and Balas. namic in calculation of process chemis- try is their abundant state property da- Impact of VISTA project ta, which is practical in validation of in- The commercial utilization of the dustrial models. Use of state properties project results has commenced in two in process simulation further improves directions. First, simulation models can model reliability and reduces or elimi- be used to improve performance and nates need of expensive trial runs and productivity of mill-scale processes. In pilot-experiments. The comprehensive steelmaking, the consumption of ar-26
    • Figure 4. Non-condensable components in flashing vapour of the desalination gon is the second highest operation-process. Calculation with (CA) and without free energy data. al cost of the mill, and it is estimated that savings exceeding 0.6 M€/year can be achieved by cutting its unneces- sary use. The other example closely re- lated to this project is an average pa- per mill, where raising the operation- al factor by one per cent corresponds roughly +1 M€ increase in annual turn- over. Model supported scale-up and choice of equipment materials usual- ly give even larger benefits. Secondly, combining multi-phase chemistry with CFD and flowsheet routines creates new opportunities for knowledge in- tensive software products and services. As the expertise developed in Fin- land in multi-phase process simulation is world-wide competitive, internation- al sales of such software products may be expected. The simulation models al- so support marketing of technology export in process, energy and environ-Figure 5. Development of new software products (VTT, Process Flow Oy). mental industries. The Constrained Free Energy method (CFE), developed by VTT’s re- searchers in VISTA project and pub- lished in 2006, was given the Best Paper Award of the Calphad Journal in Penn- sylvania State University in May 2007. Under the auspices of the VIS- TA project, M.Sc. Peter Blomberg has worked as a a research exchange stu- dent in Massachusetts Institute of Tech- nology to combine the CFE method with an MIT-based transformed Gibbs energy calculation method particular- ly focused on the thermodynamics of biochemical processes (MASIT25 – In- nosim). 27
    • Figure 6. CALPHAD Journal Best Paper 2006 award for VTT’s VISTA research. Project time scale 1.4.2005–30.6.2008 Project volume 1 512 000 €, Tekes share 1 084 800 € Project participants • VTT • Åbo Akademi University • TKK • University of Oulu • Process Flow Oy Ltd • SimTech Oy Project manager Pertti Koukkari VTT Technical Research Centre of Finland, Process Chemistry Tel. +358 40 583 4092 pertti.koukkari@vtt.fi Dissemination Koukkari, P. & Pajarre, R. 2006. Calculation The project results have been present- of constrained equilibria by Gibbs Additional information ed in 23 scienteific papers and interna- energy minimization, Calphad. Vol. 30 Pekka Taskinen tional conference presentations. Two in- (2006), 18–26. VTT Technical Research Centre of Finland ternational seminars were held in Fin- Li, B., Brink, A. & Hupa, M. 2009. CFD Tel. +358 40 558 4954 land on VISTA topics. investigation of deposition in a heat pekka.taskinen@vtt.fi recovery boiler: Part II - deposit growth Selected publications modelling. Progress in Computational Brink, A., Li, B. & Hupa, M. 2009. CFD Fluid Dynamics, 9(8), 453–459. investigation of deposition in a heat Riipi, J. & Fabritius, T. 2007. Surface recovery boiler: Part I - a dual layer tension of liquid Fe-N-O-S alloy, ISIJ particle conversion model. Progress in International, 47, No 11, 1575–1584. Computational Fluid Dynamics, 9(8), 447–452. Järvinen, M., Kärnä, A. & Fabritius, T. Detailed numerical modelling of gas- liquid and liquid-solid reactions in steel making processes, Scanmet III, 3rd International Conference on Process Development in Iron and Steelmaking, 8-11 June 2008, Luleå, Sweden. Volume I, p. 347–355.28
    • Statistical phenomena in virtual design of machines (MARTSI) – MASIT05Background ic equations. Real-time simulation allows ObjectivesExisting off-line simulation and visuali- the work environment to be altered. The The goal of the current project is to cre-zation tools for R&D of machines ignore impact of operator response and per- ate operational models that would per-statistical effects caused by users and formance on the stochastic perform- mit stochastic effects to be consideredwork processes. Statistical tools can be ance of a mechatronics machine can be in the simulation of a mechatronics ma-used to evaluate the performance data measured. This would be impossible or chine. A foundation for achieving theseobserved during the simulations. Statis- at least very time consuming, in tradi- goals is the development of real-timetical representation of the data will bet- tional off-line simulation. The real-time simulation tools and methods that canter portray the machine usage over a models must, of course, be sufficiently be used to simulate a machines per-longer period of operation. To make this realistic such that feedback from opera- formance over a longer period of oper-possible a general framework for the im- tion can be used in the product design ation. Real-time simulation will be usedplementation of real-time simulation as process. All significant aspects of the to take into account certain stochasticpart of the product design cycle is re- machine’s operation must be modelled like variations between operators. It isquired. During real-time simulation the in order to be useful in assessing the clear that the driver forms a systemicmachine operator is directly connect- overall reliability of the machine. The process with the machine according toed to the simulation model. The simula- interface between operation and real- his sensory motoric skills and thus thetion can take into account the user feed- time model must be realistic to insure overall dynamics of the human-ma-back before the first physical prototypes that the operator responses and com- chine system is determined by the sub-are manufactured. This is a challenging mands are representative. This requires systems and their interconnections astask because the dynamic machine op- both visual sensing, but also sound shown in Figure 1.eration is then connected to subjective and motion which can be provided byoperator rather than a set of mathemat- means of a motion base.Figure 1. Interconnections between subsystems in a human operated machine. 29
    • Figure 2. Real-time simulator of a log crane. • Real-time simulation implementation in product development Results Stochastic Input Variables for Multibody Dynamic Simulations The crucial and of key importance as- pect of MBD simulations is the external forcing representation in time-domain. This representation is necessary for pre- diction of fatigue reliability of virtual complex mechanical system. Current methods used to formally assess uncer- tainties include Monte Carlo (MC) sim- ulations, and linear and nonlinear ap- proximations of the system response. MC approach is costly and the accura- cy of the estimated statistical proper- ties improves with square root of the number of runs. Statistical linearization and nonlinear approximation methods compute several parameters but do not capture essential features of the nonlin- The proposed final goal of devel- same time being able to characterize ear dynamics (as revealed only by spec- oping a framework for the implemen- the stochastic operation of a machine tral analysis). tation of real-time simulation as part during its life cycle. There are two main methods pro- of the product design cycle will be re- posed for quantification of stochastic fined with the use of statistical meth- Project implementation input parameters (uncertainties). The ods for defining machine work cycles. The goals of the project were achieved first methodology was developed for Expected work cycles can later be fur- by means of a series of work packages treating complex loading spectra, and ther evaluated by means of off-line as shown below. named as Rainflow Analysis and Hidden simulation. A demonstration simulator • Real-time operating environment Markov Chains. The method for find- for a log crane (see Figure 2) was de- development ing Markov model or a hidden Mark- veloped in LUT. – Rigid body modelling ov model that fits a measured rainflow The goal of the project can be con- – Flexible body modelling matrix has been derived. This estimat- densed into an optimization problem. – Modelling of mechatronics ed model can be used for generation of The goal is to minimize the number components load sequences for fatigue evaluation. of required off-line simulations which – Motion sensing development The Markov method originally used for maximizing the reliability of the simula- – Distributing computing simulation and approximation of real tions that are performed. This presents – Development in real-time load sequences, but it also can be ap- the challenge that the simulations integration plied to any type of numerical load da- should be both simple, while at the • Probabilistic tools development ta. In our case the data for load spectra30
    • characterization and analysis were ob- simulation example. The log crane sim- for flexible bodies were developed. Thetained from the numerical arrays of out- ulator was used to produce simulation telescopic joint model based on con-puts produced by MBD real-time simu- data of log crane work cycles for statis- straint primitives and contact positionlation with human-in-the-loop interac- tical analysis. interpolation was implemented in thetion (HIL). The log crane model consists of 15 simulation code. Random order of loading was sim- rigid bodies interconnected by 17 joints.ulated by ten different hypothetical ”op- The kinematics includes two closed Collision modellingerators” and the most interesting load- loops, which are opened. The hydrau- Collisions play an important role ining histories of log lifting operation cy- lics of lift and jib booms are modelled making simulators more realistic. Es-cle – lift and jib cylinder forces were se- using the semi-empirical approach. The pecially in the simulator training, unre-lected as proto-type loading spectra for model also includes the collision mod- alistic collisions make the whole simu-simplified mechanical system named els between the log and the ground as lation unbelievable to the operator. Iffurther as ”toy case”. The algorithm of well as the log and the log grapple. The the operator does not think he is driv-external force vector implementation simulation time step using 3.4 GHz P4 ing a real machine he will not learn tointo MBD simulations is still under de- processor is 0.0018 s with visualization operate the machine. As a test case avelopment. The main hypothetical rate of 40 frames per second. log forwarder was modelled in a waytechnique is the second method men- that a log can be lifted into the for-tioned above named Polynomial Chaos Description of the structural warder using a contact based grip-per. flexibility in real time simulationTheory (PCT), which has been already In order to enable the gripping of thesuccessfully applied in structural me- The simulation of dynamics of flexible log, a collision model using the colli-chanics and in fluid mechanics stud- bodies was studied using floating frame sion intersection surface circumfer-ies. The application of PCT in MBD sim- of reference method. The method is ence was developed. The developedulations not studied yet enough and to based on the use of reference motion method enables a stable grip on theone’s knowledge it has not been pre- with vibration modes of bodies. This log as well as the contacts betweenviously applied to MBD simulations for enables the use of method in dynam- the different bodies.external force representation for real- ics simulation since reference motiontime inputs. This approach conceivably can handle large rotations that usual- Motion platform controlenables the simulation of MBD systems ly cause difficulties in flexibility analysis. Feeling of motion is important in simu-to produce results with “error bars”; sim- The floating frame of reference method lators especially in vehicle and mobileilar to the way the experimental results is suitable to be used in real-time sim- machine simulators. Control of a plat-are often presented. More-over, the pro- ulation since its computational require- form affects a lot to the created feelingposed methodology allows the quanti- ments are reasonable. The method was of motion. Control consists of signal fil-fication and modelling of stochastic in- studied in Lagrangian dynamics solu- tering, inverse kinematics and a controlput variables in both time and frequen- tion. The study resulted to a simulation loop. Platform gets its reference valuescy domains. code suitable for simulation of flexible from a dynamic model. multibody dynamics of academic lev- Acceleration data from the dynam-Real-time simulation el examples. ic model can’t be directly used in theThe study of semi-recursive methods Since telescopic boom structures motion platform control because thewith rigid bodies resulted to simulation are widely used in mobile working ma- platform has limited workspace. The ac-code that enables the simulation of ap- chines the modelling of telescopic joint celeration signal must first be filtered. Aplication size mechanisms in real-time. with flexible bodies was studied. The washout-filter is commonly used in theBoth open-loop and closed loop kine- literature search of simulation of joint platform control. It notices only thematics can be handled in the simulation constraints with flexible bodies gave high frequency accelerations and re-code. A log crane simulator was used as poor results so the constraint primitives turns the platform smoothly to initial 31
    • state after movements. The classical Publications Project time scale washout-filter is very simple to use but Summary of essential publications 1.6.2005–31.12.2007 the parameters of the filters are case- Korkealaakso, P., Rouvinen, A., Moisio, S. & specific and the classical washout pro- Peusaari, J. Development of a real-time Project volume duces errors to control signals. Adaptive simulation environment Multibody Total 620 000 €, Tekes share 558 000 € washout is more intelligent and its filter System Dynamics. Volume 17, parameters changes during the simula- Numbers 2–3, April 2007. p. 177–194. Project participants tion so it can adapt to different cases. Sallinen, J., Eskola, T. & Handroos, H. 2008. • LUT Institute of Mechatronics and With the adaptive washout it is possi- Design of a Motion Platform for a Virtual Engineering ble to achieve a better signal than with Mobile Machine Simulator by Utilizing • LUT Laboratory of Fatigue and Strength the classical. 6-D Measurements and Inverse • LUT Department of Information The problem with the washout-fil- Dynamics Analysis. p. 127–130. The 7th Technology: Laboratory of tering is that it doesn’t notice the low International Conference on Machine Communication Engineering frequency accelerations. To improve Automation (ICMA2008), September • University of Joensuu, Laboratory of feeling of motion, low frequency ac- 24–26, Awaji, Japan. Applied Mathematics celerations must also be described and Sallinen, J. 2008. Liikealustan suunnittelu • John Deere Forestry Oy it can be done by tilting the platform. liikkuvan työkoneen simulaattoriin. • Kalmar Industries Oy Hence the force affecting to user in Master’s Thesis, LUT. • Sandvik Mining and Construction Oy low frequency accelerations can be de- Åman, R., Handroos, H. & Eskola, T. • Wärtsilä Finland Oy scribed by using the gravitational force. Computationally Efficient Two-Regime Flow Orifice Model For Real-Time Contact information Impacts Simulation. EUROSIM2007, September Heikki Handroos The project led into commercialization 9-13, Ljublijana, Slovenia. Lappeenranta University of Technology of the real-time simulation technology Åman, R., Handroos, H. & Eskola, T. 2008. Tel. +358 40 510 7599 and establishment of spin-off company Computationally Efficient Two-regime heikki.handroos@lut.fi MeVEA Ltd providing commercial real- Flow Orifice Model for Real-time time R&D and user training simulators Simulation, Simulation Modelling for industry (www.mevea.com) Practice and Theory 16, p. 945–961. Åman, R. 2007. Hydraulisen kuristinmallin ja liikealustan ohjauksen kehittäminen reaaliai-kasimulointiin. Master’s Thesis, LUT.32
    • Modelling and simulation of coupled problems in mechanics and electrical engineering(KOMASI) – MASIT06Background tion, identification and validation of the equation methods is that the discre-Today, modern computers together with magnetoelastic model required con- tized matrix equation becomes ill-con-advanced numerical algorithms have struction of measurement devices. For ditioned if the frequency is low or themade it possible to simulate and analyze simulation of working vehicles coupled mesh density is high compared to thelarge complex structures. Therefore nu- hydraulic and flexible multibody me- wavelength. This yields inefficient iter-merical simulation has become an inte- chanics model is required. ative solutions and if the frequency isgral part of research and development in very low even the direct solution be-several fields of technology. Prime exam- Project implementation and results comes impossible. In this project newples include structural mechanics, elec- One of the main problems in the tradi- surface integral equations were devel-tromechanics, acoustics, fluid dynamics tional electromagnetic surface integral oped and implemented to overcomeand heat transfer. Despite their differenc-es the above areas share common math- Figure 1. Electromagnetic field simulation of a hollow plastic box on top of a metallicematical tools: the use of partial differ- plate calculated using the new stable and efficient Current and Charge Integralential equations to set up the physical Equation (CCIE) formulation.model and numerical methods for solv-ing the resulting equations. The projectbuilds on this observation. The main goalof the project is to model and simulatecoupled systems in mechanics and elec-tromagnetics profiting from their com-mon features.ObjectivesThe general goal is to develop robust,fast and thus efficient numerical sim-ulation methods for problems aris-ing in mechanics and electromagnet-ics. To obtain such a goal both mod-el and method development is neces-sary. In electromagnetism one of thekey issues is to formulate the equationssuch that the numerical solution is pos-sible. For instance, in scattering and an-tenna problems discretization results inmillions of unknowns to be solved. An-other objective was the developmentof coupled constitutive models for var-ious phenomena. E.g. in magnetoelas-ticity such a model is essential for ac-curate computation of vibrations andlosses in electric machines. In addi- 33
    • this low frequency breakdown of the Figure 2. Measurement device for spring-slide-beam element for model- traditional surface integral equations. the identification of power-loss and ling flexible translational joints, as well magnetomechanical models. Because the computational cost of as the connector element for modelling the integral equation methods is much extraction and retraction chains. higher than, for example, FE meth- This flexible multibody model has ods additional techniques are required been expanded by introducing the hy- for solving large problems with high draulic cylinder element where in ad- number of unknowns. These meth- dition to displacement variables the ods are called as fast integral equation chamber pressures are modelled as the methods. In particular, multilevel fast first order differential equations. This ap- multipole algorithm (MLFMA) is ap- proach will lead to a two field mixed or- plied in this research to accelerate the der ODE-system. The interaction be- iterative solution of the integral equa- tween the mechanical and hydraulic tion methods, see Figure 1. variables is coupled consistently yield- A magnetomechanically coupled ing precise tangential matrices between model of electrical steel was developed coupled fields. The modelling of the hy- and implemented in the existing simula- draulic system as the third coupled field tion software. An iron power-loss mod- has been examined. This approach will el was also developed and implement- lead to a coupled three field mixed or- ed and the model parameters were es- der ODE-system where the mechanical timated from measurements made on system and hydraulic system are cou- a special measurement device (see Fig- pled via hydraulic actuators, see Figure 3. ure 2) designed and constructed with- in the project. Impacts and dissemination Figure 3. A hydraulic-driven flexible A phenomenological model for the The models developed have been telescopic model. ductile-to-brittle transition of rate-de- handed to industrial partners and col- pendent solids was developed. Damage laborators. They are used in everyday coupled with visco-plasticity requires design of energy efficient and environ- special care in designing the constitu- ment friendly mechanical and electrical tive integration algorithms. A discontinu- machines. The models also bring new os-Galerkin scheme was developed and knowledge and understanding of the analyzed which performs well in both underlying phenomena. limiting cases – for viscous and for dam- aging behaviour. Main publications In modelling flexible telescop- Belahcen, A. 2008. Losses in an eccentric ic boom systems, the constraint equa- rotor induction machine fed from tions are embedded via a master-slave frequency converter. Proceedings of technique, giving a minimal system of the XVIII International Conference on ordinary differential equations without Electrical Machines ICEM. 6 p. algebraic constraint equations. Special Belahcen, A. & Arkkio, A. 2008. elements have been developed, such Comprehensive Dynamic Loss- as the length controlled bar element Model of Electrical Steel Applied to FE for modelling e.g. the hydraulic actu- Simulation of Electrical Machines. IEEE ator, the offset-beam element, beam transactions on magnetics, Volume 44, element with revolute joint, and the Issue 6, p. 886–889.34
    • Belahcen, A., Fonteyn, K., Hannukainen, Lovadina, C. & Stenberg, R. Energy No. 1, p. 58–67. A. & Kouhia, R. 2008. On numerical norm a posteriori error estimates Wallen, H., Järvenpää, S., Ylä-Oijala, P. & modelling of coupled magnetoelastic for mixed finite element methods. Sarvas, J. Broadband Muller-MLFMA problem. Proceedings of the 21st Mathematics of Computation. S for electromagnetic scattering by Nordic Seminar on Computational 0025-5718(06)01872-2. Electronically dielectric objects. IEEE Transactions on Mechanics NSCM-21, p. 203–206. published on 26 June 2006. Antennas and Propagation, May 2007,Eirola, T., Hartikainen, J., Kouhia, R. & Lyly, M., Niiranen, J. & Stenberg, R. 2006. Vol. 55, No. 5, p. 1423–1430. Manninen, T. Some observations on A refined error analysis of MITC plate the integration of inelastic constitutive elements. Mathematical Models and The project resulted in 40 internation- models with damage. Proceedings Methods in Applied Sciences 16, No. 7, al peer reviewed articles, 57 conference of the 19th Nordic Seminar on p. 967–977. presentations, and six doctoral theses. Computational Mechanics. Lund, 20– Marjamäki, H. & Mäkinen, J. Total Lagrangian 21 October 2006. O. Dahlblom et al. Beam Element with C1-Continuous Project time scale (eds.), p. 23–32. Slide-Spring. Computers & Structures, 1.5.2005–31.12.2008Fonteyn, K. & Belahcen, A. 2008. Numerical Volume 87, Issues 9–10, p. 534–542. and experimental results from a Marjamäki, H., Mäkinen, J., Fedoroff, A. Project volume vertical joke system for measuring & Kouhia, R. A Static Method for Total 1 457 500 €, Tekes share 1 428 000 € magnetic properties of Fe-Si steel Computation of the Tilting Angle of sheets. Proceedings of the 11th Working Machines. The 2nd International Project participants International Conference on Electrical Conference on Computational Methods • Aalto University School of Science and Machines and Systems ICEMS. p. 434–438. in Structural Dynamics and Earthquake Technology:Fortino, S., Kouhia, R., Belahcen, A. & Engineering (COMPDYN 2009), Rhodes, Dept. of Mathematics and Systems Analysis Fonteyn, K. 2007. A coupled model Greece 22–24 June 2009. Dept. of Radio Science and Engineering for magnetostriction in ferromagnetic Mäkinen, J. Rotation Manifold SO(3) and Dept. of Electrical Engineering materials. Proc. Int. Conf. on Its Tangential Vectors. Computational Dept. of Structural Engineering and Computational Methods for Coupled Mechanics, Volume 42, Number 6, p. Building Technology Problems in Science and Engineering, 907–919. • Tampere University of Technology, p. 483–484. Mäkinen, J. Total Lagrangian Reissner’s Geo- Dept. of Mechanics and DesignHänninen, I. & Sarvas, J. Efficient metrically Exact Beam Element without • Numerola Oy valuation of the Rokhlin translator in Singularities. International Journal for • ABB Oyj Multilevel Fast Multipole Algorithm. Numerical Methods in Engineering, • Metso Paper Oyj IEEE Transactions on Antennas and Volume 70, Issue 9, p. 1009–1048. • Nokia Oyj Propagation, August 2008, Vol. 56, No. Repin, S. & Stenberg, R. 2009. Two-sided • CSC Oy 8, p. 2356–2362. a posteriori estimates for a three field • COMSOL OyKouhia, R. 2008. Stabilized forms of formulation of the generalized Stokes • Nokian Raskaat Renkaat Oy orthogonal residual and constant problem. Journal of Mathematical • Bronto Skylift Oy incremental work control path Sciences 159, p. 541–558. following methods. Computer Schöber, J.l. & Stenberg, R. 2009. Multigrid Contact information Methods in Applied Mechanics and methods for a stabilized Reissner- Rolf Stenberg Engineering, Vol. 197, p. 1389–1396. Mindlin plate formulation. SIAM Journal Aalto University School of Science andLovadina, C. & Stenberg, R. 2005. A of Numerical Analysis 47, p. 2735–2751. Technology, Dept. of Mathematics and posteriori error analysis of the linked Taskinen, M. & Ylä-Oijala, P. Current and Systems Analysis interpolation technique for plate charge integral equation formulation. Tel. +358 9 4702 5576 bending problems. SIAM Journal of IEEE Transactions on Antennas and rolf.stenberg@tkk.fi Numerical Analysis 43, p. 2227–2249. Propagation, January 2006, Vol. 54, http://math.tkk.fi/en/people/rolf.stenberg 35
    • Modeling and simulation of dissolved and colloidal substance flows in TMP- and DIP-processes – MASIT07 Background and goals ta collection methods. New methodol- duction line. In both cases processes Dissolved and colloidal substances ogies have been developed for achiev- are modeled from log washing to wa- (DCS) are the chemicals flowing with ing reliable process values to be imple- ter leaving an effluent treatment plant. water and fibers in a TMP or DIP paper mented in process simulations. Estima- Dynamic features of BALAS reveal mill. DCS are a mixture of many organic tions of uncertainties or inaccuracies in and show dynamics of various steps in molecules dissolved or in colloidal form BALAS model parameters are now cal- paper making. Simulations of different in circulating process waters mainly re- culated. Based on different sampling real or virtual process changes can be leased out of wood chips or fibers in re- frequencies of process data, parameters simulated accurately. fining and bleaching stages in produc- can be estimated for keeping model´s Statistical methods have been a ing mechanical pulps. They in most cas- uncertainty on an acceptable level. The critical tool to estimate the accuracy es develop different process or quality storage tank dynamics of processes are and reliability of online or offline da- disturbances. MASI team in LUT Fiber now modeled. Based on process meas- ta. Single point measurements without Technology Center has modeled and urements internal time constants are statistical analysis are not good for reli- simulated these processes in an earlier surprising long and they create long able simulations. study in order to introduce ideas about lasting disturbances in water and DCS A methodology was developed to effluent free TMP and DIP paper mills. (dissolved and colloidal substances) minimize the uncertainty or inaccuracy Based on this experience a new project balances. It takes up to tens of hours be- of BALAS model. In case of a dynamic plan was written in order to a more ex- fore a DCS change in debarking or refin- simulation of a dynamic process param- act way to know and simulate flows of ing stage flows out of the effluent treat- eters of BALAS must be kept updated, DCS in these unit processes. By using ment plant. Pumping backwards differ- when process changes occur. One crit- the dynamic BALAS it could be possi- ent white water qualities counter cur- ical factor in this software is to estimate ble to follow and also to predict how rently from a paper machine water sys- the sampling frequency of critical proc- these chemicals act inside processes tem to different washing stages earlier ess variables. If these variables are very with time. The main goal was to mod- in the mill processes creates these long seldom measured, the uncertainty will el and simulate the flows of these DCS lasting material and chemical fluctua- grow out of acceptable ranges. Based from wood logs processing through tions. Accurate modeling has also indi- on targeted uncertainty of the model a the whole process till the effluent treat- cated that there are unknown fresh wa- sampling frequency can be estimated. ment plant with real measured online ter surpluses in mill processes. Dynam- Dissolved and colloidal substanc- and laboratory data and understand ic BALAS models together with reliable es (DCS) are very difficult to measure. A that flow with this storage tank dynam- process data have showed that these measuring procedure from sample col- ics of BALAS software. simulations are valuable tools for proc- lection to data processing was devel- ess studies in different situations in a oped for this project. If there were some Abstract paper mill producing uncoated or coat- deviations from the described proce- Models of two paper mills with me- ed mechanical paper qualities. dure in mill tests, these deviations im- chanical pulps have been created and mediately were misleading simulation both of them are running with online Results steps. A finding of this study indicates process data and laboratory measure- BALAS simulation models have been that the standard deviation of DCS read- ment results. Both online and offline da- created for one uncoated mechanical ings varied from +–5 % up to +–20 % de- ta must be mathematically evaluated in printing paper production line and one pending on process conditions and the order to eliminate errors in various da- coated mechanical printing paper pro- critical accuracy of laboratory technicians.36
    • Both examined real paper making process conditions. Problems in chem- result will be the dynamics and the pre-processes had long internal time con- ical dosing, their concentrations, web dictability of the process. This simulatorstants. The first step on the way to lim- breaks, broke handling and its flow and identifies a change in a key process andit fresh water consumption per a pro- quality variations, retention fluctuations is capable to tell the operators, how thisduced paper ton is to increase internal in paper machine short circulation and DCS problem will flow through and outwater flows backwards, from a paper many more trouble making situations of the entire process.machine to washers or pulp dilutions can be simulated with time. Simulations This dynamic BALAS is also a toolin different stages. This is fine, but it al- show clearly how these wanted or un- set for simulating the elimination ofso creates long time constants for any wanted changes flow through process- DCS as a material or as a trouble mak-change in processes. Time constants are es from step one to the last one. er. Different DCS separation technolo-in the range of tens of hours. This was All kind unit processes can be sim- gies can be simulated and/or mill – test-measured in many cases and this spe- ulated inside of this model in order to ed with dynamic BALAS. The softwarecific feature makes the implementation eliminate DCS disturbances in various will have features to adjust its processof dynamic BALAS obligatory. Without process steps and to lower environ- parameters based on online or offlinethis storage tank dynamics simulations mental impact of the production unit process data.of these processes results were not as and without forgetting improvementsinformative as with this dynamic BALAS. in runnability of paper machines. Project time scale Accurate water balances of BALAS 1.6.2006–31.5.2007simulations have shown that there still Impactsare some major fresh water leaks in The key result was to see, how well dy- Project volumeprocesses, although these mills both namic BALAS simulated processes in Total funding of the project 450 000 €,are running very well. A high level sim- these two paper mills. MASI team was share of Tekes funding 198 000 € andulation model requires accurate proc- capable to follow different process dis- European Regional Development Fundess knowledge and accurate online wa- turbances or changes for hours, days, (ERDF) 198 000 €ter flow data from all parts of key proc- weeks and months. The only limiting UPM-Kymmene, StoraEnso, M-real, Metsoesses. factor was the availability of error – free, Paper, Kemira & Foster Wheeler 54 000 € Mass flow balances were very dif- online or offline process data.ficult to form, because online consist- Based on mill measurements, MA- Project participantsency measurement instruments seem SI team has seen that more valid infor- • Lappeenranta University of Technologyto be very inaccurate and unreliable for mation must be collected and based • Tampere University of Technologythese purposes requiring exact proc- on that, more accurate mill runnabili- • Åbo Akademiess data. ty information will be achieved during • VTT Technical Research Centre of Dynamic BALAS made long last- projects like this. Finlanding simulations possible. This means The quality of this information isthat models can handle time spans crucial for the accuracy of the mod- Project managerfrom some hours to some months. This el and its simulations. Lots of team ef- Martti Mäkinenopens new possibilities to follow proc- forts were concentrated on the area of Lappeenranta University of Technology,esses or create forecasts or visions of collecting and analyzing process data. Fiber Technology Centerprocesses showing quite accurately MASI team never had too much of highwhat will happen in the future. The ba- accuracy, high reliability, real-time data.sic steady state BALAS simulator is not Deeper understanding of thecapable to meet these challenges. whole production line mechanical pulp- These studied dynamic models ing – paper machine – effluent treat-make possible simulations of different ment will be one of the results. The main 37
    • Scientific computing and optimization in multidisciplinary applications (Scoma) – MASIT08 Background ed, and visits of professors and research- cated non-linear and coupled models In the field of mathematical modelling ers were very common. are often used to model complex phe- and simulation, University of Jyväskylä nomena. These models were unavaila- has been very active during the last 20 Project actions ble twenty years ago. However, it is cru- years. The activities started in 1988, with The project was implemented quite cial to understand that simply obtain- numerical analysis of PDE’s and were ex- freely. The topics were chosen but we ing some approximation of the system tended to calculus of variations, optimal decided not to restrict the researchers of PDE’s is not enough. Main questions control, optimization and their numer- inside of them. This increased our pos- that need to be answered are: ical methods and efficient implemen- sibilities to collaborate with many uni- I What is the accuracy of the tations. In 2005, the Scoma project be- versities and to get a broad overview approximation obtained by the gan and, due to funding practicalities, of each topic. With open minds, we dis- numerical method (finite element was divided into three periods. The last cussed our topics with many professors method, finite volume, finite period began in 2008. During the 1st with separate approaches, and com- differences, etc.)? and 2nd periods of Scoma, some re- bined the found information to several II How accurately we know the search topics have been developed as journal articles. The used free approach problem data and what kind of new projects or concluded as planned. was found to be the correct choice for accuracy limits we need to set for In this final report, we examine close- a project like this. In addition, we also the simulations? ly three different topics which were in- brought some new software for a dai- III How accurately the model itself cluded in Scoma at the beginning. ly use. Seminars and conferences were describes the phenomenon regular with high level lecturers. The under investigation? Objectives most active collaboration was done be- IV Which quantities are computable The aim of the Scoma project was to tween University of Jyväskylä and Mos- and which are too unstable (with tackle challenging multiphysical prob- cow State University and St. Petersburg respect to data) such that com- lems from the numerical point of view. State University. Our activities comple- puting them makes no sense? We concentrated, especially, on reliable mented each other very well. computing and modelling of phenom- The question I has been seriously stud- ena, which can not be otherwise meas- Results and discussion ied for a wide range of problems in the ured. In practice, this means creation of books Neittaanmäki and Repin (2004) Reliable computing in mathematical new adaptive algorithms and a poste- and Repin (2008) and for a particu- modeling riori error control methods intended lar problem in Anjam et al. (2009). We to reliably solve elliptic-type bounda- The main collaborator was Prof. Sergey applied these results to address the ry-value problems with respect to cer- Repin from St. Petersburg. The aim of question II and the obtained results tain a priori given criteria. We were al- the topic was to develop computa- to a class of elliptic problems in Mali so interested in analysis of mathemat- tional simulation methods used in sci- and Repin (2008, 2009, 2010). These ical simulation methods for PDE’s that ence and engineering. In the modeling results obviously have practical im- takes into account uncertainties in the practice, there are several fundamen- portance. For example, the diffusion problem data. One of our main aspects tal questions that are often neglected model is widely applied in the differ- was highly active collaboration with in- in both application areas. These ques- ent fields of modeling. However, of- ternational experts. As planned, during tions have mathematical nature and ten only the general diffusive behav- these two years, international seminars require basic research. Due to the in- ior is recognized, but the parameters and conferences were regularly attend- creased computational power, compli- are obtained from experiments or his-38
    • torical data. In Mali and Repin (2009), Figure 1. Cylindrical nanofiber which has been periodically choked in the middle. Deformation is used to scatter elastic waves which carry thermal energy.we expose how to estimate the effectof uncertain coefficients on the solu-tion, and what kind of accuracy limitthe uncertain coefficients introducefor any simulation. The work done by our group isfundamental mathematical research,which has obvious practical applica-tions. Our efforts are aimed to short-en the gap between the simulationsand real experiments and engineering.Complicated and highly sophisticatedsimulations rather tend to live an aca-demic life of their own. Fancy figuresand animations of approximate solu-tions obtained by immense computa-tional effort do not provide quantitative Figure 2. Transmission coefficients of flexural waves as a function of frequency andknowledge required for engineering. number of corrugations. On the blue area transmission probability is only about 10%.The key to the problem is not in the in-creased computational power. The wayhow models are constructed and theirrelation to physical phenomena shouldbe observed and studied with greatcare. This is possible only through a re-al understanding of the mathematicalcharacter of the applied models. Thus,serious study of the questions I–IV ishighly motivated.Shape design’s effect on thermalconductance of 3D fibersWorking in collaboration with Prof. BorisPlamenevsky and Prof. Lev Baskin fromSt. Petersburg, we have applied ourknow-how of fiber design to many ar-eas of nanophysical phenomena. One The manufacturing processes of na- Instability analysis of a paper websuccessful area has been the simula- notechnology are at a gallop of reaching In our group of Fluid-Structure Interac-tion and asymptotics of propagation of the point that engineered 3D structures tion (FSI), we have made collaborativeelectrons on 2D waveguides with two can be mass-produced. Therefore also research with Prof. Nikolai Banichukcompleted doctoral theses. The tools designing of such structures must be in- from Russian Academy of Sciences. Ourused in the research were mathematical vested so that all of the new possible fea- project has been focusing on mathe-analysis and numerical computer simu- tures can be utilized. We look forward to matical modeling of dynamic behav-lations on the basis of theory of asymp- collaborate with private and public en- ior of a rectangular plate, travelling attotic analysis. terprises in the future. a constant velocity between two sup- 39
    • Figure 3. The vacuum buckling modes of an axially moving plate with two different aspect ratios. Left: The length of the plate is greater than the width. Right: The width of the plate is greater than the length. ports. The vacuum case and interaction during the project. We have published • EUROGEN 2007, Jyväskylä, 11–13 with the plate and surrounding axially 16 journal articles, 8 theses, 1 mono- June 2007 flowing ideal fluid have been investigat- graph, 22 conference papers and 10 • Database Workshop, Jyväskylä, ed. The models have been studied an- reports. In addition, two patents have 13–17 March 2009 alytically as far as possible using gener- been applied. Impact of the local com- • Workshop for Junior scientists, St. al static and dynamic analyses. Numer- panies has been dual, depending on Petersburg, 27–29 April 2009 ical methods, finite element method knowledge level of company. Some of • 10th Finnish Mechanics Days, for instance, have been used to com- the companies are interested in the re- Jyväskylä, 3–4 December 2009 plete the solution and to illustrate the sults, other are more interested in the • Database Workshop, Jyväskylä, phenomena. The results on the study research processes. We assume that the 3–4 December 2009 of the instability of the plate have been latter got much more in a strategical • Database Workshop, Jyväskylä, published in two articles Banichuk et al. level. However, knowledge of numeri- 10–12 March 2010 (2009, 2010). cal methods and tools has dramatically The project is very close to its ap- increased during the project. Patents plications in paper making processes. L. M. Baskin, P. Neittaanmäki, B. A. We look forward to continue our in- Dissemination Plamenevskii & A. A. Pozharskii. 2006. ternational collaborative research be- • 1st SCOMA Seminar, Jyväskylä, Switch devices for electron flows in tween the science community and in- 3–5 October 2005 quantum waveguides. Application for dustry. • SCOMA Seminar (OCOGT-06), patent. Jyväskylä, 6–7 March 2006 L. M. Baskin, P. Neittaanmäki, B. A. Impacts • 2nd SCOMA Seminar, Espoo, Plamenevskii & A. A. Pozharskii. 2006. Scientific impact of the project can best 23–24 November 2006 Method of the control of thermal be evaluated in two different numeri- • SCOMA Workshop for PhD conductance for dielectric nanofibers cal metrics; number of the publications students and junior scientists, and corresponding device. Application and number of the organized events Jyväskylä, 29–30 March 2007 for patent.40
    • Publications Baskin, L., Neittaanmäki, P., Plamenevsky, Project time scaleSummary of essential publications B. & Sarafanov, O. 2009. Asymptotic Scoma I: 1.4.2005–31.9.2006Anjam, I., Mali, O., Muzalevsky, A., theory of resonant tunneling in 3D Scoma II: 1.10.2006–31.12.2007 Neittaanmäki, P. & Repin, S. 2009. A quantum waveguides of variable Scoma III: 1.1.2008–30.3.2010 posteriori error estimates for a Maxwell cross-section. SIAM Journal on Applied type problem. Russian Journal of Mathematics, 70(5):1542–1566. Project volume Numerical Analysis and Mathematical Mali, O. & Repin, S. 2008. Estimates Scoma III: Total 614 500 €, Modelling, 24(5):395–408. of the indeterminacy set for Tekes share 460 000 €Banichuk, N. V. & Neittaanmäki, P. J. elliptic boundary-value problems 2010. Structural optimization with with uncertain data. Journal of Project participants uncertainties. Solid Mechanics and Its Mathematical Sciences (New York), • ABB Oy Applications, 162. Springer, Berlin. 150(1):1869–1874. • Comsol OyBanichuk, N., Jeronen, J., Neittaanmäki P. Mali, O. & Repin, S. 2010. Estimates of • CSC – IT Center for Science & Tuovinen, T. 2009. Static instability accuracy limit for elliptic boundary • Metso Paper Oy analysis for travelling membranes value problems with uncertain data. • Oy Metsä-Botnia Ab and plates interacting with axially Advances in Mathematical Sciences • Moventas Oy moving ideal fluid. Journal of Fluids and Applications. Accepted. • Patria Aerostructures Oy and Structures, doi:10.1016/j. Neittaanmäki, P. & Repin, S. 2004. Reliable jfluidstructs.2009.09.006. methods for computer simulation: Contact informationBanichuk, N., Jeronen, J., Neittaanmäki, P. Error control and a posteriori estimates. Prof. Pekka Neittaanmäki & Tuovinen, T. 2010. On the instability Elsevier Science, Amsterdam. University of Jyväskylä of an axially moving elastic plate. Neittaanmäki, P., Périaux, J. & Tuovinen, Tel. +358 40 550 7005 International Journal of Solids and T. (eds.) 2008. Evolutionary and pn@mit.jyu.fi Structures, 47(1):91–99. Deterministic Methods for Design, www.mit.jyu.fi/pnBaskin, L. M., Neittaanmäki P. & Optimization and Control: Applications Plamenevsky, B. A. 2010. The effect to Industrial and Societal Problems of charged states on the emission (EUROGEN 2007, Jyväskylä). CIMNE, of broad band semiconductors and Barcelona. dielectrics. Journal of Technical Physics. Repin, S. 2008. A posteriori estimates for Accepted. partial differential equations. Walter deBaskin, L. M., Neittaanmäki, P., Gruyter, Berlin. Plamenevsky, B. A. & Pozharsky, A. A. 2008. Method for reducing the low- temperature thermal conductivity of nanofibers. Doklady Physics, 53(1): 34–38. 41
    • Automated generation of 3D topographic visualisations – MASIT09 Background The potential of satellite imagery in prototype tools to increase the level of Architectural planning and naviga- providing consistent data globally and automation in compiling topographic tion, security and military training, vis- frequently over large areas is not ful- models and visualise the results with ef- ibility calculations and game industry ly exploited in completing and updat- ficient rendering tools. The main source use in increasing number realistic top- ing the topographic models. Best res- data is satellite and aerial imagery. The ographic 3D visualisations of the envi- olution currently available is 5 dm pixel focus is to develop tools for the map- ronment. Accurate and detailed top- size from GeoEye- and WorldView-sat- ping of building footprint, height and ographic models are generated from ellites. Detailed massive topographic colour and the mapping of vegeta- map and GIS databases, CAD systems, models over large areas need also effi- tion type and height. Existing map ma- aerial images, and laser scanning data, cient 3D data rendering methods for re- terial is exploited in the methodology. but substantial amount of human ef- al time visualisation. The tools include conversion and visual- fort is needed to synchronise this data isation software to illustrate the results of different accuracy, different format Objectives and visualise large area detailed 3D top- and different geo- and time-reference. The goal of the project is to develop ographic models. Figure 1. Satellite images with resolution from 0.5 to 5 metres with sophisticated calibration provide valuable information to update vegetation and tree cover of large area topographic models.42
    • Project implementation Figure 2. Tree crown models for tree point cloud to locate trees. Feature vec- crown matching.The project had the following phases: tors are extracted from the aerial imag-1. Survey of the bottlenecks and es for the identification of the tree spe- solutions in 3D mapping and cies. Tree species specific 3D crown visualisation models are matched to the LiDAR point2. Development of mapping tools cloud to measure the crown diameter. for building, vegetation cover and Building tool utilize the Normal tree mapping Difference Vegetation Index to deline-3. Selection of visualisation solution ate build areas from vegetated areas, the4. Integration of the tools to the Canny operator to detect edges from demonstrator the build areas, and the Hough trans-5. Estimation of benefits and usabil- formation to eliminate non straight lines ity, exploitation possibilities and combine pieces of straight lines to building and roof hips. The integrationResults of building facades to the buildings isThe Tree Tool generates tree instances the strongest factor affecting radiance designed and described in Erving, 2007.from satellite image to 3D models. The scattering. Figure 1 illustrates the com- A Demonstrator was built to inte-method is based on the calibration of bination of a high accuracy Otaniemi grate and validate the tools developedthe satellite image radiances into phys- city model with trees generated from a in the project (Niinimäki, 2007). The vis-ical reflectance values so that generic SPOT satellite image. ualisation solution is based on openpolynomial models can be used in the The Single Tree tool utilises aerial source OpenSceneGraph 3D visualisa-estimation of forest parameters. The cal- images and LiDAR data to detect trees tion library and standard geo-data mod-ibration removes the effect of atmos- and estimate the tree properties (Kor- els and formats. The components of thepheric aerosol optical density, which is pela 2007). The tool uses the LiDAR 3D demonstrator are shown in Figure 3.Figure 3. Demonstrator from geospatial information sources to 3D visualisation. 43
    • Applications and products Anne-Laure Henry from City of Geospatial information (http://www. The Tree tool, Single Tree tool and the Strasbourg prepared two internal re- commission1.isprs.org/hannover07/ Demonstrator pipeline are close to op- ports to the project: 3D modelling of start.htm). erative tools. The Tree Tool could be the city of Strasbourg, December 2005, Parmes, E. 2008. 3D Terrain – tools for used to complete data in geo-browsers and Building detection and 3D recon- extracting 3D data. Positio 1/ 2008. like Google Earth, MS Virtual Earth, and struction by automatic and semi - au- In Finnish. NASA World Wind. Other applications tomatic methods from remote sensing Rainio, K. & Parmes, E. 2006. Web based 3D that profit of up to date vegetation and imagery – State of Art, November 2006. geographical browsers. Positio 1/2006. forest cover information are: flood and In Finnish. wind simulations, illustration of envi- Publications ronmental impact of mining, propaga- Erving, A. 2007. Façade texturing of a Project time scale tion and visibility studies, and preparing 3D model. Master’s Thesis, Helsinki 1.8.2005–30.7.2007 to rescue operations in natural disasters. University of Technology, Laboratory of Other potential applications and busi- Photogrammetry and Remote Sensing, Project volume ness potentials are presented in Exploi- Espoo 2007. In Finnish. Total 294 000 €, Tekes share 196 000 € tation plan, Parmes 2007. Erving, A. 2008. Foto adds reality. Positio 1/ The Building tool need further de- 2008. In Finnish. Project participants velopment, but would be important Erving, A. 2008. New possibilities with • VTT tool globally if successful. CityGML – models. Positio 1/2008. In • HUT, Institute of Geodesy and Finnish. Institute of Photogrammetry and Impacts Korpela, I. 2007. Incorporation of Remote Sensing Participation in EC FP7 security pri- allometry into single-tree remote • Helsinki University, Department of ority project “Transportable Autono- sensing with LiDAR and multiple Forest Resource Management mous patrol for Land bOrder Surveil- aerial image. Proceedings of ISPRS • Insta DefSec lance” (TALOS), 2008–2012, responsible Hannover Workshop 29.5. – 1.6.2007, • Vianova Systems Finland Oy for 3D modelling, visualisation and vir- High Resolution Earth Imaging for • Pieneering Oy tual modelling of TALOS system topo- Geospatial information (http://www. • Terrasolid Oy graphic and tactical data (www.talos- commission1.isprs.org/hannover07/ • Helsinki City border.eu). start.htm). Niinimäki, T. 2007. Interactive multi- Contact information International cooperation scale visualization of built areas. Eija Parmes Prof Eberhard Gulch from Stuttgart Uni- Master’s Thesis, Helsinki University VTT Technical Research Centre of Finland versity of Applied Science gave two lec- of Technology, Telecommunications Tel. +358 20 7226 284 tures on mapping of buildings and the Software and Multimedia Laboratory, eija.parmes@vtt.fi CityGML standard, in project kick off Espoo 2007. seminar on “Generation of 3D visuali- Parmes, E. & Rainio, K. 2007. Production sations on built environment”, Espoo, of vegetation information to 3D 9.5.2006. Over 50 participants from 25 city models from SPOT satellite mapping and planning companies, city images. Proceedings of ISPRS measurement departments and univer- Hannover Workshop 29.5.–1.6.2007, sities and research institutes participat- High Resolution Earth Imaging for ed to the seminar.44
    • Improvement of evacuation safety in large buildings by the combined simulation of fire andhuman behaviour – MASIT10Background, goals and programme and evacuation processes. The evacua- to develop an evacuation module forTraditionally, the evacuation capacity tion simulations must be able to model FDS to allow the simultaneous and cou-of the building is designed according the dynamics of large and high density pled simulation of fire and evacuationto a set of relatively simple design cri- crowds and consider the evacuees’ de- processes. The second goal was to per-teria on the required width and length cision making processes behind the re- form evacuation experiments for theof evacuation routes, as described in action times, premovement times and model validation, exploring the newthe national building codes. Howev- the exit route selection during the ac- techniques for observing the humaner, the modern public buildings, which tual evacuation. For the reliability of the behaviour during the evacuation.are constantly increasing in size and ca- performance based design, the simula- The goals of the project were topacity, are usually designed using the tion tools must be validated for the giv- develop a simulation tool for the evac-performance based design method, in en type of application. uation of large buildings, and to val-which the safety of the design is stud- During the last few years, VTT has idate the tool using interdisciplinaryied as an entire system, not as fulfilment participated in the development of Fire approach and experimental data. Theof individual rules given by the build- Dynamics Simulator (FDS) software in project partners, funding and durationing code. The performance based de- co-operation with the National Insti- are summarized below.sign relies much on the numerical mod- tute of Standards and Technology, USAelling and simulation of both the fire (NIST). The first goal of the project was Figure 1. An example of simultaneous and coupled simulation of fire and evacuation. 45
    • Results • The grouping behaviour of humans al evacuation of large shopping cen- The main features of the developed is modelled by dividing the tre. Promising results were achieved for FDS+Evac software are actions of a group into two stages: the use of radio frequency identification • Human movement based on gathering stage and egress stage. (RFID) as a means to make observations PANIC model. Individual humans An example of group behaviour is on the human movement in the evac- are modelled as agents with their shown in Figure 2. uation. own equations of motion. A three- circle representation of humans The software is freely available at ht- Impacts is used to account for rotational tp://fire.nist.gov/fds and documenta- Despite the relatively short history of forces. See an example in Figure 1. tion and application examples can be FDS+Evac, it already has users in engi- • Fire-human interaction is based found at http://www.vtt.fi/fdsevac. neering companies that design build- on the Fractional Effective Dose The individual features and sub- ings and infrastructure (both domes- (FED) concept of Purser, and the models of FDS+Evac software were ver- tic and international). VTT researchers algorithms for speed reduction ified using a large group of tests, includ- have used the tool for real fire safety and exit route selection by smoke. ing those required by the IMO guide- engineering assignments. In the future, • Game theoretic reaction functions lines (MSC/Circ.1033). Experimental da- potential users can also be found in fire and best response dynamics ta on flows through doors, hallways services and the educational organi- are applied to model the exit and staircases were used to validate the zations. Indirectly, the results will ben- route selection of evacuees. movement algorithm. efit the owners and managers of large Exit selection is modelled as an Three evacuation experiments building clusters, shopping centres and optimization problem, where the were performed to provide the valida- ships through the increased safety. In evacuee tries to select the exit that tion data. In the experiments, new tech- addition to the actual reduced risk of minimizes the evacuation time. niques of observing the human behav- large hazards, the safety is strongly be- The exit selection is implemented iour were studied. The use of surveil- coming a marketing value. The project as a preference order table for the lance cameras was studied using the created new co-operation between the available doors and exits. video material recorded during a re- participating research organizations. Figure 2. Snapshots of simulations with the group model.46
    • Publications Korhonen, T., Hostikka, S., Heliövaara, Project time scaleHeliövaara, S. 2007. Computational S., Ehtamo, H. & Matikainen, K. 1.8.2005–31.12.2007 Models for Human Behavior in Fire Integration of an agent based Evacuations. M.Sc. Thesis. Systems evacuation simulation and the state- Project volume Analysis Laboratory, Helsinki University of-the-art fire simulation. 7th Asia- Total funding 243 000 € (Tekes, Finnish of Technology, Finland. Oceania Symposium on Fire Science Fire Research Fund (Palosuojelurahasto),Heliövaara, S., Ehtamo, H., Korhonen, T. & Technology. 20–22September 2007, Ministry of the Environment and VTT), & Hostikka, S. Poistumissimuloinnit Hong Kong, China. Tekes share 152 000 € palotilanteissa. Pelastustieto, Korhonen, T., Hostikka, S., Heliövaara, S. 58, Erikoisnumero, p. 109–113. Ehtamo, H. & Matikainen, K. FDS+EVAC: Project participants Palotutkimuksen päivät 2007. Espoo, Evacuation module for fire dynamics • VTT Technical Research Centre of 27. – 28.8.2007. (in Finnish) simulator. Proceedings of the Interflam FinlandHostikka, S., Korhonen, T., Paloposki, T., 2007 Conference, University of London, • Helsinki University of Technology, Rinne, T., Matikainen, K. & Heliövaara, S. UK, 3–5 September 2007, p. 1443. Systems Analysis Laboratory 2007. Development and validation of Korhonen, T., Hostikka, S., Heliövaara, S. • Helsinki University, Department of FDS+Evac for evacuation simulations. & Ehtamo, H. FDS+Evac: Modelling Social Psychology VTT Research Notes 2421. VTT, Espoo, Social Interactions in Fire Evacuation. 64 p. 7th International Conference on Contact informationHostikka, S., Paloposki, T., Rinne, T., Saari, Performance-Based Codes and Fire Simo Hostikka J.-M., Korhonen, T. & Heliövaara, S. Safety Design Methods. 16–18 April VTT Technical Research Centre of Finland 2007. Evacuation experiments in 2008, Auckland, New Zealand. Tel. +358 20 722 4839 offices and public buildings. VTT Matikainen, K. 2007. Käyttäytyminen simo.hostikka@vtt.fi Working Papers 85. VTT, Espoo, 52 p. uhkatilanteessa – PoistumisreitinKorhonen, T., Hostikka, S. & Keski- valintaan vaikuttavat sosiaalipsyko- Rahkonen, O. 2005. A proposal for logiset tekijät tulipalossa. Pro Gradu the goals and new techniques of -tutkielma. Valtiotieteellinen tiede- modelling pedestrian evacuation in kunta, Helsingin yliopisto. (in Finnish) fires. 8th International Symposium on Fire Safety Science, 18–23 September 2005, Beijing, China. International Association of Fire Safety Science. 47
    • Modelling and simulation of manufacturing systems for value networks (MS2Value) – MASIT12 Background, goals and work ysis of manufacturing operations in val- Results programme ue networks. The framework should in- The Modelling and Simulation Frame- Modelling and simulation technolo- clude tools for optimization and analy- work was defined in the WP1 and WP2, gies represent tremendous opportuni- sis on different levels of abstraction, as starting with the conceptual design and ties for radical improvement of our abil- well as filtering of information from one later the implementation of the frame- ity to design, develop, manufacture, op- tier to the next, going from machine work. The MS2Value Framework was en- erate, and support complex products – level to supply chain. visioned to be a self-reconfigurable dis- to reduce the time and cost of translat- The project was divided into five tributed and scalable simulation envi- ing products from concept to delivered Work Packages which were: WP1 – ronment, in which companies would be systems, to improve operational per- MS2Value Modelling Framework, WP2 able to analyze their manufacturing op- formance, system availability, and cost – Modelling and Simulation methods erations from any location, without the efficiency to reduce total cost of own- and tools, WP3 – Value Networks, WP4 need to request information from dis- ership. The project did use these high- – Modelling and Simulation Infrastruc- persed geographical locations. The initial level goals as guidelines in the develop- ture and WP5 – Case Studies and Pilot architecture was defined by Tampere Uni- ment of the methods and tools to aid Implementations. Actual WP4 develop- versity of Technology. The goal of the WP1 in the achievement of the objectives ment was done in collaboration with was to develop a modelling framework. of the project. The main goal of this MASIT11 project. The project has close In order to accomplish it, an extensive re- project was to develop a generic mod- collaboration with MASIY01 project – search was done by TUT about technolo- elling and simulation framework that Digital enterprise simulation frame- gies that would allow the desired interac- would enable the modelling and anal- work. tion between users. Some test cases were designed for further development. Figure 1. Distributed simulation environment.48
    • Figure 2. Integrated analysis methods, factory simulation and analytical calculation. WP2 consisted of a research of test case for hybrid analysis method and Federates were developed allowing thetools and methods for implementing TCO is integrated to Visual Components simulation software to share data acrossa distributed simulation. Results were simulation software. Development sup- resources.presented in the paper ”Parallel and Dis- ports semiautomatic cost model crea- In the WP5 development result istributed Simulation” which was handled tion, TCO analysis results are shown in partly software based functional proof-to the partners. In addition to that, a re- simulation software user interface but of-concepts based on developmentsearch about RTI’s and simulation soft- it can be used also as an independent work done in WP2. An initial imple-ware was done, from where the tools MS-Excel workbook application. mentation for Sandvik’s case study in-for the development were chosen. The work done in the WP 3: Val- cludes a graphical user interface (GUI) In the area of advanced cost mod- ue Networks consisted of a field study with simulation capabilities for produc-elling (WP2), strides have been made – interview – among the Finnish com- tion managers, including a robust inte-to improve the state of the art in cost panies. The analysis outlined that highly gration to ERP system with partially au-modelling by improving the Total Cost competitive business situation of today tomated model building. Planned useof Ownership (TCO) approach devel- drives companies to seek solutions be- of system is to evaluate production sce-oped at VTT. The TCO MS2Value anal- yond their own organizational bound- narios, order scheduling, capacity man-ysis tool for assembly system compar- aries. agement and help production manag-ison uses factory simulation, simulation WP 4 concentrated on designing ers in decision making. The Raute’s caserun results and model data to calcu- a modelling and simulation infrastruc- study is an implementation of a simu-late system key performance indicators ture. At first, the proposals of the pre- lation tool for planning of the plywood(KPI). Analytical calculations are based vious work packages were compiled in factory and later for scheduling of realon OEE (Overall Equipment Efficiency) architecture. The next step was the im- plywood mill operations. The first devel-analysis, Cost of Ownership (COO), Life plementation of the architecture. This opment focus has been in the creationCycle Cost (LCC) and discount cash flow implementation was called DS-HLA of methods for fast hierarchical simu-calculations, Net Present Value (NPV) tool, which allows the management lation model building as well as toolsand Internal Rate of Return (IRR). This is a of a federation through Web Services. for simulation data and model man- 49
    • Figure 3. Raute case study and Sandvik case study. agement. Potential use for the devel- data management has been developed Heilala, J. Hybrid Decision Support and opment are many, a tool for sales engi- and tested. Human factors are always Justification Methods for Production neering, factory design. Later the devel- import, simulation system must be System Selection I*PROMS 2007 oped methods can be used for optimi- easy to use, model building fast and re- conference. 2–13 July 2007. zation of factory operations. sult must be presented in an attractive Heilala, J., Montonen, J., Helin, K., Salonen, way to users, especially if the planned T. & Väätäinen, O. Life Cycle and Impacts users are not simulation experts. Devel- Unit Cost Analysis for Modular Re- Hierarchical modelling, from single ma- opment done in the project is in a right Configurable Flexible Light Assembly chine to factory level and value net- track. Development has been tested Systems. Proceedings of the 2006 work has been developed further. Dis- with industry cases, industrial partners IPROMS Virtual Conference. July 2006. tributed manufacturing simulation and as well research partners have gained Heilala, J., Montonen, J. & Helin, K. Select use of HLA interface in industrial man- valuable knowledge on the use of simu- Right System – Assembly System ufacturing applications is still rare. The lation and modelling. Results have been Comparison with Total Cost Ownership distributed simulation framework for presented in international conferences Methodology. Assembly Automation manufacturing systems is expected to and published in journals. 27/1 (200) 44–54. Emerald Group be used in several industry sectors and Publishing Limited, ISSN 0144-5154. future case studies shall show the po- Publications Heilala, J., Montonen, J., Salmela, A. & tential of this approach. To speed up Heilala, J., Helaakoski, H. & Peltomaa, I. Järvenpää, P. Modeling and Simulation model building and simulation analy- Smart Assembly – data and model for Customer Driven Manufacturing sis, one key factor is data integration, driven, IPAS 2008. Chamonix France System Design and Operations from various manufacturing informa- 10–13 February 2008. Planning. Proceedings of the 2007 tion systems simulation system. Dur- Heilala, J., Helin, K. & Montonen, J. 2006. Winter Simulation Conference. S.G. ing the project information integration Total cost of ownership analysis for Henderson, B, Biller, M.-H. Hsieh, J. mainly from Enterprise Resource Plan- modular final assembly systems. Inter- Shortle, J.D. Tew & R.R. Barton (eds). ning (ERP) systems to simulation was national Journal of Production Research, Washington D.C. 9–12 December improved, also methods for simulation vol. 44, No: 18–19, 3967–3988. 2007.50
    • Heilala, J., Montonen, J. & Väätäinen, O. Rodríguez Alvarado, J.R., Velez Osuna, R. Project participants Life Cycle and Unit Cost Analysis for & Tuokko, R. Distributed Simulation • Tampere University of Technology, Modular Re-Configurable Flexible in Manufacturing using High Level Institute of Production Engineering Light Assembly Systems. Journal of Architecture. IPAS 2008, Chamonix • VTT Industrial Systems Engineering Manufacture (Part B of France 10–13 February 2008. • Visual Components Oy (Digital the Proceedings of the Institution of Velez Osuna, R. & Tuokko, R. Modeling Enterprise Simulation Framework, Mechanical Engineers), IPROMS 2006 and Simulation as a Tool for Decision MASIY01) Special issues. Making in Adaptive Value Networks. • Satakunta University of AppliedHeilala, J., Montonen, J., Väätäinen, O. & International Conference on Sciencies (Modeling and Simulation Voho, P. Modeling and Simulation of Concurrent Enterprising, June 2006. Infrastructure, MASIT11) Manufacturing Systems in Different Velez Osuna, R., Tuokko, R., Heilala, J., • Industrial case studies: Life Cycle Phases. I*PROMS 2007 Lybeck, C. & Asmala, H. MS2Value Flexlink Automation Oy, Photonium Oy, Conference, 2–13 July 2007. – Modeling and Simulation of Raute Oy, Sandvik Mining andHeilala, J., Väätäinen, O., Montonen, J., Manufacturing Systems for Value Construction Finland Oy Laaksonen, T. & Kulmala, H. Decision Networks. EURO XXI, Iceland, July 2006. Support and Simulation Methods For Contact information Assembly System Sales Engineers. Project time scale Minna Lanz The 6th EUROSIM Congress, Ljubljana, 1.7.2005–31.12.2007 Tampere University of Technology, Slovenia, 9–13 September 2007. Department of Production EngineeringMoosmann, M. 2006. Change Project volume Tel. +358 40 849 0278 Management from A Production Cost Total funding 775 000 €, minna.lanz@tut.fi Perspective. MSc Thesis. Tampere Tekes share 548 000 € University of Technology, p. 87. Juhani HeilalaRodriguez Alvarado, J.R. 2008. Distributed VTT Technical Research Centre of Finland Simulation in Manufacturing using Tel. +358 20 722 5386 HLA. MSc Thesis. Tampere University of juhani.heilala@vtt.fi Technology. 51
    • In silico models of disease pathogenesis and therapy (TRANSCENDO) – MASIT13 Project background and goals available, the incidence has increased In November 1994, September The overall objective of TRANSCENDO rather steadily during the past 5 to 40 1995 and October 1997 the Type 1 Dia- programme is to build a comprehen- years. In Finland the annual incidence betes Prediction and Prevention Project sive modelling framework for studying of T1D is record high: 50/100 000 chil- in Finland (DIPP) was launched in the cit- human pathophysiology in silico, with dren (1 child in 170 develops T1D be- ies of Turku, Oulu and Tampere, respec- the initial focus area of Type 1 Diabe- fore the age of 15 years), and the an- tively. In 1999, the JDRF Center for Pre- tes (T1D). nual 3% increase in incidence contin- vention of Type 1 Diabetes in Finland The modelling goals of the project ues at a constant rate (Nejentsev, S. et was established around the project. This are to couple different modelling levels al. 1998). Based on recent US estimates is the largest project of this kind world- (cellular pathway-level knowledge, ani- T1D accounts for 10% of total Diabe- wide. By March 2004, the T1D risk alleles mal physiology, human physiology) to- tes cases, yet accounts for 40% of to- of >79 000 consecutive newborns and gether, predict the disease, its proper- tal Diabetes healthcare costs (approx. older siblings of the at-risk newborns ties, and responses to interventions and €83 billion annually in USA alone) (The have been studied, and >7 100 children to explain the experimental findings Economist 2004). In Finland, based on with genetic risk are in tight follow-up. such as clinical data. We aim to com- 1997 data, total costs/year for the treat- 11 000 newborns are screened annual- bine a variety of mathematical model- ment of diabetes was 858 million € and ly for genetic T1D risk. The program for ling approaches for these tasks, includ- the additional costs/year 471 million €. discovery of molecular markers using ing semantic and probabilistic model- T1D share was 12% of total costs and systems biology approaches has been ling, and biosimulation. We will apply 16% of additional costs (Kangas, T. launched in October 2004 as part of the our methodology to practical problems 2002). Tekes FinnWell programme. of direct relevance to drug discovery. Mathematical modelling is not new to biology. Many of the new math- Figure 1. Outline of the TRANSCENDO project. The models built from collected data ematical methods developed during and available knowledge will enable mappings across different levels of complexity. the past century have been motivated by biological questions. Given the re- cent progress in life sciences and rise of systems biology, it is likely that the two-way interaction between mathe- matical modelling and biology will on- ly intensify. Overload of information is an in- creasing problem in biomedical re- search and development. It is becom- ing evident that in order to put the vast amounts of data to use, they have to be put in context. In western countries T1D is the most common metabolic-endocrine disorder in children. In most countries where accurate T1D statistics have been52
    • Results rently, the integration of OAT with the that this experimental model may onlyThe results and deliverables of TRAN- visualization system is under work, with in part reflect the immune system andSCENDO project are directly applica- continuous development of our meg- T1D pathogenesis in man. Only a frac-ble to drug discovery, nutrition, health- Net software (as part of VISUBIOMED tion of NOD mice progress to disease,care, and bioinformatics domains. Giv- project). In the particular context of with the incidence of spontaneous di-en our approach of uniquely combin- TRANSCENDO, megNet is developed abetes being 60%–80% in females anding several levels of modelling (seman- and applied to integrate OAT ontology 20%–30% in males.tic, probabilistic, and biosimulation), we and T1D data We performed an NOD mouseexpect our approach will result in nov- As a by-product of the seman- study where 75 mice (30 female, 45el solutions for modelling complex sys- tic modelling development an article male) were monitored weekly with se-tems and phenomena. called “A text mining system for bioin- rum collection from age 3 weeks until formatics: requirements and architec- the development of diabetes and treat-Semantic modelling ture” has been written and presented ment with insulin for 4 weeks (progres-Ontology Aided Text miner (OAT) sys- in the ICDM2006 conference in Leipzig, sors), or 36 weeks of age in females andtem has been developed and imple- Germany in July 2006 (Karanta, I. et al. 40 weeks in males (non-progressors).mented. OAT extracts subject-pred- 2006). Also, one graduation work “Im- The cumulative incidence of diabetesicate-object triplets from biomedi- plementation of Ontology-Based Bio- was 39% in females and 20% in males,cal texts and inserts the triplets into logical Knowledge base” for the Helsin- which was lower than the colony inci-knowledge base as relationships be- ki University was prepared by Mika Ti- dence of 80% and 35%, respectively.tween concepts. The text material (cor- monen.pus) is collected from PubMed abstracts Physiology modellingbased on the selection criteria defined Animal studies Lipidomic analysis was performed onby the user. The current version cov- The non-obese diabetic (NOD) mouse a complete sample series from 26 fe-ers already the implementation of the is an excellent model of autoimmune male mice (12 progressors, 14 non-pro-overall framework from the text retriev- disease which is widely used in stud- gressors) and 15 male (7 progressors,al to the information extraction and fi- ies aiming at elucidating the patho- 8 non-progressors) mice, comprising anally knowledge base update. The final genesis of T1D, although it is also clear total of 1172 samples or 28.6 samples/domain specific knowledge base struc-ture (ontology) is currently under con-struction. Figure 2. Age-dependent progression of lipidomic profiles in females, viewed as ratios of In addition to developing the OAT, mean lipid concentrations of diabetes progressors (n=12) vs. the non-progressors (n=14).massive amounts of data related to mo-lecular interactions and pathways, func-tional genomics and biomedical ontol-ogies, and gene expression have beencollected from publicly available sourc-es. In order to store and manage thesedata in appropriate database formatsseveral parsers have been implement-ed. Furthermore, a system has beendeveloped for integrating and visual-izing various types of molecular inter-action and pathway data, and for inte-grating gene expression data with mo-lecular interactions and pathways. Cur- 53
    • mouse on average (733 from female More generally, we developed Sysi-Aho et al. Publication on NOD data, and 439 from male mice), with 154 li- probabilistic methods for integrating to be submitted. pids measured in each sample. When data from multiple sources under mul- Timonen, M. 2007. Implementation of comparing the lipid concentrations of ti-way experimental setups. In particular, Ontology-Based Biological Knowledge diabetes progressors and non-progres- we studied multivariate analysis of lipid- base. Master’s Thesis. Helsinki sors, the first weeks of life (3–10 weeks) omic data from experiments with a mul- University, dept. of Computer Science. were characterized by an overall lipid- ti-way experimental design. The result- Timonen, M. & Pesonen A. Combining lowering trend among the female pro- ing method is capable of overcoming Context and Existing Knowledge When gressors, while the period close to the the main restriction in high-throughput Recognizing Biological Entities - Early disease onset (15 week and older) was biological studies: small sample-size and results. PAKDD2008, Osaka, Japan, characterized by elevated triglycerides high dimensionality. Since the method is 20_23 May 2008. and phospholipids. Progressor female Bayesian a rigorous uncertainty estimate NOD mice had elevated lysoPC as com- is obtained, which is crucial in such con- Project time scale pared to IAA-negative non-progressors. ditions. The approach was extended to 1.1.2006–31.12.2007 Intriguingly, IAA positivity had the op- experiments integrating data from mul- posite association with diabetes pro- tiple sources, such as different tissues Project volume gression. IAA-positive (IAA+) mice with with mostly distinct lipids or different Total funding 499 333 €, high lysoPC were protected from diabe- measurement techniques. The promis- Tekes share 360 000 € tes, unlike the IAA+ female mice with ing probabilistic modeling framework low lysoPC. This suggests that the met- is currently being further extended into Project participants abolic profile in combination with the HMM-based time-series modeling prob- • VTT Technical Research Centre of autoimmune status may be an impor- lems and into translational modeling. Finland, Biotechnology (Coordination, tant checkpoint in diabetes progres- Bioinformatics, Physiology modelling, sion. Additionally, due to their oppo- Publications and reports Metabolomics) site association with disease progres- Huopaniemi, I., Suvitaival, T., Nikkilä, J., • University of Turku (Animal models) sion IAA measurement in combination Orešič, M. & Kaski, S. 2009. Two-way • Helsinki University of Technology with lysoPC may help predict diabetes analysis of high-dimensional collinear (Probabilistic models) in NOD mice. data. Data Mining and Knowledge • VTT Technical Research Centre of Discovery, Volume 19, Issue 2, p. Finland, Information Technology Probabilitic modelling and 261_276. (Text mining, Semantic modelling) virtual clinical trials Huopaniemi, I., Suvitaival, T., Nikkilä, J., We developed novel computational Orešič, M. & Kaski, S. 2009. Multi- statistical methods for analyzing me- Way, Multi-View Learning. NIPS 2009 tabolomics data from structured exper- workshop on Learning from Multiple iments: time series and multi-way set- Sources with Application to Robotics. ups, where the different measurements Karanta, I. et al. 2006. A text mining system can even have different variables. for bioinformatics: requirements For time-series measurements we and architecture. ICDM2006, Leipzig, developed models for discovering latent Germany. state progressions underlying lipidomic Nikkilä, J., Sysi-Aho, M., Ermolov, A., profiles, using Hidden Markov Models Seppänen-Laakso, T., Simell, O., Kaski, S. (HMM). Type 1 diabetes was the appli- & Orešič, M. 2008. Gender-dependent cation area. The model was extended to progression of systemic metabolic translational modeling of lipidomic ex- states in early childhood. Molecular periments from multiple species. Systems Biology, Volume 4, Article 197.54
    • From discrete to continuous models for multiphase flows – MASIT14Background Each of the five research groups have in challenging environments such as inAlthough modelling and simulation is been developing novel approaches in the Barents Sea. The other mixing appli-nowadays an established method to modelling of relevant phenomena. The cation examples are agitated leaching instudy different phenomena in proc- necessary experimental work has been the mining industry, rubber crumb, crys-ess industry, as well as to design equip- mainly on the responsibility of Lap- tallization, precipitations. In this attemptment where these phenomena take peenranta University of Technology, large-eddy simulations (Zamankhanplace, there are problems which are out Department of Chemical Technology. & Huang 2006) of a turbulent flow in aof the reach of the conventional mod- solid-liquid, baffled, cylindrical mixing Resultselling methodology. Multiphase flows, vessel, as illustrated in Figure 1, with acomplex fluids, solids with imperfec- Particle transport method large number of solid particles, are per-tions in their crystalline structure and A novel numerical technology, the par- formed to obtain insight into the fun-polymers often pose modelling prob- ticle transport method (PTM), has been damental aspects of a mixing tank. Pa-lems where classical continuum level studied to solve convection-dominated rameters that affect water-sodium for-descriptions fail or are invalid. Moreo- problems. The method has been test- mate mixing are the shape of solids, sol-ver, many of the physical phenomena ed on linear convection, convection-re- id size distribution, solid concentration,involved in process technology are not action and convection-reaction-diffu- solid density, and water density and vis-known well enough to allow a precise sion problems. The approach has been cosity. The impeller-induced flow at theand reliable mathematical description. compared with existing numerical blade tip radius is modelled by usingExamples of many such phenomena methods, such as Discontinuous Galer- the dynamic-mesh Lagrangian meth-are the coalescence of gas bubbles in kin method and a high-resolution finite od. The simulations are four-way cou-gas-liquid flow or turbulent behaviour volume method proposed by R. LeV- pled, which implies that both solid-liq-of fluids in many cases. eque. The results are published in the uid and solid-solid interactions are tak- articles (Smolianski et al. 2007), (Shipi- en into account. By employing a softObjectives lova et al. 2007). For practical applica- particle approach of Zamankhan andThe aim in this project was to devel- tions, the particle transport method has Bordbar (Zamankhan & Bordbar 2006),op new models and computational ap- been employed to gain subgrid accura- the normal and tangential forces areproaches to several applications where cy in simulations of unsteady-state crys- calculated acting on a particle due tomodelling so far has been unsatisfac- tal growth (Hatakka et al. 2005a, 2005b) viscoelastic contacts with other neigh-tory or impossible. Simulation tools, and separation processes (Shipilova et bouring particles. The results suggestbased on novel numerical methods al. 2007, Shipilova 2007). that the granulated form of sodium for-were developed. The applications were mate may provide a mixture that allowsapproached by elementary cases which Mixing tank faster and easier preparation of formaterepresent subproblems of the complete Traditionally, solid-liquid mixing has brine in a mixing tank. In addition it iscases. The modelling of the elementa- always been regarded as an empirical found that exceeding a critical size forry cases was supported by experimen- technology with many aspects of mix- grains phenomena, such as caking, cantal activities, which are needed also for ing, dispersing and contacting where be prevented.validation purposes. related to power draw. One important application of solid-liquid mixing is the Two-fluid modelProject implementation preparation of brine from sodium for- In this subproject the purpose was toThe project was carried out as co-op- mate. This material has been widely develop a novel solution method for aeration of five different laboratories. used as a drilling and completion fluid two-fluid model. The governing equa- 55
    • Figure 1. Upper: Schematic and some dimensions of a standard baffled tank with Rushton radial turbine used in the present attempt. (a) Gas-liquid mixing tank in which the interface is located at H = 260 mm. (b) Three-phase mixing tank with the solid phase shown to be deposited at the bottom. Lower: Standard impellers. (a) A pitched blade turbine. (b) A disk (Rushton) turbine with six flat blades. tions are the time-averaged field equa- merically compute turbulence in mul- terdigital micromixers. As a result, the tions for liquid and gas. The solution tiphase flows. Three lines of research configuration of the mixers were op- method is based on a pressure-cor- have been pursued. These are: 1) The timized and improvements suggest- rection approach that has been imple- parameterization of small-scale dynam- ed by Turunen et al 2006. The veloc- mented on the FINFLO code. The goal is ics in the context of passive-scalar tur- ity contour in the microchannel is not that the interfacial transport phenom- bulence, 2) Dynamics of two miscible uniform. After optimization, the flow ena that require modelling can bene- fluids in the presence of turbulent con- distribution becomes more uniform. fit from the development work made vection under the Boussinesq approxi- Furthermore, CFD models based on in the other parts of this project. The mation, 3) The study of two-dimension- the VOF method in ANSYS CFX 10 and flow model developed has been fur- al convection model qualitatively corre- in Fluent 6 have been developed for ther tested using a cavitating hydrofoil sponding to the Stokes approximation the simulation of drop formation in a case. The basic solution method has al- of the Rayleigh-Taylor model. single hole in solvent extraction (So- so been studied and new SIMPLEC type leymani et al. 2008). The VOF method pressure coupling has been used in a Flow in microchannels and is used for the calculation of the lo- on solids surfaces single-phase cases. cation of the interface between the Numerical simulation in narrow chan- two liquid phases. Simulations were Turbulence in multiphase flows nels was applied to study the flow dy- carried out to study the effect of hole The subproject was aimed to provide namics and mixing characteristics of size and shape on drop formation. theoretical background for efforts to nu- liquids in commercial standard slit in- The material properties of the plate,56
    • Figure 2. Temporal evolution of the drop shapes from numerical calculations (top Celani, A., Mazzino, A., Muratore-Ginanneschi,row) and experimental study (bottom row). The diameter of the hole is 3 mm and the P. & Vozella, L. 2009. Phase-field modelsuperficial velocity of the liquid in the hole 14 cm s-1. for the Rayleigh-Taylor instability of immiscible fluids. Journal of Fluid Mechanics, Vol. 622, 115–134. Haario, H., Smolianski, A. & Luukka, P. 2007. Numerical study of dynamics of single bubbles and bubble swarms. To appear in Appl. Math. Modelling. Hatakka, H., Shipilova, O., Haario, H. & Kallas, J. 2005b. Modeling of Reactive Crystallization: Using Particle Transport Method in Unsteady-State Modeling of Crystal Growth. Proceedings of the 16th International Symposium on Industrial Crystallization, p.145–150. Dresden, Germany, September 2005. Kamali, R.M., Laari, A., Sha, Z. & Turunen, I. Prediction of bubble size and interfacial area in bubble column CFD simulations through solutionsuch as the wetting properties and which are out of the reach of conven- of population balance equations.surface roughness, are taken into ac- tional modelling methodology. This will European Congress of Chemicalcount by setting the contact angle lead to improved design of process and Engineering-6, 16–21 Septemberbetween the liquid and the solid. The process equipment, and hopefully also 2007, Copenhagen, Denmark.VOF method makes it also possible to to new innovations in the field. Kamali, R. M., Laari, A. & Turunen, I. A studycapture interfacial phenomenon such of hydrodynamics and interfacialas drop breakage and coalescence. Publications momentum exchange terms inSome simulation results are shown in Arponen, H. & Horvai, P. 2007. cylindrical bubble column by CFD,Figure 2. The shown results demon- Dynamo Effect in the Kraichnan European Congress of Chemicalstrate that the VOF method is well ca- Magnetohydrodynamic Turbulence. Engineering-6, 16–21 Septemberpable in handling this type of flow sit- Journal of Statistical Physics 129, 205. 2007, Copenhagen, Denmark.uations and the results are well in line Berti, S., Bistagnino, A., Boffetta, G., Mousavi, M. & Zamankhan, P. Largewith experiments. The CFD model Celani, A. & Musacchio, S. 2008. Two- Eddy Simulations of a Brine-Mixingcan be used to optimize the size and dimensional elastic turbulence. Tank. In proceedings of the 25thshape of the holes. It can be also used Physical Review E 77, 055306(R). International Conference on Offshoreto investigate the effects of the phys- Berti, S., López, C., Vergni, D. & Vulpiani, A. Mechanics and Arctic Engineeringical properties of various liquid-liquid 2008. Combustion dynamics in steady (OMAE 2006), Hamburg, Germany,pairs and the construction materials compressible flows Europhysics Letters June 4th–9th 2006 (Paper numberof the sieve plate. 83, 54003. OMAE2006-92082). Berti, S., López, C., Vergni, D. & Vulpiani, Shipilova, O., Sainio, T. & Haario, H.Impacts A. 2007. Discreteness effects in a 2008. Particle transport methodThe results will, especially after further reacting system of particles with finite for simulation of multicomponentdevelopment, enable the modelling interaction radius. Physical Review E chromatography problems. Journal ofof multitude of process phenomena 76, 031139. Chromatography A, 1204, 1, 62–71. 57
    • Shipilova, O., Smolianski, A. & Haario, H. Soleymani, A., Laari, A. & Turunen, I. Project participants 2007. A fast high-resolution algorithm Simulation of drop formation in a • Lappeenranta University of Technology, for linear convection problems: Particle single hole in solvent extraction Department of Information Technology transport method. International using the Volume-of Fluid method, • Lappeenranta University of Technology, Journal for Numerical Methods in Chem. Eng. Res. Des., accepted for Department of Chemical Technology Engineering, Vol. 70, p. 655–684. publication. • Lappeenranta University of Shipilova, O., Smolianski, A. & Haario, H. Turunen, I., Soleymani, A. & Kolehmainen, Technology, Department of Energy and 2007. Particle Transport Method for E. CFD-based optimization of standard Environmental Technology Convection Problems with Reaction slit interdigital micromixer. In the book • University of Helsinki, Department of and Diffusion. International Journal for of abstracts of the 9th International Mathematics and Statistics Numerical Methods in Fluids, Vol. 54, p. Conference on Microreaction • University of Helsinki 1215–1238. Technology (IMRET 9). Potsdam/Berlin, • Helsinki University of Technology, Smolianski, A., Shipilova, O. & Haario, H. 6.–8.9.2006. Laboratory of Applied Thermodynamics A Fast High-Resolution Algorithm for Zamankhan, P. & Bordbar, M.-H. 2006. Linear Convection Problems: Particle Complex flow dynamics in dense Contact information Transport Method. Int. J. Num. Meth. granular flows: Part I Experimentation. Heikki Haario Engng., Published online 2006, in Press J. Applied Mech. (T-ASME), vol. 73. Lappeenranta University of Technology, 2007. Zamankhan, P. & Huang, J. 2006. Department of Information Technology Soleymani, A., Kolehmainen, E. & Turunen, Dynamical Simulations of Vertical Tel. +358 5 621 2825 I. Numerical and experimental Vibrated Granular Materials. J. Fluid haario@users.csc.fi investigations on liquid mixing in Engineering (T-ASME). T-type micromixers. Book of Abstracts, Ilkka Turunen p. 304–305. 9th International Project time scale Lappeenranta University of Technology, Conference on Microreaction 1.7.2005–30.6.2008 Department of Chemical Technology Technology, 6.–9.9.2006, Potsdam/ Tel. +358 5 621 2165 Berlin, Germany. Project volume ilkka.turunen@lut.fi Soleymani, A., Laari, A. & Turunen, I. Total 396 200 €, Tekes share 100%. Simulation of drop formation in a single hole in solvent extraction using VOF method. European Congress of Chemical Engineering-6, 16– 21 September 2007, Copenhagen, Denmark.58
    • Virtual engineering in design, training and completion of demanding maintenance worktasks (Virvo) – MASIT15Background These studies were focused on the Phase III: The created generic Vir-Service is nowadays essential element maintainability design of rock crush- vo concept (Figure 2) was tested in twoin machine manufacturing business. ers and elevators. industrial case studies, and it was rede-Companies want to be also service pro- fined based on feedback. Also maturi-viders for their products. The product li- Project implementation ty of technology tools and practical in-fecycle must be managed so that the Phase I: The Virvo project started with formation flows between tools and sys-requirements of customers and service state-of-the-art study. It was focused tems were evaluated.are taken into account in the product on literature related to usage of virtu- Phase IV: The Virvo concept andengineering and design phase. Industri- al engineering in maintainability de- findings from industrial case studiesal maintenance operations involve nu- sign. A survey of virtual engineering were published.merous risks, and downtime at industri- software and hardware products in theal plants is very expensive and econom- market was carried out. Engineers, man- Resultsically threatening. To manage mainte- agers and workers in involving compa- Summary of the main results:nance related risks, good routines and nies were interviewed in order to list re- • State of the Art report: Literaturework guidelines are required. Virtual En- quirements for maintainability and vir- and software surveygineering methods and tools, like Virtu- tual engineering. Based on all this infor- • Industrial requirements foral Reality (VR), Augmented Reality (AR) mation, a roadmap for the project was maintainability planningand digital human models (DHM) are generated. • Roadmap for the projectpotential means for enhancing mainte- Phase II: Based on information • Research exchange visit innance work task planning. They are rel- gathered in Phase I, a generic Virvo con- University of Málagaatively new tools in industrial engineer- cept and set of methods were created. • Generic Virvo method: Task analysising and one of key challenges is to inte- The concept includes a process and methods, design principles,grate these new methods into product guidelines, as well as tools and meth- maintainability analysis methodsprocesses and product lifecycle man- ods for planning and analysing mainte- in virtual environment, safety andagement. nance work and maintainability. ergonomics analysis methods.Objectives Figure 1. Maintainability planning of a mobile rock crusher machine in virtual environment.The research project Virvo was launchedin 2006 with the following aims: 1) Totest the applicability and requiredlevel of virtual engineering tools, 2)to develop computer-aided meth-ods for designing, training and com-pletion of critical maintenance worktasks in industry, and 3) to integratethem into PLM. Aim was to introducea comprehensive method (Figure 1)for virtual design, planning, trainingand guidance of critical manual worktasks. The method was also plannedto be tested in industrial case studies. 59
    • • Virtual engineering tools for Virvo detailed description of the method’s ling. They play a more active role in method: Tool for modelling and tasks: building the VE and planning a task updating work sequences in 1. Initial data collection: Ideally, data is in detail. virtual environment, driver for created while the product and the sys- 4. Task planning: All the work phases low-cost haptics device in virtual tem are being conceptually modelled; related to the designed mainte- environment the latest stage to compile initial data nance tasks are planned and ana- • Technology maturity assessments: is when chosen critical maintenance lyzed in this phase. This includes in Laser scanning in physical tasks are analyzed and designed in de- addition to the actual maintenance environment modelling, CAVE tail. Initial data can also be gathered in task also the planning of prepara- tests in SeAMK VR laboratory, the early phases of product develop- tory and afterward actions, which low end virtual environments, ment or from the product data man- together form the description of commercial software tools testing agement system (PDM). In addition, maintenance process. Task plan- and assessment usability surveys enable gathering ning includes also the definition of • Industrial case studies: 1) Maintain- valuable information from the end resources and tools, and estimation ability planning in new generation users of the product. of the time needed in the task. rock crusher development, 2) 2. Task modelling: The task and the 5. Plan inspection: After virtual model- Elevator modernisation planning working environment should first ling, the task plan must be inspected and analysis. be modelled conceptually using by a development group, represent- simple flowcharts. Modelling here ing workers, designers, experts, and The analysis process of Virvo concept has two aims: first, to create a basis management, to ensure that all re- (Figure 2) consists of the following for input for virtual modelling of the quired knowledge and information seven tasks: initial data collection, task system, and, second, to assess the is available during design and plan- modelling, virtual modelling, task plan- criticalness of the tasks. ning. In addition, usability, ergonom- ning, plan inspection, task training, and 3. Virtual modelling: According to the ics, and safety must be assessed. documentation (Mäkiranta et al. 2009). method, machine design and main- 6. Task training: Task training can be These tasks link and exploit design en- tenance planning occur simultane- done in a training simulator, con- gineering data and relay constructive ously. 3D CAD models, created in sisting of 3D CAD models, virtual information on product maintainabil- the machine design phase, are used environments, and instructions cre- ity to the product process. Below is a already for conceptual task model- ated during machine design and maintenance planning. The training Figure 2. Generic Virvo Concept includes seven steps analysis process for maintain- program can be built on models ability planning and supporting processes, methods and tools for it. (i.e., flowcharts) describing the pro- cedures of the work task. 7. Documentation and guidance: Pro- ducing maintenance materials (doc- umentation and guidance material) is challenging, because the contents must be easy to generate and cost- effective. Of course, e.g., 3D models and animations created earlier in the product lifecycle and product development could be re-used. VE and maintenance materials can be automatically generated and up- dated by virtual simulation software60
    • reading the data from the database Computer Interaction, HCI 2009, 19–24 13th International Conference on during VE generation. July 2009, San Diego, CA, USA. 10 p. Human-Computer Interaction, HCI Lind, S., Leino, S.-P., Viitaniemi, J., Helin, 2009, 19–24 July 2009, San Diego, CA,Impacts K., Multanen, P., Mäkiranta, A. & USA. 10 p.Results of the Virvo project can be ex- Heikkilä, J. Development of a virtual Viitaniemi, J., Lind, S., Evilä, T. & Helin, K.ploited widely in different kinds of fac- environment for promoting safety in Task analysis and rehearsal of industrialtories, plants and ma-chine systems. machine maintenance. In: Mondelo, maintenance operations in virtualWith virtual engineering based meth- P., Karwowski, W., Saarela, K., Hale, environments – The viewpoint ofodology manual and remote operat- A. & Occipinti, E. (eds.) Proceedings safety. In: Knezevic J. (ed.) Proceedingsed maintenance tasks can be designed, of the 6th International Conference of 1st International Symposium onplanned, documented, trained and on occupational Risk Prevention, Understanding Human Limitations andguided efficiently. The safety of man- ORP´2008, Coruña, Galicia, Spain, 14– Errors. 24–25 September 2007, MIRCEual work improves when tasks can be 16 May 2008. 14 p. Akademy, Exeter, UK.planned and better trained. On the ba- Lind, S., Leino, S.-P., Multanen, P., Mäkiranta,sis of Virvo project, EU project called A. & Heikkilä, J. A Virtual Engineering References“ManuVAR – Manual Work Support Based Method for Maintainability Mäkiranta, A., Multanen, P., Leino, S.-P.Throughout System Lifecycle by Ex- Design. Proc. of 4th International & Lind, S. CM. Method and tools forploiting Virtual and Augmented Reali- Conference in Maintenance and Facility machine maintainability design in VE.ty” was launched in 2009. Management. Rome, 22–24 April 2009. The 6th International Conference on CNIM – Italian National Committee for Condition Monitoring and MachineryInternational cooperation Maintenance. p. 117–122. Failure Prevention Technologies, CM,During the Virvo project research ex- Multanen, P., Mäkiranta, A., Helin, K. & Lind, 23–25 June 2009, Dublin, Ireland. 12 p.change visit was made at the Univer- S. Improving the maintainability ofsity of Málaga, Spain. A researcher vis- elevators with virtual tools. In: Lustig, Project time scaleited Professor Arcadio Reyes Lecuona’s A. (ed.) Elevator Technology 17. Proc. 24.5.2006–31.8.2009Diana Group of Man-Machine Interfac- of Elevcon 2008, 11–13 June 2008,es and Virtual Reality. The Diana Group Thessaloniki, Greece. p. 278–288. Project volumeis specialised in haptics and training in Multanen, P., Mäkiranta, A., Nuutinen, P., Total 1 043 000 €, Tekes share 510 000 €virtual environments. Leino, S.-P., Helin, K. & Lind, S. Adaptation of Virtual Tools to Support Cost-effective Project participantsDissemination Maintenance of Machines. Comadem • VTT Technical Research Centre of FinlandResults of the project were disseminat- 2009, 9–11 June 2009, San Sebastian, • Tampere University of Technology/IHAed in several international conferences Spain. Tekniker, Spain. 8 p. • Seinäjoki University of Applied Sciences(see publications). Project and its results Mäkiranta, A., Multanen, P., Leino, S.-P. • Metso Mineralswere also promoted in several nation- & Lind, S. CM. Method and tools foral seminars. machine maintainability design in VE. Contact information The 6th International Conference on Simo-Pekka LeinoPublications Condition Monitoring and Machinery VTT Technical Research Centre of FinlandLeino, S.-P., Lind, S., Poyade, M., Kiviranta, Failure Prevention Technologies, Tel. +358 40 7377 184 S., Multanen, P., Lecuona, A., Mäkiranta, CM2009, 23-25 June 2009, Dublin, simo-pekka.leino@vtt.fi A. & Muhammad, A. Enhanced Ireland. 12 p. Industrial Maintenance Work Task Poyade, M., Lecuona, A., Leino, S-P., Petteri Multanen Planning by Using Virtual Engineering Kiviranta, S., Viciana-Abad, R. & Lind, Tampere University of Technology Tools and Haptic User Interfaces. 13th S. A High-Level Haptic Interface for Tel. +358 50 599 4329 International Conference on Human- Enhanced Interaction within Virtools™. petteri.multanen@tut.fi 61
    • Modelling changing needs of consumers (KULTA) – MASIT16 & MASIT36 Background their needs. The different ways of cre- that are organized together with re- Developing methods and understand- ating knowledge of consumers within searchers, company people and in- ing of consumer needs and habits in business organizations has been a cen- volving consumers (National Consum- both academic and business contexts tral issue. The aim has been to develop er Research Centre consumer panel) has been the underlying motivation 1) prototypes of new models and proc- which successfully incorporate knowl- for the KULTA project. Strong existing esses and 2) suggestions of how to use edge from research and business part- adaptive informatics and qualitative different models, and 3) ways to under- ners as well as from daily life of Finnish consumer research were brought to- stand consumer practices in product consumers. International implementa- gether in close relation to business part- and service development. tion of the project is covered with three ners. The project begun with analyzing over six months visiting scholarships in how companies in different fields of B- Project implementation universities relevant to the topic and to-C industries understand their cus- The project has taken place in two peri- the modelling methodology (Universi- tomers and how conceptualizing and ods. The first period (Kulta I) lasted from ty of California, Berkeley, Stanford Uni- anticipating the changing needs of August 2006 to December 2007 and versity and University of Edinburgh) and consumers can be developed by com- the second period from January 2008 continuous collaboration with Lancas- bining adaptive informatics and qualita- to April 2010 (Kulta II). The research ter University (UK). tive advanced research methods. It was partners in the network have been the found that there is a lot of data within Aalto University School of Science and Results the companies about markets that do Technology (former Helsinki Universi- As part of studying and developing not turn into understanding changing ty of Technology), National Consumer methods and models of consumer busi- consumer needs or adequately support Research Centre, University of Helsin- nesses, researchers have been closely the decision making processes in com- ki (Department of Philosophy) (phase involved with business organizations panies. I), and the Aalto University School of that are eager to develop their strate- Economics and University of Helsinki gies of using consumer data. These eth- Objectives (former Helsinki School of Economics) nographical and action theory oriented The basic objective of the project has (phase II) . Companies involved in the case studies have been focused on de- been to study how developing new project have been Fazer Bakeries Fin- veloping new practices and tools for models of consumer behaviour can land (phase I), Fujitsu Services (phase I), processing the complex phenomena of benefit both consumer participation Elisa (phase I), Helsingin Energia (phase consumers’ needs. The outcomes of this and product and service development II), Nokia (phase II), RAY (Finland’s Slot collaboration are for example a concept in companies. From the business sector Machine Association phases I, II), Pöyry of a new tool for gathering, fostering point of view, the aim of the project has (phase II), Leiki (phases I, II) and Penta- and using innovative ideas developed been to find and apply methods to op- gon Design (phase I). by researchers Kotro and Paukkeri. This erate with complex data and to develop The project was implemented in new tool can be applied as a support new approaches to changing consumer close collaboration between the re- system for organization memory crea- needs into developing business. An im- search partners, with the companies tion and research and development da- portant objective has also been to pro- involved, within the host institutions ta base that is linked to the practices of vide multiple complementary views on and with the national and internation- organizational innovativeness (Paukkeri models that are used in analyzing com- al collaborators. Important part of the and Kotro, 2009). One motivation for pany data concerning consumers and implementation have been workshops promoting innovativeness has risen62
    • from the research on corporate uses of tational models not only have various consumers’ active participation, findingstrategy tools. Stenfors (2007) conclud- roles within a specific scientific or tech- ways in which communities of peopleed in her PhD research that most of the nological domain, but also travel across or agents can benefit from each oth-strategy tools used in companies con- disciplines. A travelling computation- er is a question shared by the machinecentrate on supporting efficiency of ex- al template is a computational meth- learning community and social scienc-isting procedures but do not facilitate od that has a variety of applications es alike. In our research, we have devel-innovation and relevant change. in different scientific and technologi- oped a methodological framework for Based on Pantzar and Shove’s cal domains. We have analyzed in de- modelling lay and expert knowledge as(2010) practice theory, a visualization tail how adaptive informatics modelling well as individual and socially construct-and simulation model called Pracsim methods can be considered as compu- ed knowledge (Honkela et al. 2009).has been developed in the project. The tational templates and how this facili- In summary, the results of thefirst version of the system was used to tates their general applicability in vari- project are new methods of generatingdemonstrate the basic concepts of the ous domains (Knuuttila et al. 2007, Knu- and analyzing data, better processestheory and to visualize its dynamics uttila and Merz 2009). within the partnering business organ-(Lindqvist et al. 2007). The second ver- In the energy business case, the izations in relation to customer involve-sion of Pracsim combined practice-lev- focus became electricity pricing mod- ment and new perspectives to consum-el and consumer-level modelling. The els, because they contain assump- er value creation.first and second versions of the model tions about consumer practices in en-were theory-driven. The third version of ergy use. The researchers studied the ImpactsPracsim is data-driven so that the prac- existing models, gathered new data The results of the KULTA project have antices are modelled based on real world from energy use, developed concepts impact within the consumer businessdata (Malmi et al. 2009). In the prac- for new models, and validated these based on the modelling techniquestice theory, it is assumed that practices concepts with consumers (Lovio et al. and simulation models that have beenconsist of three basic elements, name- 2010). Compared to the existing pric- developed and better understandingly materials (materials, technologies ing models, the new concepts fit bet- their use in business practices. The re-and tangible, physical entities), imag- ter the variety of energy use practices sults of the project improve the use ofes (domain of symbols and meanings), in different market segments. Thanks to models and the application of model-and skills (competence, know-how and an increased interaction with consum- ling and simulation methods withintechniques) (Pantzar and Shove 2010, ers and deepened insight into their en- business practices. The project resultsShove et al. 2011). The theory has been ergy use practices, it was possible to in- provide means to improve businessused to re-evaluate companies’ view on clude not only economic-rational pur- processes by indicating ways to benefittheir customers through increased un- chase drivers, but also drivers that re- from customers and employees as ac-derstanding of the everyday life. In the late to social energy use in communi- tive innovators and by bringing up theresearch, a central aspect has been to ties, which is a totally new approach to possibility to model consumer activitiesdeepen understanding on the rhythms developing B-to-C models. as practices. This approach is directly re-of everyday life (Pantzar and Shove A distinction has traditionally been lated to the Web 2.0, which is based on2009, Pantzar 2010). made between experts in possession of the active role of the users themselves. We have also considered adaptive systematic knowledge, and lay persons Based on this, the project fits well withinformatics models from a strategic lev- possessing only contextual knowledge. the overall goal of the MASI technolo-el. Traditionally, it has been thought However, there has been a clear shift gy programme which is to promote thethat models are primarily models of in consumer and innovation research use of modelling and simulation meth-some target systems, since they repre- from the viewpoint of the recipient of ods and techniques that can improvesent partially or completely the target technology towards that of an active the competitiveness of a business. Thissystems. However, sometimes compu- consumer. Related to the increase in kind of improvement takes place, e.g., 63
    • by accelerating the product develop- In addition to the longer visits de- Knuuttila, T., Rusanen, A.-M. & Honkela, ment process, by creating new forms scribed above, the senior researchers in T. 2007. Self-Organizing Maps as of service business, and through new the project further promoted interna- Travelling Computational Templates. applications in business processes and tional cooperation by shorter visits to Proc. of IJCNN 2007, Int’l Joint practices. Stanford University (Pantzar, Lovio and Conference on Neural Networks, Honkela), Google, Nokia RC (Palo Alto), p. 1231–1236. International cooperation and UC Berkeley, UC Southern California, Knuuttila, T. & Merz, M. 2009. dissemination Indiana University Bloomington, Pur- Understanding by Modeling: An From September 2008 to May 2009, due University, and University of Chi- Objectual Approach. H. de Regt, S. Tanja Kotro (National Consumer Re- cago (Honkela). The dissemination ac- Leonelli and K. Eigner (eds.) Scientific search Centre) worked as a visiting tivities at the national level have also Understanding: Philosophical scholar in Stanford University Human- been active. Contacts with the partic- Perspectives. Pittsburgh: University Sciences and Technologies Advanced ipating companies and organizations of Pittsburgh Press. Research institute led by Professor Keith took often place at a weekly level. A Kotro, T., Lindh-Knuutila, T. & Hiltunen, Devlin and took part in both advanced large number of meetings, workshops E. 2009. How to analyze various studies in organizational theory and and seminars were organized both with consumer data in the future? seminars and round tables on human the consortium members and external Proceedings of the Futures of the computer interaction. stakeholders. Central results of the re- Consumer Society, 11th International From January to June 2009, Tiina search have been published as journal Conference of Finland Futures Lindh-Knuutila (Aalto University School and conference articles and technical Research Centre and Finland of Science and Technology) visited the reports. Futures Academy. Artificial Intelligence group at the In- Lindqvist, L., Honkela, T. & Pantzar, M. ternational Computer Science Insti- Selected publications 2007. Visualizing practice theory tute (ICSI) at University California Ber- Heiskanen, E., Hyysalo, S., Kotro, T. & Repo, through a simulation model. Technical keley, hosted by Professor Jerome Feld- P. 2010. Constructing innovative Report E9, Helsinki University of man. During the visit, Lindh-Knuutila users and user-inclusive innovation Technology. concentrated on obtaining consumer communities. Journal of Technology Lovio, R., Mickwitz, P. & Heiskanen, E. 2010. knowledge from textual data and stud- Analysis and Strategic management. Path dependence, path creation and ied a computational semantic represen- Forthcoming. creative destruction in the evolution tation system developed at ICSI. Honkela, T., Janasik, N., Lagus, K., Lindh- of energy systems. In: Wuestenhagen, During spring 2009, Mari-Sanna Knuutila, T., Pantzar, M. & Raitio, J. 2009. R. & Wuebker, R. (eds.) Handbook of Paukkeri (Aalto University School of Sci- Modeling communities of experts – Energy Entrepreneurship. Edwar Elgar ence and Technology) visited the Hu- conceptual grounding of expertise. (forthcoming). man Communication Research Centre Technical Report TKK-ICS-R24, Helsinki Malmi, E., Raitio, J. & Honkela, T. 2009. and the Institute for Communicating University of Technology. Modeling practice diffusion with and Collaborative Systems in the School Johnson, M. & Neuvonen, A. 2009. Images an agent-based social simulation of Informatics at the University of Edin- of Energy Consumers: Standalone framework. Proceedings of the burgh, United Kingdom. During the Households or Communities?. 6th European Social Simulation visit Paukkeri concentrated on devel- YHYS Autumn Colloquium 2009, Association Conference, ESSA 2009, oping software for analysing customer Environmental governance of p. 53, Guildford, U.K., September 2009. data. In Edinburgh, Paukkeri contacted natural resources, the economy, and Extended abstract. many researchers on statistical natural consumption. 26–27 November 2009, language processing field. Finnish Environment Institute, Helsinki.64
    • Pantzar, M. 2010. Future shock – Project time scale Phase II (Kulta II) from January 2008 to Discussing changing temporal Kulta I: August 2006 – December 2007 April 2010: architecture of daily life, Journal of Kulta II: January 2008 – December 2009 • Aalto University School of Science and Future Studies, forthcoming. (April 2010) Technology (former Helsinki UniversityPantzar, M. & Shove, E. 2009. Time in of Technology) practice – Discussing rhythms of Project volume • National Consumer Research Centre practice complexes. Ethnologia Kulta I: Total funding 674 000 €, • Aalto University School of Economics Europaea. Journal of European Tekes share 485 000 € and University of Helsinki (former Ethnology, forthcoming. Kulta II: Total funding 961 000 €, Helsinki School of Economics)Pantzar, M. & Shove, E. 2010. Tekes share 670 000 € • Helsingin Energia, Leiki, Nokia, RAY Understanding innovation in practice: (Finland’s Slot Machine Association), a discussion of the production and Project participants Pöyry reproduction of Nordic Walking. Phase I (Kulta I) from August 2006 to Technology Analysis & Strategic December 2007: Contact information Management, forthcoming. • Aalto University School of Science and Timo HonkelaPaukkeri, M.-P. & Kotro, T. 2009. Framework Technology (former Helsinki University Aalto University School of Science and for analyzing and clustering short of Technology) Technology message database of ideas. In • National Consumer Research Centre Tel. +358 50 384 1578 Proceedings of the 9th International • University of Helsinki (Department of timo.honkela@tkk.fi Conference on Knowledge Philosophy) Management and Knowledge • Fazer Bakeries Finland, Fujitsu Services, Tanja Kotro Technologies (I-KNOW’09), p. 239–247, Elisa, Kaisaniemen dynamo, RAY National Consumer Research Centre Graz, Austria, September 2009. (Finland’s Slot Machine Association), Tel. +358 50 550 8836Shove, E., Pantzar, M. & Watson, M. 2011. Leiki, and Pentagon Design tanja.kotro@ncrc.fi Everyday life: the dynamics of social practices. N.Y: SAGE.Stenfors, S. 2007. Strategy Tools and Strategy Toys: Management Tools in Strategy Work. Acta Universitatis oeconomicae Helsingiensis. PhD Thesis. 65
    • Combining multiblock and CFD modelling – MASIT17 Background The problem with CFD is that it still re- simple one-phase flow and the make In recent years the use of various com- quires long computation times, when the division for the multi-block model putational methods to reduce the need dealing complex systems such as mul- based on the results from CFD. With this of expensive experiments has been tiphase or non-Newtonian flows. The way the complex system can be solved used in chemical engineering appli- accuracy of the models is also often lim- quite accurately relatively fast. cations. Because in industrial scale the ited in these cases. Besides model development also rate of input power is rarely sufficient To solve these complex systems a model validation was made and vari- to achieve ideal level of mixing, tradi- simpler approach can be used. In the ous experimental techniques were de- tional models developed earlier often multi-block model, the flow domain is veloped and compared. fail. This has lead to unnecessary high divided into larger blocks than in CFD, over sizing of energy sources. In the last and each block is considered ideally Actions decades, the computational capacity mixed (see figure 1 ). Multi-block solves Two zoning algorithms were developed has increased so much that the inho- the system fast, but the optimal division at VTT and implemented in commer- mogeneities of the system can be im- (block size, shape etc.) of the system has cial CFD program Fluent. The first algo- plemented to the models. been difficult to find, because of the in- rithm is based on region growing meth- Computational Fluid Dynamics homogeneous state in the vessel. od with criteria to monitor zone topol- (CFD), which solves the Navier-Stokes ogy. The algorithm starts with a seed and continuation equations numerical- Objectives cell and grows a zone around it by join- ly, has been the main tool for this pur- In this project the main task was to com- ing one by one the best individual cells pose. The system is divided into small bine CFD modelling and multi-block neighbouring the zone. Cells are evalu- cells, which are modelled with various modelling. The key idea was to calcu- ated by regarding the discrepancies in sub models, depending on the system. late various variables from CFD with chosen fluid flow parameters. The algo- rithm produces zones that are homoge- nous in relation to the chosen flow field parameters but irregular in shape. The Figure 1. The differences between ideally mixed model, multi-block model and CFD. second algorithm is a novel threshold method which builds zones layer by layer while monitoring pre-determined threshold values for flow field and top- ological parameters. Generated zones are regular in shape resembling manu- ally created zones but at the cost of ho- mogeneity. Functioning of the two al- gorithms is demonstrated with a flota- tion test case. The research groups at TKK fo- cused on the model development and validation of the CFD models. Mechan- ical Process and Recycling Technology research group focused on experimen- tal and theoretical study of bubble-par-66
    • ticle interactions and implementation flotation, and a method for setting feasi- the project a Particle Image Velocime-in the open source CFD package Open- ble tolerance values was presented. All try – equipment was set up and also di-Foam. Chemical Engineering research zonings created with the developed al- rect imaging was made. Besides numer-group focused on the model develop- gorithms were demonstrated to be ca- ical data also the method gives a visu-ment of gas-liquid systems and non- pable of predicting reasonable bubble al output, which can be analyzed qual-Newtonian fluids. The models were im- Sauter mean diameters and air hold- itatively.plemented into the multi-block mod- up values by comparing the results to Single phase CFD-modelling hasel and commercial CFD program CFX. available experimental data. The differ- been extensively validated for Newto-Both research groups also performed ent simulations were also able to ade- nian fluids at the turbulent and laminarexperimental work to validate the mod- quately capture the characteristics of flow regimes. However, there are manyels. Also a novel system called Particle a flotation cell, such as the jet of small difficulties when modelling turbulenceImage Velocimetry (PIV) was set up dur- bubbles streaming through the rotor at the transitional turbulent regime.ing the project. towards the walls and the vortices form- Unfortunately transient modelling is ing in the cell. Therefore, the automat- essential when dealing with systemsConclusions ic zoning algorithms offer a feasible op- where the local conditions vary signifi-Single phase CFD results were com- tion for manual zoning. They also pro- cantly (bioreactors etc.). Models need tobined with a multi-block model using a vide a fast visualization tool for multi- be also validated in wider range vesselbubble number density approach with block model results. However, some au- geometries and operating conditionsa constant bubble size and two phase tomatically created zones affected the to be reliable in scale-up.flow field was combined with both convergence of the multi-block mod- Multiphase experiments and mod-bubble number density approach and el. Thus, the automated zoning proc- elling resulted that the investigated sys-population balance approach with 20 ess still requires an experienced user to tems were very heterogeneous (e.g.bubble size distribution classes (see ex- choose suitable zoning parameters. 50% of mass transfer occurred at 10%ample, figure 2). Dissipation rate of tur- In experimental work the focus reactor volume), which basically meansbulent energy and pressure were cho- was to develop optical methods to val- that ideal assumption is far off from realsen as suitable zoning parameters for idate the data from modelling. During life. The problem with multiphase mod-Figure 2. Gas hold-ups (%, left) and Sauter mean diameters (mm, right) in the flotation cell in casesCBC-BSD (62 blocks) and LBL-BSD (62 blocks) with 20 size classes. 67
    • elling was same as in transient flows, we economical. The automatic combina- model development was supervised by were able to get the right trends, but tion of CFD and multi-block modelling, Dr. Ž. Tuković and Prof. H. Jasak of FSB actual values divide from the simulat- developed in the project, has increased at the University of Zagreb, Croatia. The ed values. the usefulness of the model signifi- bubble model uses a dynamic mesh In order to better understand cantly. The multi-block model can be motion method, developed by Dr. Ž. the fundamental physical and physic- used for modelling industrial process- Tuković and Prof. H. Jasak, to track the chemical processes involved in mul- es involving bubble and particle pop- air-water interphase. The bubble-parti- tiphase flows experimental and the- ulations, reactions, and mass and heat cle interaction model developed dur- oretical investigation has been car- transfer. It is also useful and fast meth- ing the MASIT17 project uses addition- ried out and is ongoing at the research od in finding suitable model param- al particle-bubble collision, attachment, group of Mechanical Process and Recy- eters for more detailed and time con- sliding, and detachment algorithms in cling Technology. The focus of this ef- suming CFD models. turbulent liquid. Figure 3 shows a snap- fort is on formulation and measure- shot of the promising preliminary re- ment of higher order momentum cou- International cooperation sults of this model. The bubble-parti- pling in turbulent multiphase systems. During September 2009 the basis of a cle model can be used to better under- Pressure fluctuation and linear momen- bubble-particle interaction model in stand the fundamentals of turbulent tum transfer between phases has been the open source CFD package Open- three-phase systems and to test new measured for bubbles during collision FOAM has been developed at the NU- (sub)models. with mineral particles. This experiment MAP-FOAM Summer School 2009. The has given significant insight in the trans- fer mechanisms of (linear) momentum Figure 3. Preliminary results of the bubble-particle interaction model in OpenFOAM and quantification of the energy barri- (1.5 mm air bubble in water colliding with a 50 µm solid particle with a density of 4 g/cm3). er that needs to be overcome for bub- ble-particle attachment to occur. A ful- ly coupled CFD model has been devel- oped in OpenFOAM that can provide a suitable testing ground for new (sub) models of bubble-particle interaction models. Findings and model develop- ment on the micro-scale and, in partic- ular, the meso-scale can contribute to more accurate predictions of industrial processes. Multi-block CFD modelling of industrial processes is still in a devel- oping stage, however, results are prom- ising and development toward better, validated industrial modelling will con- tinue. Impacts The multi-block model is a computa- tionally inexpensive approach for simu- lating complicated processes and there- fore especially suitable for developing industrial processes more efficient and68
    • Dissemination Alopaeus, V., Laakkonen, M. & Aittamaa, J. Visuri, O., Laakkonen, M. & Aittamaa, J.During the project, two Ph.D. theses 2006. Numerical solution of moment- 2007. A digital imaging technique forand one licentiate thesis were made. transformed population balance the analysis of local inhomogeneitiesTwo other Ph.D. theses will use some of equation with fixed quadrature points. from agitated vessels. Chemicalthe results gained in the project. Chemical Engineering Science, 61, 15, Engineering and Technology, 30, 12, p. 4919–4929. 1692–1699.Publications Alopaeus, V., Laakkonen, M. & Aittamaa, J.Summary of essential publications 2006. Solution of population balances Project time scale with breakage and agglomeration 1.8.2006–31.12.2009Thesis by high-order moment-conservingLaakkonen, M. 2006. Ph.D. Thesis. method of classes. Chemical Project volume Development and Validation of Mass Engineering Science, 61, 20, p. 6732– Total 1 146 415 €, Tekes share 982 000 € Transfer Models for the Design of 6752. agitated Gas-Liquid Reactors. Chemical Laakkonen, M., Moilanen, P., Alopaeus, V., Project participants Engineering Report Series, No.51. Aittamaa J. 2007. Modeling local gas- • Helsinki University of Technology,Moilanen, P. 2009. Ph.D. Thesis. Modeling liquid mass transfer in agitated vessels. Faculty of Chemical and Material Gas-Liquid Flow and Local Mass Chemical Engineering Research and Sciences, Department of Biotechnology Transfer in Stirred Tanks. Chemical Design, 85, p. 665–675. and Chemical Technology Engineering Report Series, No.53. Laakkonen, M., Moilanen, P., Alopaeus, V. • Helsinki University of Technology,Seppälä. M. 2008. Licentiate Thesis. & Aittamaa, J. 2007. Modeling local Faculty of Chemical and Material Automatic zoning for combined CFD bubble size distributions in agitated Sciences, Department of Material and multiblock modeling. vessels. Chemical Engineering Science, Sciences 62, 3, p. 721–740. • VTT Technical Research Centre ofReferred publications Moilanen, P., Laakkonen, M., Alopaeus, FinlandAlopaeus, V., Laakkonen, M. & Aittamaa, J. V. & Aittamaa, J. 2008. Mass Transfer • Outotec Oyj 2007. Solution of population balances in an Aerated 0.2 m3 Vessel Agitated • Neste Oil Oyj with growth and nucleation by high by Rushton, Phasejet and Combijet • Roal Oy order moment-conserving method of Impellers. Chemical Engineering • Rintekno Oy classes. Chemical Engineering Science, Journal, 142, 1, p. 95–108. • Galilaeus Oy 62, 8, p. 2277–2289. Moilanen, P., Laakkonen, M., Visuri, O. &Alopaeus, V., Laakkonen, M. & Aittamaa, J. Aittamaa, J. 2007. Modeling local gas- Contact information 2008. Solution of population balances liquid mass transfer in agitated viscous Ville Alopaeus by high order moment-conserving shear-thinning dispersions with CFD Helsinki University of Technology method of classes: reconstruction of Industrial & Engineering Chemistry +358 9 451 2630 a non-negative density distribution. Research 46, 22, p. 7289–7299. ville.alopaeus@tkk.fi Chemical Engineering Science, 63, 10, Moilanen, P., Laakkonen, M. & Aittamaa, J. http://chemat.tkk.fi p. 2741–2751. 2006. Modeling Aerated FermentersAlopaeus, V., Moilanen, P. & Laakkonen, with Computational Fluid Dynamics. Additional information M. 2009. Analysis of stirred tanks with Industrial & Engineering Chemistry The results of the project will be used in two-zone models. AIChE Journal 55, p. Research, 45, 25, p. 8656–8663. coming EFFMIND-project. 2545–2552. 69
    • Utilisation of simulation in industrial design and resulting business opportunities (SISU) – MASIT18 Background Figure 1. Matrix form of SISU project. Simulation with all types of applications is considered an important know-how in future societies, also in small and medi- um-sized enterprises (SME). Use of simu- lation in industrial design and resulting various business opportunities is essen- tial part of business in the future. Objectives SISU project aimed enhancing utilisa- tion simulation in industry, particular- ly in small and medium-sized enterpris- es. The objective was to develop new Conclusions Every phase contains questions: ways that enable quicker, cheaper and Actors and their roles in simulation Why? How? Where? How it works? more reliable modelling and simula- business were identified and strengths, The actors and their roles and sim- tion, in order to achieve a better inte- weaknesses, opportunities and threads ulation phases of Q9 can be combined gration of industrial design, simulation (SWOT) were analysed for each actor. that is illustrated in Figure 2. and testing of models. The goals of the Typical pitfalls of modelling and simula- A general observation is that suc- project were: tion were collected from literature and cess stories are based on three el- • New simulation and design combined with SWOT analysis results. ements: visions, know how and re- methods especially for small and These results have been published in sources. During the execution of SISU medium-sized enterprises project reports. (Olin 2007, Leppävuori all these elements have been prelimi- • Detailed plan for taking these 2009) nary investigated aided by Q9. First, it new methods into active use in Q9 operations model was created. was observed that present know how industry The purpose of Q9 is to guide execut- in simulation was sufficient for at least • Assessment of the new ing simulation projects, to avoid pit- SME purposes. Second, SME compa- developed business opportunities falls and help and enhance commu- nies are not ready for paying simulation (economy, technological) nication and understanding between work themselves without public sup- • Creation of potential and different actors in simulation project. port even though resources are avail- opportunities for new simulation- The Q9 operations model is divided able in Finland. We believe that suc- based business into nine phases: cess stories and shown benefits of sim- 1. Desired impact ulation for SMEs would increase the in- Project implementation 2. Problems encountered terest. According our experience oper- SISU was constructed in matrix form. 3. Solution proposed ations models like Q9 are an essential Specific case studies were small simu- 4. Conceptual model part in creating these success stories. lation applications done between re- 5. Data needed search partner and a company. Gen- 6. Model construction Scientific or technical progress eral knowledge from case studies was 7. Application of the model Eleven case studies were carried out in collected and compiled into Q9 oper- 8. Presentation of results the areas of product simulation, proc- ations model. 9. Maintenance of the model ess simulation and logistics simulation.70
    • Figure 2. Phases (left) of Q9 operations model and actors andtheir roles (right) in simulation business.The results contain a number of simu- • Process simulation helping the business. By using Q9, companies canlation-based applications for industry small-scale biodiesel plant design use it to help buying simulation servic-and few beta-level products that might • Simulating liquid penetration es from companies or research organ-have market potential. The topics of the into paper structure by isations. Service providers may use itcase studies were the following: supercomputer application. when constructing their business plan• General interface into CAD • Simulation flow rates and particle and designing their own ways to serve software to ease parametric emissions in a peat power plant their customers. Project managers may design • Simulation methods for use it in managing projects and com-• Virtual prototype of novel trailer simulating and visualisation of municating with modellers and setting• Use of modelling and simulation logistical solution offered for targets for modelling. in very early phase of product customers Nine case studies were done most- design ly by students in Metropolia. The result• Design geometry of electric Impacts is a number simulation trained engi- precipitator SISU project has impacts in many levels. neers graduated on employee market.• Integration of simulation, CAD Some of simulation applications are in and experimental methods in use in industry, which itself is a proof of Dissemination biogas reactor design benefit. Some of solutions have poten- Project material has been collect-• Measurement data reconciliation tial for commercialisation or to be used ed onto public wiki-pages (https:// tool for power plants in simulation service business. wiki.metropolia.fi/display/sisu/Home).• Combined process simulation and General work has produced a Project progress reports have been PI-diagram construction foundation for establishing simulation published in VTT’s and Metropolia’s se- 71
    • ries. Reports are available online. Also, a Olin, M., Lahti, S., Valli, A., Hasari, Project participants number of participated persons for this H., Koistinen, A. & Leppänen, • VTT Technical Research Centre of project will know how to apply the de- S. 2007b. SISU. Simuloinnin ja Finland veloped Q9 operations model in the fu- suunnittelun uudet sovellustavat ja • Metropolia University of Applied ture and help disseminate the results. liiketoiminta. Projektin tavoitteet ja Sciences simulointiesimerkkien yhteenveto. • Etteplan Oyj Publications Espoo, VTT. 58 p. VTT Tiedotteita – • Sweco Industry Oy Summary of essential publications Research Notes; 2405. • Oy Sandman-Nupnau Ab Lahti, S. & Suvilampi, J. 2008. Integration Olin, M., Leppävuori, J., Keränen, J., Lahti, • Kardex Finland Oy of Simulation, Cad- and Experimental S., Valli, A., Koistinen, A., Hasari, H., • Watrec Oy Tools in Biogasreactor Design. ICERT (8) Leppänen, S. & Ropanen, T. 2010. • Pöyry Forest Industry Oy Conf. Penang, Malaysia. Anyone can simulate? Q9 Operations • Rintekno Oy Lahti, S., Häppölä, M., Repo, P. & Mäkinen, Model for Enhancing the Utilisation of • Genano Oy S. 2008. Data Reconciliation in Power Simulation in Industrial Design. Espoo, • Fortum Power and Heat Oy /Generation Plant Environment.ICERT (8) Conf. VTT. VTT Tiedotteita – Research Notes. • Fortum Power and Heat Oy /Service Penang, Malaysia. Olin, M., Valli, A., Hasari, H., Koistinen, • Oy Metsä-Botnia Ab Leppävuori, J., Olin, M. & Valli, A. et al. 2009. A. & Lahti, S. 2007c. Suunniteltu SISU – Simuloinnin ja suunnittelun Suomessa vai Intiassa! Auttaako Contact information uudet sovellustavat ja liiketoiminta. SISU? MASI Mallinnus ja simulointi Juha Leppävuori Hyödyn elementit ja käyttöönoton tutkimusohjelman vuosiseminaari. VTT Technical Research Centre of Finland prosessit: SISUQ8, Metropolia Tampere, 15.–16.5.2007. Tampere. 31 s. +358 20 722 2726 ammattikorkeakoulu. 65 p. Metropolia juha.leppavuori@vtt.fi Ammattikorkeakoulun julkaisuja, Sarja Project time scale D; Työpaperit 1. 1.4.2006–30.10.2009 Markus Olin Olin, M., Laakso, L., Hannula, J., Galkin, VTT Technical Research Centre of Finland T. & Väkeväinen, K. 2006a. Model Project volume +358 20 722 5450 calculations about deposition of Total 955 900 €, Tekes share 546 992 € markus.olin@vtt.fi aerosol particles in electronic devices. https://wiki.metropolia.fi/display/sisu/Home In: Gregersen, L. (ed.) Proceedings of the Nordic Comsol Conference 2006 Copenhagen. p. 117–122.72
    • Multi-scale flow modelling (MUSCA) – MASIT19Background Project implementation ance equations. Alignment of the fi-Macroscopic flow properties of com- Research was accomplished in a close bres in a flow field was modelled byplex fluids are often dependent on in- collaboration between University of the fibre orientation probability distri-teractions that occur at microscopic Kuopio (UKU), University of Jyväsky- bution (FOPD) model. The FOPD mod-scales. The presence of gas bubbles, sol- lä (JYU), Lappeenranta University of el is based on a probability of fibres toid particles or other liquids chance the Technology (LUT), University of Oulu be oriented in a certain angle. Both theproperties of mixtures by effecting, e.g., (OU), Tampere University of Technolo- FFE and FOPD model were implement-turbulence of the carrier liquid. Numer- gy (TUT), VTT Technical Research Cen- ed in commercial CFD software. Also,ical modelling of such flow phenome- tre of Finland, and Numerola Oy. The the models were validated with exper-na is difficult, since the interactions be- research included two interconnect- imental data provided by TUT (orienta-tween phases are not generally known ed parts, modelling and experimental tion data) and VTT (flocculation data);and model validation lacks proper ex- research. Modelling focused on multi- see Figure 1.perimental data. The length scales in phase flow models in microscopic and The fibre orientation measure-industrial unit processes, on the oth- macroscopic scales. The experimental ments at TUT have produced new in-er hand, are frequently three orders of part provided physical background in- formation on the kinetics of flow in-magnitude larger than that of the par- formation and validation data for the duced fibre orientation. Several fibreticles. Thus it is obvious that the model- developed models. types were studied in varying flow con-ling of these processes can not be done ditions. The results indicate the essen-at the particle level, and there is need Results tial role of fibre mechanical proper-for macroscopic models that describe, The work done at TUT focused on de- ties in the fibre–flow interaction. Floc-e.g., the motion of air bubbles in a mix- veloping experimental techniques for culation measurements have providedture without modelling motions of indi- multi-phase flows and producing nov- detailed information on the dynamicsvidual bubbles. el measurement data for the research of fibre flocculation in controlled flow partners, thereby supporting their mod- conditions.Objectives el development and validation. Imag- A primary goal for VTT, NumerolaThe aim was to develop reliable phe- ing-based measurements were devel- and JYU was to create validated semi-nomenological models for complex in- oped to detect and track individual dis- empirical models for mixing and filtra-dustrial and biological fluids by mul- persed phase elements in the flow and tion of fibre suspensions. For this pur-ti-scale modelling and detailed exper- study their interaction with the contin- pose, a new 2D filtration device wasimental validation. On a microscop- uous phase. The work focused on fibre developed at VTT. At JYU, a model ofic level, detailed models were used to suspension flows and bubbly flows. the consolidating fibre suspension hasstudy e.g. flexible fibrous particles, de- Research at UKU concentrated on been constructed using a covariant for-formable bubbles and orientation of modelling of fibre floc evolution and mulation of the theory of large defor-non-spherical particles in the flow. The fibre orientation. The developed fibre mations together with general elasto-results from microscopic modelling floc evolution (FFE) model is based on viscoplastic rheology behaviour for fi-and from experiments were combined an Eulerian two-phase flow model such bres. Based on the filtration model, sim-to macroscopic and phenomenolog- that water is the carrying phase and ulators were developed at Numerolaical models applicable in the analysis, flocs are the dispersed phase. Further- for one and two dimensional flow ge-design and optimization of selected in- more, the size distribution of the flocs ometries. Parameter identification al-dustrial and biological processes. was modelled by using population bal- gorithm was implemented to identify 73
    • Figure 1. Left: A transillumination image through a headbox contraction. Right: An example of measured and modelled fibre orientation probability distributions at three different positions in the flow direction. Figure 2. Left: The 3D ultrasound probe with one emitter at the centre and three receivers. Middle: The tank used for mixing experiments; T=H=0.59 m. Right: Measured velocity field for a 2% fibre suspension on six angular positions between two baffles. the material parameters of the filtration Experimental results obtained for a tral region of the vessel. Comparison model from experimental data. solid-liquid (both sand and pulp) stirred with full Eulerian model showed poor- New method was developed at tank have been used to validate alge- er agreement. The concentration pro- VTT for measuring 3D velocity fields braic multiphase models at VTT. The ve- file was also qualitatively correctly pre- in opaque suspensions. The measure- locity field of sand suspension comput- dicted with the ASM model. Closer to ments are based on pulsed ultrasound ed with the algebraic slip mixture (ASM) the tank wall, more deviation was ob- Doppler velocimeter (PUDV) equipped model showed generally good agree- served between measured and simulat- with a submersible probe, see Figure 2. ment with measurements in the cen- ed results. Figure 3 shows an example of74
    • Figure 3. Measured and simulated axial (on the left) and radial (on the right) velocity profiles along the vertical line r = 0.105 m for 5%sand suspension in a stirred tank.model validation at 5% solid concentra- water in, e.g., paper making process. At paper machine circulation water in ation. Similar results were obtained with LUT, gas removal was studied both ex- gas separation channel. The developed1% and 10% concentrations. perimentally and by CFD simulations. A CFD models take into account the in- The main focus at LUT and at OU CFD model was developed for the sim- teraction of bubbles, fibres and solids.was at the removal of gas entrained in ulation of entrained air separation from The changes in bubble size distributionFigure 4. Left: Laboratory gas separation channel. Right: Comparison of simulated (CFD) and measured (PIV) vertical gas velocityprofiles in one horizontal position. 75
    • are described by population balanc- lies heavily on processes based on mul- der to validate them against measured es. Bubble coalescence was modelled tiphase flows and understanding of data, to define ranges of validity, and to considering turbulence, presence of fi- their physics. convert the models into practical tools bres and solids and the effect of degas- The results of studies on removal of for design process. sing chemicals. The size distribution of entrained air have so far aided in devel- the dispersed bubbles was measured opment of new measurement technol- International cooperation and with submerged photographical meth- ogies and provide new information on dissemination ods that have been developed at TUT. deaeration efficiency, phenomena and International cooperation has been Flow fields of the liquid and gas bub- limitations. New tested and validated mostly carried out through ERCOFTAC bles were studied by Particle Image Ve- measurement methods and CFD mod- Special Interest Group on Fibre suspen- locimetry (PIV). The measured and sim- els will be usable in a variety of multi- sion flows (SIG43) managed by Prof. ulated velocity profiles in the gas sep- phase environments and applications, Jari Hämäläinen. The group was found- aration channel were found to be in e.g., in searching for optimal flow con- ed during the MUSCA project. The first good agreement, see Figure 4. ditions and optimal feed of degassing workshop was organized in 2009 in Fin- At OU, experimental studies took chemicals. land and the second one in 2010 in Swe- place in depressurizing bubble column According to the representatives den. The paper physics group at the Uni- with optical imaging in collaboration of Metso Paper Oy, the experimental versity of Kuopio organized also an inter- with TUT, revealing the microbubble and modelling results obtained in this national conference called Papermaking dynamics and drag effects of industri- project will increase the accuracy in Research Symposium – PRS2009 in June al suspensions on bubble rise. Channel studying, designing and optimizing rel- 2009 in Kuopio, participated by more flow efficiency analyses were made in evant processes, and they will enable than 100 contributors from 13 countries. pilot scale environment by microwave further development work on the proc- Results have been disseminated analysers and submerged imaging. Ad- esses. This project has supplemented with international publications (see be- ditional, flow field analysis from deaer- company’s ongoing R&D work regard- low), with one Ph.D. thesis, and with one ation channel were also measured us- ing, e.g., flow phenomena in headbox international Master’s thesis. In addition, ing 3D-PUDV apparatus with VTT. In ad- and their affect on fibre orientation and results have been presented in 17 inter- dition, the research included modelling flocculation, as well as filtration in shear national conferences and seminars. of gas separation efficiency in channel field, and its effect on water removal. flow based on measurement data with Within the perspective of Sulzer Publications LUT, as well as studies of white water Pumps Finland Oy, the most important González, P. 2009. M.Sc. (tech) thesis. Solids frothing and solids sedimentation dur- achievement of the project was the pa- sedimentation in low consistency ing gas separation. rameter identification for some existing papermaking suspensions. University viscosity correlations by using exper- of Oulu, p. 150. Impacts imental data. Due to a small number Haapala, A., Honkanen, M., Liimatainen, The experimental methods and results of CFD simulations and validation tests H., Stoor, T. & Niinimäki, J. 2010. created in this project provide new compared to the large number of stud- Hydrodynamic Drag and Rise Velocity means for various modelling purposes. ied models including many uncertain- of Microbubbles in Papermaking Besides conventional time-mean sta- ties, the validity of the models could Process Waters, Experiments in Fluids. tistics of the flow, instantaneous cou- not been linked in such a way that (Submitted 9/2009) pling between the phases and relat- they would be of practical importance Haapala, A., Liimatainen, H., Karinkanta, P., ed terms can be assessed. In addition, as part of design process. Next steps Stoor, T. & Niinimäki, J. 2010. Bubbly these methods yield results readily ap- would be to select one or two of the gas content reduction in open channel plicable to the Finnish industry that re- models, to make extensive work in or- flow. Tappi Journal. (Submitted 2/2010)76
    • Haapala, A., Stoor, T., Liimatainen, H., Nelo, Project time scale Contact information M. & Niinimäki, J. 2009. Passive white 1.8.2006–30.4.2010 Jari Hämäläinen water deaeration efficiency in open University of Eastern Finland channel flow. Appita Journal. 62(2), p. Project volume Tel. +358 40 5961999 105–109. Total 1 511 160 €, Tekes share 1 146 000 € jari.hamalainen@uef.fiHaavisto, S., Koponen, A., Syrjänen, http://www.uef.fi/fysmat/jari-hamalainen J. & Manninen, M. 2009. UDV Project participants measurements and CFD simulation • University of Kuopio (University of to two-phase flow in a stirred vessel. Eastern Finland since January 2010) Progress in Computational Fluid • University of Jyväskylä Dynamics Vol.9 Nr.6–7, 375–382. • Lappeenranta University of TechnologyHämäläinen, T. 2008. Modelling of Fibre • University of Oulu Orientation and Fibre Flocculation • Tampere University of Technology Phenomena in Paper Sheet Forming. • VTT Technical Research Centre of Ph.D. thesis. Tampere University of Finland Technology, Tampere, Finland. • Numerola Oy (in VTT’s subproject)Hämäläinen, T. & Hämäläinen, J. 2007. • Steering group and funding: Kemira Oyj, Modelling of fibre orientation in the Metso Paper Oy, Sulzer Pumps Finland headbox jet. Journal of Pulp and Paper Oy, Tamfelt Oyj Abp Science, Vol. 33(1), p. 49–53.Hyensjö, M., Dahlkild, A., Krochak, P., Olson, J. & Hämäläinen, J. 2007. Modelling the Effect of Shear Flow on Fibre Orientation Anisotropy in a Planar Contraction. Nordic Pulp and Paper Research Journal, vol. 22(3), p. 376– 382. 77
    • Nonlinear temporal and spatial forecasting: modelling and uncertainty analysis (NoTeS) – MASIT20 Background probability density functions (pdf ) analyzing and producing predictions It is common to industrial production of the predictions and about their about stochastic and dynamic multi- processes, economic systems, and mul- development over the forecasting variate systems can be categorized in- ti-imaging that they have complex de- horizon. Such uncertainty informa- to those providing static background pendence structures, internal sto- tion is necessary when the forecasts information when analysis/prediction chastic mechanisms, and that the da- are fused with other data in decision system is initialized – system identifi- ta obtained from these systems is un- making. cation, model validation and posterior certain and incomplete. In all the cas- 2. To implement this methodology in analysis – to those that use fresh data es the goal of analyzing the data is to a form that can be readily used in for providing dynamic background in- support decision making – either by practical data analysis either au- formation while the analysis/prediction humans or in automatically optimized tonomously or as packages easy to system is operated – model updating form – through inferring the depend- integrate into present systems of – and those that are directly interpret- ence structures as non-linear models the companies partly financing the ing the fresh data – filtering/estimation, and then to use the models in forecast- project. forecasting and detection/recognition. ing (temporal structures), in object en- 3. To demonstrate the applicability of NoTeS project developed a com- hancement (spatial structures) or in ob- the methodology at least in three mon modelling and forecasting frame- ject forecasting (spatio-temporal struc- widely differing application areas: in work for a number of widely different tures). The spatial (imaging), temporal analysis of industrial process of pa- applications. In system identification (system dynamic) and spatio-temporal permaking and nuclear energy pro- the method was a combination of var- (system dynamic of functionally relat- duction (temporal and spatio-tem- iable selection methods, maximum a ed observations) modelling are strong- poral analysis), in analysis of energy posteriori (MAP) parameter identifi- ly linked in that the mathematical the- markets (temporal analysis) and in cation, and time warping in some ap- ory of non-linear time series analysis to analysis of medical multimodal- plications. In variable selection a new large extent carries over to non-linear ity imaging of healthy and disease methodology called Optimally-Pruned spatial series and spatio-temporal anal- state Imaging analysis). Altogether Extreme Learning Machine (OP-ELM), ysis simply be changing the dimension- project addresses five application based on the original ELM introduced ality of the support set from 1 to 2. cases, three of which are in the area in 2004. The OP-ELM methodology is of industrial processes. accurate: comparing to well-known Objectives methodologies the OP-ELM achieves 1. To integrate the pre-existing method- Methodological development roughly the same level of accuracy. The ologies of the partners (SOM, time- The main concept for prediction is ex- main advantage of OP-ELM is that the series analysis, functional time series tended Kalman filtering. Mathematical computational time is orders of magni- analysis, distribution dynamics, da- description for prediction system can tude less that with traditional methods. ta-assimilation, and Kalman filtering) be written in terms of state variables, The Self-Organizing Map (SOM) into a coherent approach to nonlin- measurements and parameters. The key is an important modelling option for ear modelling, analysis and forecast- models for the system are the state evo- multivariate and nonlinear stochastic ing/filtering for dynamic/spatial/ lution, measurement and parameter ev- systems. In NoTeS dynamical behaviour spatio-temporal systems with inher- olution models, and the related proba- was visualized as trajectories which link ent stochasticity and measurement bility densities for stochastic effects on together the adjacent winner neurons uncertainty. Forecasting provides state, measurement data and parame- (Best Matching Units, BMU) in the SOM information about the uncertainty/ ters. The main tasks when modelling, grid. The SOM trajectories have such78
    • features as linked BMUs, where each ror is largely decreasing the costs and variable. Thus, the abnormal state of theBMU represents a certain instant of then the use of environmental resourc- system could be predicted by featurestime. In industrial applications the op- es. The accuracy of the mid-term pre- detected in certain signals that tend toerator is able learn to adjust the con- diction has not been satisfactory. One be accompanied by a simultaneous (ortrol variables according to the visual of the reasons is the difficulty to take in- delayed by a few time points) shift inimpression so that the process stays in to account the uncertainty of the exter- the estimation error of the statisticallydesired regions of the map. nal variables (for example, the weather). constructed normal state model. Varia- State estimate filtering was ob- Thus the mid-term forecasting (several bles causing such deviations in the sys-tained mainly as the filtering step of weeks ahead) based on hourly values tem state can be identified by observ-(extended) Kalman filter. Forecasting was chosen as the focus. ing the signal levels of the candidatewas obtained as the prediction step of Tools for the selection of the best variables during the transitions be-(extended) Kalman filter. Detection and variables for the mid-term prediction tween abnormal and normal state us-recognition were application specific. have been developed. Variables are se- ing a reasonable time lag window. Sim-However, signal feature detection de- lected from the past values of the time ilarity measures were constructed andveloped is generalizable. Industrial pro- series to be predicted itself and from data analyzed accordingly.duction processes are often non-sta- exogenous variables such as temper-tionary by their nature; changes in un- atures. The problem of the computa- Estimation and prediction for control in web productionmeasured/unknown factors (or varia- tional time needed for the predictionbles) may cause values and dependen- has been also investigated. Feed-for- The paper machine quality scannerscies of individual variables to gradual- ward neural networks are often found move regularly over the web at speedsly change over time. Furthermore, the to be rather slow to train, especially on up to 0.5 m/s. Therefore on a 10 m wideconditions in the system may change important datasets related to the data paper machine with web speed of 30in so large extent that the normal state mining problems of the industry. A new m/s, the web travels 600 m in machinemodel of the production process be- algorithm for the determination of the direction during one scan. The mostcomes deficient. Abnormal periods can weights of the hidden neurons called common way of estimating the 2d var-be identified in industrial data, and po- Extreme Learning Machine (ELM) has iations has been a) CD variation is thetential features causing these chang- been introduced in 2004. This algorithm vector average over 4–10 scans and b)es analyzed. However, selection of fea- decreases the computational time re- MD variation is the scalar average oftures is largely application specific. Fur- quired for training and model structure one scan. This is known to have manythermore, while dependencies may be selection of the network by hundreds. shortcomings. Furthermore, the meas-observed between individual variables, urement scan path could be used as athere may be more complicated inter- Analysis of a large industrial degree of freedom in control. Hence, data set, a pulp mill casedependencies involving several inputs. estimation and prediction methods are The original aim in this application required for irregular scan paths. TwoResults in applications was to use both model-based and da- approaches for the estimation were de- ta-based time warping and apply stat- veloped, both forms of (extended) Ka-Time series estimation of electricity ic non-linear regression models for un- lman filtering/data assimilation.grid loading derstanding origins of process distur- In the first method a process mod-Prediction of electric load or consump- bances, but due the data problems it el and disturbance models were de-tion is becoming more and more im- was decided that signal features should fined and the Kalman filter construct-portant due to the liberalization of be extracted and their relationships an- ed accordingly and in the data assim-the energy market in Europe. Howev- alyzed. The hypothesis was that unex- ilation approach, the 2d variation waser, the behaviour of electric time series pected variations in the response signal modelled as a truncated Fourier seriesis quite nonlinear. Furthermore, even are caused by a feature detected in sig- in space and ARMA process in time. Ita small decrease of the prediction er- nal level of one (or several) explanatory was noted that the scanner path is an 79
    • important degree of freedom for esti- self-organizing map (SOM) was used in A Robust segmentation method for mation and control. Methods to choose data analysis for resolving and visual- premature infant brain MRI the path optimally were developed. izing nonlinear relationships in a com- Magnetic Resonance Imaging (MRI) is plex process. An application of the SOM a non-invasive medical imaging meth- Decision support at a nuclear power for depicting state and progress of a re- od for analyzing human anatomy. The station al time process was studied. The self-or- scanning device is cylinder shaped Early fault detection includes both iden- ganizing map is used as a visual regres- and it produces 3D images consist- tification and separation of failures. The sion model for estimating the state con- ing of multiple 2D-slices. Different tis- following tasks were studied: process figuration and progress of an observa- sue types in human body have differ- and progress visualization, failure detec- tion in process data. The main tool was ent intensity values in MR images by tion and separation, leakage detection process state trajectory in the compo- which they can be recognized. In hu- with adaptive modelling, feature selec- nent plane. The failure detection is based man brain MR imaging, the images are tion on process fault detection, and de- on prototype system DERSI, whose user often segmented into four main re- tecting pre-stage of process fault. The interface is presented in Figure 1. gions of Gray Matter (GM), White Mat- Figure 1. DERSI user interface. Frame 1 shows the rule-based diagnostics result. Frame 2 shows the process trajectory in U-matrix representation of SOM. Frame 3 allows user input and guiding the analysis. Frame 4 gives process data. The frames 5 and 7 give SOM mappings for selected variables for failure data and normal data. Clear differences can be noted in the normal operation SOM maps (frame 7) and failure SOM maps (frame 5). In the frames 6 and 8 the component plane quantization errors as bars of varying height and colour are seen.80
    • Figure 2. Segmentation of the CSF region of two sample images. From left to right: is the key when applying the results inT1-weighted image, manual segmentation, HMRF and WSEG. The GM+WM region is practical decision making through for-labelled as white and the CSF region is labelled as gray. mal statistical decision making theory. The impact of the results obtained is two-fold. Firstly, the development of the generic methodology (implement- ed as an alpha version toolset) opens up wide possibilities for industrial advanced spatio-temporal forecasting applications on long term, and secondly, each of the test cases has direct short-term industrial relevance and these results can be inte- grated into products of the funding part- ners. Obviously, successful case stud- ies are also important in building con- fidence towards the usefulness of the advanced spatio-temporal forecasting methods, and therefore test cases sup- port the uptake of the generic toolset. Test case 1 has provided forecast- ing methods for the difficult medium- term optimization energy productionter (WM), Cerebrospinal Fluid (CSF), and corrections, and finally clusters the the under non-stationary conditions. Suchother head tissue containing fat, bone, GM, WM, CSF segments with a Gaussian methods have tremendous value foretc. While there are several segmenta- Mixture Model (GMM). the energy producer and opens uption methods available for adult brain strong business opportunities for com-images, there was a clear need for de- Impact of the results panies providing software based onsigning a robust technique for automat- The research problem addressed in these models. Within the funding con-ic volume measurement of small chil- NoTeS is highly relevant for MASI pro- sortium of the project Process Visiondren brain. MRI images have previous- gramme in the sense that non-linearity operates in this business.ly been automatically segmented with and non-stationary and incomplete in- Test case 2 has provided diagnos-techniques that utilize a priori informa- formation are common characteristics tic tools for dynamic process and qual-tion collected from manual brain im- in most of the data available from in- ity variations, in particular for pulp pro-age segmentations performed by ex- dustrial and economic systems. NoTeS duction. As pulp is produced in largeperts. In the NoTeS the images are seg- project is focused on adding value to quantities and as Finland is an impor-mented in a data-driven way with the data by using advanced modelling tant player in the pulp making busi-coarse-level watershed segmentation techniques. Although linear methods ness, the reduction of quality variationsas a priori for Gaussian-Mixture-Model and many existing nonlinear methods has both commercial and national val-segmentation. The NoTeS WSEG meth- provide useful information out of such ue. KCL provides pulp mills diagnosticod first corrects for biases, then extracts data, the results of NoTeS increase the services and is expected to be the firstthe brain region with adaptive 3D mesh amount of information achieved and, in exploiter of the methods. The methodsmethod, proceeds to determine the particular, increase the understanding develop can be applied in much wid-watershed segments, clusters the GM, of the validity/uncertainty of the results. er context of process and quality varia-WM, CSF segments with appropriate The accompanying uncertainty analysis tions in any process industries. 81
    • Test case 3 has opened up a Publications • University of Turku, Department of new control degree of freedom in pa- A total of approximately 30 conference Information Technology (UTU: multi- per quality control: the mode of sen- or magazine articles, as well as several imaging, segmentation) sor scanning. This has been shown to project reports, in addition to several ar- • Lappeenranta University of Technology; be an important tool in paper quality ticles were made in collaboration with Department of Mathematics (LUT: Kalman management and some of the results other projects. filtering and other estimation methods) are expected to be product features in • Tekes near future. Metso Automation, a fund- Project time scale • Oy Keskuslaboratorio – ing partner of the project, is expected 1.4.2006–31.12.2007 (NoTeS) Centrallaboratorium Ab (KCL) to be the main avenue for productiza- 1.1.2008–31.12.2008 (NoTeS2) • Metso Automation tion and commercialization of TC3 re- • Nordkalk sults. Project volume • Process Vision The results of test case 4 strongly Total funding 684 000 €, • Teollisuuden Voima (TVO) support process diagnostics at nuclear Tekes share 602 000 € (NoTeS) • Varsinais-Suomen sairaanhoitopiiri power plants. Furthermore, education Total funding 400 000 €, (VSSHP) was a non-funding partner of students both with various meth- Tekes share 360 000 € (NoTeS2) providing data for the project odologies and application knowledge is an important impact. These benefits Project participants Contact information can be readily achieved at Teollisuuden • Tampere University of Technology, Risto Ritala Voima, a funding partner of the project. Inst. of Measurement and Information Tampere University of Technology, Medical imaging is important from Technology (TUT: coordinator, Bayesian Automation Science and Engineering healthcare and business point of view. information dynamics, uncertainty and Tel. +358 40 8490 922 Image segmentation of premature in- measurements) risto.ritala@tut.fi fants has been a long standing image • Helsinki University of Technology, interpretation problem to which the Adaptive Informatics Research Centre NoTeS projects have provided an es- (HUT: nonlinear time series modeling, sentially improved solution. Hence, the variable selection, SOM) results of test case 5 have a high im- pact in healthcare and medical imag- ing business.82
    • Genuinely three-dimensional user interfaces in product design and animation (HandsOn)– MASIT21Goals tions and user testing follow each oth- Results and applicationsThe goal of the project was to develop er iteratively. Results of each user study To implement modelling and animationmethods and work processes for two- guide the development and further im- features by modifying existing off-the-handed interaction applied in the in- provement of prototypes. shelf tools we used Blender, a model-dustrial design and computer anima- For development of new concepts ling and animation software developedtion tasks. Instead of typical human- and metaphors for user interface de- as an open source project. For enablingcomputer interaction model based on sign, a method was developed that immersive stereoscopic rendering ona monitor, keyboard and mouse, the us- makes use of role-playing and body our two-walled lightweight CAVE virtu-ers are provided with means to perform storming to involve all participants in al reality display system, we used Chro-animation and modelling tasks in a the collaborative creation of design mium, a stream processing frameworkthree-dimensional virtual environment scenarios. Two scenarios were created: for distributing OpenGL graphics ren-(VE). In such an environment, created one describing the user experience for dering on several computers.with the aid of stereographic displays, a gesture-based user interface and the With Chromium and modifiedcamera based tracking and haptic force other detailing the workings of a tangi- Blender, basic polygonal geometryfeedback devices, the users are able to ble user interface system for 3D model- modelling tasks could be performedtouch, sketch, manipulate and trans- ling and animation.form objects directly with the move-ments and gestures of their hands. In the provided environment the Figure 1. Modelling in virtual environment.users will be able to create three-di-mensional objects gradually from ar-bitrary sketches to dimensionally ac-curate models. The users are also ableto build mechanic and kinematic ma-chinery, and investigate how they func-tion. The movement of objects can bedefined with different controls (as withmarionettes or puppetry), or hand byhand as a theatre director. A guiding principle was to devel-op a robust, fast, accurate, unobtrusive,stabile, and affordable two-handed in-teraction tool. Affordable here meansthat the system should be composed ofcheap off-the-shelf components, ideal-ly allowing anyone to build their ownsystem and use our software.MethodsResearch was carried out in a construc-tive manner: prototype implementa- 83
    • within VE. This enabled us to design a for immersive rendering. We first built Evaluating complex design (such test scenario for comparing the usabil- optical tracking relying on infra-red de- as cockpits) based on visual sense alone ity of our novel three-dimensional us- tecting cameras and retro-reflective 2D is demanding. A tactile feedback device er interface and original two-dimen- markers lighted by infra-red LEDs. The was developed, a haptic glove based on sional interface of the modelling appli- hand tracker was incrementally im- McKibben actuators, as shown in figure cation. Two-dimensional user interface proved by a client-server architecture 2. This device enables the user to feel was used with a mouse, a keyboard supporting multiple cameras, and by panels and switches in her fingers, and and a monitor; whereas a pointing de- Kalman filtering for providing more ac- it allows unlimited movement in VE. vice for detecting location in three-di- curate tracking results from noisy cam- Design work in mechanical engi- mensional space was used for control- era measurements. Different marker neering is mainly performed using 3D ling the modelling in VE, as illustrated patterns and retro-reflective materials CAD software. However, such mod- in figure 1. were examined. The latest version was els need some pre-processing before The user interface was then ex- based on coloured LEDs. Inertial track- they are ready for real-time visualiza- tended to support direct three-dimen- ing was also considered as an addition- tion in VE. In addition, importing CAD sional manipulation and gestural input al tracking enhancement, but not uti- models to VE framework is problemat- using both hands. Prototypes of biman- lized in this project. In addition to hand ic because no native CAD format is sup- ual tools were implemented for polyg- tracking, a new method for head track- ported in VE. Some well prepared con- onal modelling and kinematic charac- ing in virtual environments was devel- version paths were found for CAD pro- ter animation. oped. Location and orientation of the grams used by co-operation partners In a three-dimensional user inter- user’s head are detected from a shaped in this project. Problems related to CAD face we need to track user’s hand and marker pattern added to the frame of format conversion consist of loss of hi- finger movements, as well as the head the eye glasses. erarchy, variation between scales and coordinates, modifications of texture and material setups. Figure 2. Working with wearable haptic glove that enables sensing of virtual surfaces. With the objective of providing meaningful content and context for the testing of the system, an interactive showcase displaying a 3D model of the Finnish pavilion of the World Expo 1900 was developed and exhibited at the De- sign Museum in Helsinki. Publications Ellman, A. 2009. Designing Mobile Work Machines in Cyber Space. Keynote speech at the 7th International Conference on Machine Automation (ICMA2008). In Shirase and Aoyagi (eds.) Service Robotics and Mechatronics. Springer. Ellman, A., Laitinen, J. & Tiainen, T. Combination of Virtual and Physical Objects in User-centered Design of Mobile Work Machine Cabin.84
    • Proceedings of IMECE2007, 2007 ASME Takala, T. 2009. Optical Finger Tracking Project participants International Congress and Exposition. Using Color LEDs. M.Sc.Tech. Thesis. • Helsinki University of Technology, 11–15 November 2007, Seattle, Helsinki University of Technology. Telecommunication Software and Washington, USA, 6 p. Tiainen, T., Ellman, A., Kaapu, T. & Multimedia LaboratoryHarviainen, T. 2008. Virtual Reality Aided Roberts, D. Effect of Navigation Task • Tampere University of Technology, Design. M.Sc. Thesis. University of on Recalling Content: The Case of Institute of Machine Design Helsinki. (in Finnish) Occasional Users in Restricted, Cave- • University of Art and Design Helsinki,Harviainen, T., Svan, L. & Takala, T. Usability like Virtual Environment. In Alba, Media Laboratory Testing of Virtual Reality Aided Turner, Roberts and Taylor (eds.) • Bronto Skylift Oy Ab Design: Framework for Prototype Proc. 11th IEEE ACM International • Finnish Science Centre Foundation Development and a Test Scenario. 4th Symposium on Distributed Simulation (Heureka) INTUITION international conference and Real-Time Applications. 22.– • Generator Post and workshop on virtual reality and 23.10.2007, Chania, Greece, p. 209– • Metso Power Oy virtual environments. Athens, Greece, 216. • Sandvik Mining & Construction Oy 4–5 October 2007, p. 172–181. Tiainen, T., Katajamaki, T., Ellman, A. & • SenseTrixIltanen, M., Ellman, A. & Laitinen, J. Kaapu, T. 2006. Occasional Users’ Wearable haptic device for an IPT Experiences of Visiting a Virtual Contact information system based on pneumatic muscles. Environment. In E. Alba, S.J. Turner, Responsible leader Proc. 2007 ASME International Design D. Roberts and S.J.E. Taylor (eds.) Tapio Takala Engineering Technical Conferences Proceedings of Tenth IEEE / ACM Aalto University School of Science and IDECT/CIE. 4–7 September 2007, Las International Symposium on Technology Vegas, USA, 7 p. Distributed Simulation and Real- tapio.takala@tkk.fiKorkalo, O. & Takala, T. Monocular Time Applications. 2.–4.10.2006, head tracking for desktop virtual Torremolinos, Spain. IEEE Computer Project manager environments. 13th Eurographics Society, USA, ISBN 0-7695-2697-7, Tatu Harviainen Symposium on Virtual Environments. p. 63–69. Aalto University School of Science and Weimar, Germany, 15.-18.7.2007, p. Technology 53–58. Project time scale tatu.harviainen@tml.hut.fiKuusisto, J., Takala, T., Korkalo, O., Ellman, 1.5.2006–31.3.2009 http://www.tml.tkk.fi/Research/HandsOn/ A. & Takala, T. Wearable Haptic Glove index.html with McKibben Actuators and Optical Project volume Tracking for Virtual Environments. 762 700 €, Takes share 720 700 € Proc. 4th International INTUITION (in two phases) Conference Virtual Reality and Virtual Environments. Athens, Greece, 4–5 October 2007, 10 p. 85
    • Developing chemometrics with the tools of information sciences (CHESS) – MASIT23 Background namic modelling, 3) tools resulting for vironmental time series – but so far the The goal of this project was to merge solid multi-block modelling, and 4) ro- lack of modelling (analysis) tools has the modern computational tools of in- bust novel non-linear approaches. Re- prevented this. This is not due to lack formation science onto the applica- search partners responsible for the test of techniques as such, but merely a lack tion platform created by chemomet- problem: TKK/AIRC and LUT/CG togeth- of expertise of environmental officers in rics society. Having partners from both er with Neste Oil. applying new approaches developed in fields, the created synergy allows new Test case 2: Food production: information sciences. Research partner approaches to emerge. Great practical Danisco is interested in creating moni- responsible for the test problem: UT/ application possibilities lie in the field tors that display the current state of the ARI, TKK/AIRC and UH/LAC. of environmental monitoring, which process warning the user of potential ties together the chemical environ- hazards, as well as predictors that allow Methodological development and mental data producers (manufacturers future process conditions to be estimat- results in applications of the analyzers) and the governmen- ed. Research partner responsible for the Test case 1: Oil production tal institutes (the environmental offic- test problem: TKK/AIRC and Danisco. ers) responsible of environmental mon- Test case 3: Process manufac- Analysis of instrumental data, on-line itoring (where, especially, the possibili- turing: In UPM Kymmene RC produc- monitoring data and quality data: The ties of modern time series analysis still es data from the technical paper prop- case has been progressed using a real are largely unexploited or underdevel- erties. The data is used for research, de- process data set having 13000 on-line oped). velopment and quality monitoring pur- samples (time points) and over a thou- poses as well as for competitor surveil- sand variables. This data have been uti- Objectives lance purposes. UPM Kymmene is in- lized in development of algorithms of The CHESS project addresses five prob- terested in developing the statistical different kind: (1) Multivariate Control lems – Test cases – from rather differ- methods for evaluating and classifying Charts have been utilized to diagnose ent application domains – oil produc- different paper grades and their prop- the quality of spectral data, (2) Dynam- tion, food production, process manu- erties in multidimensional approach. ic PLS models to predict the quality of facturing, plastics production and en- The chemometrics tools are the most end product. A Matlab based program vironmental analysis. The following de- beneficial approaches of this type. Re- (GUI) has been developed. The GUI en- scribes the test problems shortly and search partner responsible for the test ables rapid updating of models (da- discusses their commonalities. Due to problem: LUT/CG. ta and methods), and can be used as confidentiality, the meaning or the sig- Test case 4: Plastics production: a tool for model development during nificance of the studied processes will The aim of the research work is to in- the project. All these methods are ad- not be given or published. crease the material knowledge and the vanced variations of the traditional ch- Test case 1: Oil production: The competitiveness of the Finnish plastic emometrics methods and the analy- aim is to get new empirical modelling and rubber industry. Research partner ses have been done by LUT/CG. Algo- tools, which are based on information responsible for the test problem: TUT/ rithms such as advanced multi-block al- technology. The outcome has been em- LPET. gorithms have been developed further. phasized on tools, which are suitable in Test case 5: Environmental anal- The multi-block methods are applica- fast data mining from large data sets, ysis: Envidata will study problems of ble within certain limits in integration e.g., 1) tools capable to find the most environmental monitoring, such as how of economics into MSPC models. significant variables from large empir- a biological monitoring time series is re- Non-linear processes: Sometimes ical databases, 2) tools for reliable dy- sponding to another – e.g. chemical en- the data exhibit some curvature, which86
    • makes forecasts from the linear models tic, data-driven training. The SOM per- pose. The tool features the following at-not reliable. Methods have been devel- forms a topology-preserving projec- tributes: (1) Calibration tools, (2) classifi-oped to identify the situations, where tion of high-dimensional data onto a cation tools, and (3) univariate and mul-data exhibit (multivariate) curvature. low-dimensional grid allowing nonlin- tivariate statistical process control tools.They also suggest revised non-linear ear interpolation of missing values. The Different types of data sets have beenmethods, which take the curvature in- Empirical Orthogonal Functions (EOF) involved: Lorentzen & Wettre Autolineto account and provide with more re- is deterministic, enabling linear projec- data (Automatic instrument for measur-liable forecasts than linear methods. In tion to a high-dimensional space. They ing the quality of paper) and compari-chemometrics there are three common have also been used to develop mod- son of different paper grades and dif-types of solutions: (1) Parameter estima- els for finding missing data. Moreover, ferent manufacturers based on techni-tion (hard or kinetic models), (2) Nonlin- EOF models allow continuous interpo- cal paper properties.ear regression (soft models) with differ- lation of missing values, but are sensi- Lorentzen & Wettre Autoline data:ent nonlinear variations of PLS Regres- tive to the initialization. We have devel- The equipment determines automati-sion, and (3) Neural networks of differ- oped a new methodology, which com- cally over 20 variables related to paperent kind (soft models). bines the advantages of both the SOM quality. The aim was to quickly and eas- Identification of delays between and the EOF. The nonlinearity property ily analyze different paper sheets, andstages in industrial processes: Identifica- of the SOM is used as a de-noising tool identify deviations from “normal qual-tion of delays or diagnoses of process and then the continuity property of the ity”. The application will automaticallydynamics is an important topic in proc- EOF method is used to efficiently recov- detect the paper grade and compareess industry. Identification methods in er missing data. the sample to a calibration set of thisthis case study were (1) Numerical align- We have created tools for the se- paper grade. The solution is based onment of process variables determined lection of the best variables for two days PCA and Multivariate Statistical Proc-from different stage of process (differ- beforehand prediction of the fructose ess Control charts combined with di-ent units), (2) Utilization of spectral data value. Feature selection and dimension agnostics of Soft Independent Model-in defining delays or process dynamics reduction includes two different ways of ling of Class Analogy. Thus the Matlabbetween different process units (a mul- reducing the number of inputs of the re- program contains calibration tools andtivariate extension is being developed), gression model. First, inputs are select- a tool for diagnosing the new upcom-and (3) Diagnosis of response time from ed among the original features; this is ing data, and enables early warning ofone unit to another where the chang- usually referred to as feature selection significant deviations from normal qual-es may be detected with response win- or input selection. Second, inputs can ity. It also enables comparison of differ-dow of different length. be built from the original features, by ent paper grades in multi- and univar- combining them in a linear or nonline- iate space.Test case 2: Food production ar way; this leads to dimension reduc- Alternative solutions: The generalThe project focused on the problem tion. In such a context, a new algorithm aim of activities of TKK/AIRC was in theof missing data in the database and for variable selection and feature extrac- development of data analysis and esti-the determination of important varia- tion has been developed. This selection mation methods that can be tailored tobles for the prediction of the fructose. strategy algorithm is based on Noise Var- fulfil the ad hoc requirements of moni-The fructose database includes 50% iance Estimation. toring and visualizing production proc-of missing data. The methods to solve esses. The dimensionality reductionthe problem and fill the missing values Test case 3: Process manufacturing methods concentrated to topology andcan be classified into two distinct cate- In TC3 the main focus has been on ef- distance preservation for data projec-gories: deterministic methods and sto- fective utilization of available data and tion and visualization. Diverse manifoldchastic methods. The Self-Organizing estimation of reliability of the data. A learning techniques, ranging from tra-Map (SOM) is based on unsupervised multivariate tool has been developed, ditional Principal Components Analysislearning principle with entirely stochas- which is devoted solely for this pur- to Laplacian Eigenmaps, have been in- 87
    • vestigated and applied to our study cas- which parameters like mould temper- method. This approach was used in es. The results obtained were coupled ature, melt temperature, velocity (time) the project for more detailed parti- and validated by the domain knowl- for injection and back pressure. These tioning of the runoff events during edge of our industrial partners. They al- parameters can, however, vary depend- the study period to find out years, lowed the definition of meaningful dis- ing on product, and will certainly vary in or periods, when runoffs have been plays for process visualization providing different processes. in high vs. low levels affecting the the qualitative framework for a macro- In the final phase field tests in loading intensity in opposite ways. scopic understanding the studied pro- SME´s were carried out to determine 3. Nutrient accumulation processes – duction processes and facilitated the suitability and functionality of select- Our models for nutrient accumula- quantitative development of devices ed tools. The results of the field tests tion processes in seawater turned for monitoring the properties of inter- are used to create not only single qual- out to be very weak for both sub- est from the spectral measurements. ity tools, but also a comprehensive net- stances. We were able to find a mod- The research on spectral meas- work-based quality management serv- el only for organic form phosphorus, urements was also conducted consid- ice – from measurements to satisfied and it was evident only in two up- ering techniques that exploit the func- customer – for plastics industry. permost water columns. One pos- tional structure of the observations. An sibility for weak results could be the original approach to variable selection Test case 5: Environmental analysis high rate of processes and therefore where the relevant inputs are identified Analysis of Baltic Sea data: One of the with series resolution used in our in the correspondence of the function- main statements of the BACC assess- models we just were not able to de- al features was developed characteriz- ment is that in the future the overall tect the real course of events. Also, ing the shape of the spectral curves. We rainfall will increase in the Baltic Sea some additional processes can act also formalized a method for compress- catchment area which will enhance the simultaneously which can blur the ing the spectra by representing them as eutrophication processes in the sea. Fo- general view. a linear combination of Gaussian basis cused on present eutrophication proc- functions whose location and width is esses, we already have been able to in- Analysis of environmental samples (at- optimized. The methods have been an- crease this scientific knowledge during mospheric particles): Laboratory of An- alyzed mostly on referenced problems the project. Examples of such cases are: alytical Chemistry (University of Helsin- from literature and compared to con- 1. General runoff regulation – We dem- ki) has together with Data Rangers de- ventional techniques. onstrated that the North Atlantic veloped and applied data analysis soft- weather effect can generally be de- ware for the measurement data of en- Test case 4: Plastics production tected in the Baltic Sea runoffs with vironmental samples (atmospheric par- TC4 was deeply involved with Da- various climate indices, and even ticles). Software includes basic mathe- ta Rangers Ltd and its software. It is separated between Baltic sub-areas matical tools for statistics and some strongly designed that tools like Web- as the effect showed considerable new tools based on the latest research mailer and Dataminer could form com- geographical variation. results of the information technology mon everyday tools in plastics indus- 2. Nutrient loading processes – Nutri- (for example support vector machine). try. Together with the data determina- ent loading models indicated very Software is easy to use without the tion a study of critical parameters was strong coupling between nutrient need for deep expertise on statistics. carried out. In this work assistance of loading and freshwater runoff, and previous Tekes programmes, such as showed that the Baltic nutrient Impact of the results ProMuovi was reached. It is commonly loading can be modelled only on The developed research results have known that there is not any consensus the basis of incoming freshwater immediate applications in a number among the experts in determination of runoffs. More accurate estimates of industrial fields. We will discuss ben- critical parameters. Research group was of this coupling can be achieved efits starting from immediate bene- concentrated in injection moulding in with some non-linear modelling fits and proceeding towards strategic88
    • benefits. The studied concepts relate tation and monitoring of historical da- Project time scaleto large companies Neste Oil, Danisco, tabases. Practical tools for monitoring 1.6.2006–31.12.2007UPM Kymmene and small companies the quality of the data are required. Tra-Envidata, Data Rangers, as well as to an- ditional Multivariate Statistical Process Project volumealytical technology in general. Control methods were used to solve Total funding 360 470 €, Data Rangers is the medium for the problem. The methods also allow Tekes share 315 470 €transferring the findings to the indus- a robust practical tool for visualizationtry. This spin off of the TKK is special- of data, as well as, for (semi)automated Project participantsized in the implementation and com- monitoring of outliers, extreme samples • Helsinki University of Technology,mercialization of research results. Part of or clustering. Adaptive Informatics Research Centrethe algorithms developed by the Hel- As a co-operative action with our (TKK/AIRC, coordinator)sinki and Lappeenranta Universities of industrial partners (Envidata and Da- • Lappeenranta University of Technology,Technology were implemented dur- tarangers) we have applied our ap- Laboratory of Chemistry (LUT/CG)ing the project. The companies will also proach to produce a web-based service • University of Turku, Archipelagohave access to the algorithms through for environmental time series visualising. Research Institute (UT/ARI)Data Rangers and Envidata commercial A service demo from the vicinity of Por- • University of Helsinki, Laboratory ofsoftware platform. The Archipelago re- voo town sea-areas is already available at Analytical Chemistry (UH/LAC)search centre and Muovipoli dissemi- demo.datarangers.fi. In its final form the • Tampere University of Technology,nate the new analysis practices to their service will be based on Finnish author- Plastics and Elastomer Technologyaffiliated companies. ities’ HERTTA database established for (TUT/LPET) Neste Oil may implement the algo- network of environmental monitoring • Tekesrithms to improve their unit operations. stations in coastal sea areas, which da- • Neste Oil OyjThe new methods have been applied ta will be become public in 2008 by EU • Danisco Sweeteners Oyin developing more reliable and robust legislation, and then the software could • UPM Kymmene Oyjmodels for research and process con- serve as a valuable toolbox for consult- • Data Rangers Oytrol/optimization purposes. One main ants, authorities or decision makers. • Envidata Kyapplication field will be the simultane- To summarize, the CHESS consor-ous utilization of process and spectral tium has had a well defined structure Contact informationvariables in modelling of quality varia- for creating chemometrics innovations, Olli Simulables, which are utilized in controlling of encoding these as software, testing the Aalto University School of Science andthe oil refinery. findings within the partnership, and dis- Technology, Dept. of Information and LUT/CG has been in close interna- seminating the refined concepts to the Computer Sciencetional cooperation with the develop- partner companies and to industry in Tel. +358 500 746 852ment of algorithms concerning meth- general. olli.simula@tkk.fiods such as multi-block modelling, pri-ority regression, CovProc and non-line- Publicationsar modelling. As a result of this lucrative A total of about 30 publications, includ-activity, several international scientific ing 12 scientific papers, 9 conference pa-publications have been published. Al- pers and 6 working reports, have beengorithms are available to the partners published during the project. In addi-who have participated in the develop- tion, several publications were madement process. with collaboration with other projects. The main focus in UPM Kymmene The complete list of CHESS publicationsResearch Center has been the interpre- is in the MASI Yearbook 2008. 89
    • Modelling and simulation in software engineering (MoSSE) – MASIT24 Project background, goals and actual process model to manage the Here Assessment Driven Model- work programme process changes. ling is illustrated by a simple example, Software process improvement can be The MoSSE project can be seen which was built using the Eclipse Proc- based on several approaches such as as a part of the strategic, continued re- ess Framework Composer (EPF Compos- modelling, assessment, measurement, search of CoSE with the aim to develop er). SPICE assessment model constitutes and technology adoption. The ap- an efficient methodology framework a process library, which was implement- proaches supplement each other, but for process improvement in software ed as EPF method content. Descriptive one usually dominates. Process assess- organizations. The Software Process Im- and prescriptive process models were ment is a norm-based approach, which provement iNItiation framework (SPINI) realized as EPF capability patterns. is often used for evolutionary process developed by CoSE provides the start- In this example the Software Con- improvement. Process modelling com- ing point for this research. The assess- struction process of a software organ- prises analysis of activities, artifacts, ment method contained in SPINI fulfills ization was assessed and modeled. roles and tools. the requirements of the ISO/IEC 15504 Base practices were used as indica- The goal of the project is to inte- standard (SPICE). tors. Figure below on the left depicts grate a method for descriptive process the actual, descriptive process mod- modelling with an approach of assess- Results el as an activity diagram. The assess- ment based software process improve- In this study we complemented the ment model’s practices Develop Soft- ment. The application of the method SPINI framework with Assessment Driv- ware Units and Verify Software Units results in detailed process profiles with en Process Modelling. We propose have been mapped to the organiza- process improvement opportunities, three extensions to the approach: proc- tion’s activities, Code Software Mod- and a descriptive process model of the ess modelling related to capability indi- ule and Test Software Module, which assessed software unit. The main bene- cators, prescriptive process modelling, are shown in the diagram. It was found fit of the approach is that the improve- and process library to support prescrip- that both of the assessed activities are ments are clearly expressed using the tive process modelling. performed by Developer role. Software Figure 1. Development of the process improvement framework. 2006 2008 2010 SPINI SPINI (+) SPINI (++) SataSPIN Process Modeling Process Practices Simulation ISO/IEC 15504 Assessment Process SPI Approach Model Extensions Knowledge Base90
    • Figure 2. Activity diagrams of the descriptive and prescriptive models of software construction process. SPU SW Module SPU SW Design 17-14 SPU SPU Test SPU SPU SPU case SW Design SW Module SW Design SW Design SW Module specification SPU Developer ENG.6.BP1 Developer ENG.6.BP3 Ensure SPU Code SW Module SPU Test SW Module SPU Developer unit verification SPU Code SW Module SPU Test SW Module consistency procedures 17-14 SPU 13-22 14-04 SPU Test SW Module Tracebility Test log SW Module case record specificationDesign acts as the input work product ness goals to meet the process criteria at the ISO/IEC JTC1 SC7 WG24 as a pos-of Code Software Module activity, of of the assessment model. sible means to publish the emerging in-which output is Software Module work ternational standard 29110. With activeproduct. Test Software Module activity Impacts participation in The Finnish Softwareuses Software Module workproduct as The results of MoSSE will enable effi- Measurement Association (FiSMA) wethe input. The assessment result sug- cient use of process assessment data to are able to support the Finnish indus-gests implementing counterparts for support process modelling. Integration try by affecting the contents of the fu-the base practices Develop Unit Verifi- of assessments and modelling may re- ture international standards and by pro-cation Procedures and Ensure Consist- sult in increased understanding of the viding the related directions well beforeency and related work products into process, accurate process improve- the standards take effect.the organization’s process. ments, and faster process development Intensive contacts with the Techni- The activity diagram of the pre- cycles. The experiments are carried out cal University of Ostrava (TUO) helpedscriptive process model on the right con- with software engineering and IT serv- in experimenting combined processtains the improvement suggestions. ice processes, but the results are appli- modelling and assessment. During theComparing it with the descriptive mod- cable to many human centered design project we set up also new researchel there are still the same actual activi- and service domains. connections with other European re-ties, but also additional elements from Participation in the ISO/IEC stand- search institutes.the process library. The prescriptive ardization work is of utmost importancemodel proposes a library activity De- in providing international contacts and Publicationsvelop Unit Verification Procedures be- an exceptional opportunity to present Ala-Uotila, J. 2007. Robottijärjestelmänfore the activity Test Software Module, our expertise in the field. ISO/IEC JTC1/ suoritusarvojen mallintaminen jaand the activity Ensure Consistency af- SC7 is the main source for software raportointi. Diplomityö, Tampereenter Code Software Module. and system engineering process mod- teknillinen yliopisto, 69 p. The descriptive process model de- els used in the global software indus- Barafort, B., Jezek, D., Mäkinen, T., Stolfa,scribes how the process is actually per- try. The technologies applied in mod- S., Varkoi, T. & Vondrak, I. Modellingformed in the organization. The pre- elling and creation of process libraries and Assessment Models in IT Servicescriptive process model describes how are applicable also in the international Process Improvement. Proceedings ofthe process should be performed, when standardization work. The results of the the EuroSPI 2008 European Softwareit complies with the organization’s busi- project have already been presented to Process Improvement Conference, 91
    • 3.–5.9.2008, Dublin, Ireland, submitted Mäkinen, T., Varkoi, T. & Soini, J. Integration Soini, J., Varkoi, T., Tenhunen, V. & Tukiainen, for review. of Software Process Assessment and M. Empirical case study of software Fiedler, G., Jaakkola, H., Mäkinen, T. & Modelling. PICMET ‘07 Management of metrics using the SPICE framework. Varkoi, T. Process improvement for Converging Technologies Conference, Proceedings of the 7th International web information systems engineering. 5–9 August 2007, Portland, Oregon, SPICE Conference on Process Proceedings of the 7th International USA. Assessment and Improvement, 9–11 SPICE Conference on Process Soini, J. Keto, H. & Mäkinen, T. Toward May 2007, Seoul, Korea, p. 22–27. Assessment and Improvement, 9–11 a balanced software business May 2007, Seoul, Korea, p. 1–7. measurement. In: Dekkers, T. (ed). Projcect time scale Gresse von Wangenheim, C., Varkoi, T. & Proceedings of the 3rd Software 1.1.2006–31.12.2007 Salviano, C.F. 2006. Standard based measurement European Forum, 10–12 software process assessments in May 2006, Rome, Italy, p. 33–46. Project volume small companies. Software Process Soini, J., Keto, H. & Mäkinen, T. An 290 000 €, Tekes sharw 250 000 € Improvement and Practice 11 3, p. approach to monitoring the success 329–335. factors in software business in small Project participants Mäkinen, T. & Varkoi, T. 2007. A harmonized and medium size software companies. • Tampere University of Technology in design for process assessment Proceedings of PICMET ‘06, Technology Pori, Centre of Software Expertise (CoSE) indicators. Software Process Management for the Global Future. • Tekes, the Finnish Funding Agency for Improvement and Practice 12, p. 331– Istanbul, Turkey, 8–13 July 2006, p. Technology and Innovation, 338. 2801–2808. • Cimcorp Oy Mäkinen, T. & Varkoi, T. Assessment Driven Soini, J., Mäkinen, T. & Tenhunen, • Elinar Oy Ltd Process Modelling for Software Process V. Managing and processing • Satakunnan Puhelin Oy Improvement. PICMET ‘08 Technology knowledge sharing between software • TietoEnator Oyj Management for a Sustainable organizations: a case study. PICMET Economy Conference, 27–31 July 2008, ‘07 Management of Converging Contact information Cape Town, South Africa, accepted for Technologies Conference, 5–9 August Timo Varkoi & Timo Mäkinen publication. 2007, Portland, Oregon, USA, p. 1108– Tampere University of Technology, Pori 1113. Tel. +358 2 627 2844 timo.varkoi@tut.fi, timo.makinen@tut.fi92
    • Innovative simulation method of multi-phase chemistry (InnoSim) – MASIT25Objectives the relative role of corresponding inten- tions provides a link between free en-The primary objectives in the InnoSim sive and extensive variables by altering ergies and conservation constraints,project were to develop methods and the base vectors of the energy space. which can be used to elucidate sever-software for the use of Transformed The three most common transforms al energy-related modelling methods.Gibbs energies in the Constrained Free concern pH, ionic strength and change Also the previous development on theEnergy (CFE) framework. The knowl- of the standard reference state for sol- Constrained Free Energy concept trans-edge of transformed Gibbs energies utes. These transforms connect tradi- lates into Legendre transforms whenimportant in biochemical systems was tional thermodynamics with what was needed.to be sought from Massachusetts Insti- formerly known as biochemical con-tute of Technology (MIT) while the CFE ventions. Scientific or technical progressmethod has been developed by VTT The developed techniques to combineTechnical Research Centre in Finland. Results the benefits from transformed and con-The combined method was to be val- strained energies allow thermodynamic Generalidated and demonstrated by examples modelling to move from process chem-of increasing importance. Modelling Main part of the work was performed istry to biochemical applications. Thetasks were selected primarily from bio- during a 10 month visit by M.Sc. Peter methods show potential for promisingchemistry but also from the biorefinery Blomberg at MIT in 2007–2008. The pri- applications in pathway analysis, met-separation processes. mary objective was achieved and, to abolic engineering, and high-through- some extent, exceeded. Transformed put screening. A brief illustration of theMethods Gibbs energy standard state values can basic components is given in what fol-Constrained Free Energies is a compu- be used in stead of Gibbs energies if lows. The systems are biochemical intational concept developed at VTT for the conservation equations are prop- nature but the methods are applicablemodelling and simulation of thermo- erly adjusted. This allows existing ther- to any chemical system.chemical processes, where physical modynamic software to be used with For example, material baths can beand chemical phenomena are mutual- compiled tables. A method developed used to implement ideal buffers withly indispensable. The concept relies on exclusively for validation was used as a limited capacity. Figure 1 shows the ti-the fundamental tendency of systems basis for the subsequent progress. The tration behaviour of a phosphate bufferto increase their entropy and thereby method developed is now referred to as and its ideal equivalent. Once the idealdecrease their energy. There are how- constant contributions. It can be used buffer has run out, the system behavesever limitations to how energy can be to implement material baths and Leg- as if the buffer never existed. The sec-transformed from one form to anoth- endre transforms to Gibbs energy min- ond set of curves show how the alka-er. These limitations can be either stat- imization. This leads to three differ- linity is affected.ic or dynamic and are included as entity ent but equivalent ways to calculate Another example is the thermody-conservation relations, which are treat- with transformed energies in the con- namic pathway analysis consisting ofed as internal constraints in the thermo- strained free energy framework. reaction feasibility evaluation and statedynamic system. Following this result, the possible change probability assessment. This Transformed Gibbs energies are uses of constant contributions in oth- can be done either comparatively or onLegendre transforms of the Gibbs en- er fields were assessed. In principle any an absolute scale. Results are often bi-ergy fundamental energy potential to work term or energy contribution could nary for any given scenario. Energy min-better suit the specifics in biological sci- be implemented with this method. The imization software may be used to gen-ences. A Legendre transform exchange general method of constant contribu- erate time traces and study entity-con- 93
    • Figure 1. Buffer comparison. nent modelling from process chemis- try and materials science to biochem- 9 pH phosphate buffer 30 pH ideal buffer ical analysis. The new methods can al- 8 so be applied in various problems when alk phosphate buffer 20 Alkalinity [mM] 7 alk ideal buffer developing models for the biorefinery. 6 10 pH 5 Co-operation 0 4 InnoSim research was organised under -10 the auspices of the MASIT04 consorti- 3 2 -20 um. The international part consisted of 0 5 10 15 20 25 a 10 month visit to MIT Advanced Study Added NaOH [mmol] Program by M.Sc. Blomberg. Figure 2. Pathway energy diagram. Dissemination 0,05 The new method will be published as part of a doctorate dissertation. Relative energy [MJ] 0 -0,05 Publications Stepwise 1M std -0,10 Stepwise 1mM std Blomberg, P. & Koukkari, P. 2009. The -0,15 Stepwise and mix Combination of Transformed and Gmin and mix Constrained Gibbs Energies, Math. -0,20 Biosci 220, 81–88. Glu Pyr H&G G6P F6P 3PG 2PG GAP FBP BPG PEP Blomberg, P. & Koukkari, P. 2009. Thermo- Prevalent metabolite chemical Analysis of Reaction Pathways, Figure 3. Concentrations for blue curve. 19th European Symposium on Computer Aided Process Engineering 2,0 Glu – Escape19, J. Jezowski and J. Thullie G6P (editors) Elsevier, 7 p. Concentration [mM] F6P 1,5 FBP DHAP Project time scale 1,0 GAP 1.8.2007–31.5.2008 BPG 0,5 3PG 2PG Project volume 0 PEP Total 160 000 €, Tekes share 112 000 € Glu H&G BPG 3PG 2PG G6P F6P FBP GAP PEP Pyr Prevalent metabolite Project manager Pertti Koukkari VTT Technical Research Centre of Finland strained equilibria. Figure 2 shows the Thermal analysis makes use of Tel. +358 20 722 6366 effect of mixing on reaction feasibility transformed enthalpies in assessing pertti.koukkari@vtt.fi evalutation. Pathway analysis with step- heat production or consumption dur- wise advancement, for instance, may be ing chemical reactions. Additional information improved by considering the likely con- Peter Blomberg centrations at each step. The concentra- Impacts VTT Technical Research Centre of Finland tions are shown in Figure 3 for interpre- The developed method extends the Tel. +358 20 722 4013 tation as an exercise. scope of thermodynamic multicompo- peter.blomberg@vtt.fi94
    • Development of the 3D power plant simulator – MASIT27Background el is made for design face of the pow- Project implementationKymenlaakso University of Applied Sci- er plant. So it is ready before the actu- The purpose of this 3D-project was toences has history of operator simulators al power plant is built. This gives big develop a new kind of training simu-since year 1999. Simulator training start- advantage in operator and power plant lator concept. Simple project goal wased with a project with Foster Wheeler training when the model is used in the to connect 3D-model and DCS-simula-Energia Oy (FWE). The main goal was to 3D-simulator and plant personnel can tor to one simulator and use it as a newdevelop prerequisite simulator training be trained in virtual world that actually concept. It could be used at power orfor students, refresher courses for op- works like real power plant. recovery boiler plants for commission-erators and FWE`s personnel and cus- Comparing different ways to make ing training, operator training and engi-tomers. 3D-simulator was investigated in the neering student education. Mostly power plant simulators are project. This included game motors in-used operator training and usually on- tended to fun purposes and commer- Project implementation shortlyly covered operations are limited in the cial 3D-visualition software’s. • The goal was to produce workingcontrol room area. The simulators are This research confirms the fact but limited simulatorbased in DCS-displays and calculation that it is possible to connect DCS-sim- • The goal was to assure 3D-worldmodel. ulator and 3D-model together. This can usability Simulators based for the DCS-op- be done in reasonable amount of work • To use real power plant as modeleration displays are only suitable for and money.training power plant control room op-erating and DCS-systems. The 3D-simu- Figure 1. View in the 3D-simulator (Game Demo).lator provides wider platform for train-ing because it is possible train all need-ed things that are connected to suc-cessful operation of power plant. Thismeans that field operations, handvalves and local controls can be oper-ated with 3D-simulator. This is the mainreason for starting the 3D-simulator re-search project. In the project the goal was to con-nect traditional DCS-simulator with thenew concept 3D-simulator. The envi-ronment for the 3D-part of the simula-tor was borrowed in the game world. Inthis new concept it is possible to oper-ate in control room and all the areas inboiler and turbine building. One of the basic principles wasto use 3D-desing model for start pointof the 3D-world. This 3D-desing mod- 95
    • • Piggybacking of real power plant Impacts Urpalainen, S. 3D-voimalaitossimulaatorin automation and DCS systems The project proves that advance 3D- kehittäminen. Tekes final report. • Use of existing 3D-design model simulator is possible to make with Kymenlaakso University of Applied • Use of existing process model reasonable cost. This fact had also im- Sciences. pact on companies other than those Urpalainen, S. 2008. Tutkimusjulkaisu, Results in the project. New companies are in- Kymenlaakso University of Applied As the result of the project, partners can terested to join in the next project. Sciences. achieve new business activities around The project also proves that there is Vilpponen, P. 3D-mallien optimointi ja simulators. In future, simulators can need for advanced 3D-simulator. Un- voimalaitossimulaattoriin. Bachelor be offered to customer side by boiler doubtedly, there will be new project Thesis. Kymenlaakso University of projects. Developed 3D-simulator con- where the existing and new project Applied Sciences. cept improves Kymenlaakso University partners develop 3D-simulator con- of Applied Sciences and project part- cept further on. Project time scale ners training possibilities. One of main 1.11.2006–31.12.2007 focus areas was simulator concept’s Publications suitability in training and finding the Liljeqvist, D. Hallintaohjelman toteutus Project volume best ways to use it in different training 3D-voimalaitossimulaattoriin. Bachelor Total 122 000 €, Tekes share 91 500 € situations. Thesis. Kymenlaakso University of The research made in the project Applied Sciences. Project participants confirms the fact that it is possible con- Tertsunen, P. 3D-voimalaitossimulaation • Kymenlaakso University of Applied nect DCS-simulator and 3D-model to- pelimoottori. Bachelor Thesis. Sciences gether. This can be done with reasona- Kymenlaakso University of Applied • Foster Wheeler Energia Oy ble amount of work and money. Sciences. • Systecon Oy • Jamtec Oy Figure 2. View in the 3D-simulator (JetStream). • Media Center Kotka • Cursor Oy as partial financier Contact information Markku Huhtinen Kymenlaakso University of Applied Sciences Tel. +358 44 7028 323 markku.huhtinen@kyamk.fi96
    • Flow physics and modelling (FLOPHY) – MASIT28Background and DNS is LES, where only a part of ty are investigated. Furthermore, exper-The connecting themes of the partic- turbulence spectrum is simulated in iments on diesel spray formation haveipants’ work packages are: Computa- the time-accurate manner. Today, die- been carried out.tions of different jets, use of Large Eddy sel engine research constitutes a multi-Simulation (LES), use of the open soft- disciplinary field of science where ex- Project actionsware (OpenFOAM), and researchers’ vis- periments and numerical simulations Reactor measurements was done build-its abroad and from abroad. The thor- complement one another in an insepa- ing up a new cross flow reactor to dem-oughness and complexity of CFD (Com- rable way. The quality of turbulent mix- onstrate combustion and SNCR processputational Fluid Dynamics) modelling ing within the fuel spray is in a key role in bubbling fluidized bed boiler. Bothhas reached a level that even by experts when developing new, less polluting RANS and LES computations using com-was hardly predictable a few decades and more efficient, engines. mercial FLUENT software and academ-ago. This involves modelling of compli- ic solver developed at Stanford Univer-cated geometries, a use of sophisticat- Objectives sity were done. Steady state simulationsed physical models, and also coupling One objective in the project was to im- were made with commercial CDF-code,of CFD with other simulation tools like prove understanding of different as- Ansys Fluent software. Turbulent com-structural analysis, optimisation or elec- pects of reactive turbulent cross flow. bustion is modelled first with finite ratetromagnetics. The approach is called In this study, the emphasis was on the and EDCM combination following with‘multiphysics’ and new acronyms like FSI combustion in bubbling fluidized bed EDC model. Nitric oxide formation was(Fluid-Structure Interaction) or TCI (Tur- freeboard conditions and the forma- simulated with NOx model included inbulence-Chemistry Interaction) have tion and reduction of nitric oxide emis- the software. Ammonia is injected tobeen invented to describe various fields sions with the SNCR (selective non- the main among secondary air and ni-of application. Most engineering CFD catalytic reduction) process. Both the tric oxide is fed among main flow. Sec-applications are based on the Reynolds CFD and the experimental approach- ondary air is injected from three 20 mmAveraged Navier-Stokes (RANS) equa- es were used to understand the phe- diameter nozzles. Main flow is preheat-tions. This technique is normally used nomena. The main computational tool ed 900 °C and secondary air is at roomto obtain steady-state results that are is LES technique but also RANS one was temperature. At second case meth-convenient from the engineering point used. The experimental part included ane was replaced with oxygen and on-of view. However, gradually it has been building a new pilot cross flow reactor ly nitric oxide formation was studied. Inrealized that RANS approach will remain in which the emission reduction can be third case methane was replaced withunreliable in spite of the improvements observed in more detail. oxygen and secondary air was preheat-made in recent years. Time-dependent The connection between drop- ed at 150 °C. Heat transfer for super-problems can be solved using a same let size and mixture quality was not ful- heated tubes was done with LES com-type of modelling called URANS (Un- ly understood. The aim of the research putations using OpenFOAM in order tosteady RANS), but its physical model- is to bring new insight to the fuel spray demonstrate heat transfer in boiler tubeling is even vaguer than that of RANS. It mixture formation problem using the package. Two researcher visits to Stan-is possible to solve directly the Navier- LES and Lagrangian Particle Tracking ford University (USA).Stokes equations for laminar flow cas- (LPT) methods to simulate the droplet Overall developments in simula-es and even for turbulent flows when motion. In specific, detailed paramet- tion methods are made, in which it hasthe Reynolds number is low enough. ric studies on droplet size effects, drop- been concentrated in the OpenFOAMThe approach is called Direct Numer- let size distribution effects and droplet CFD toolkit, which has been extensive-ical Simulation (DNS). Between RANS mass loading effects on mixture quali- ly used especially in LES. Co-operation 97
    • has been made with CSC and the su- Results tion of OpenFOAM. LES has been exten- percomputers are utilized. Python- A new cross flow reactor was built to sively studied in room ventilation prob- based simulation tools have been de- TUT laboratory. Experimental results will lems. It has been found that LES can veloped for OpenFOAM. RANS/URANS be performed in following projects. Re- easily lead to completely wrong results, modelling of impinging jets have been sults from methane combustion simu- whereas the conventional RANS meth- carried out in WP8. A new turbulence lations are realistic, all methane is burnt ods are much more robust. However, model has been developed and results and highest temperature is approx- in many applications it is known that have been compared with the experi- imately 1360 °C. In this case nitric ox- RANS simulations cannot predict cer- mental data [Rahman et al.]. Room ven- ide reduction with selective non-cata- tain phenomena and thus LES or its var- tilation simulations have been made lytic reduction does not occur. Temper- iant DES have to be applied. The strong using LES, DES and various RANS ap- ature level is too high for reduction; the effect of the boundary conditions in LES proaches. One topic is a fuel rod bun- optimal temperature window for SNCR must be taken into account. On the oth- dle of a nuclear reactor. is 800–1100 °C. In following cases tem- er hand the influence of the sub-grid- The fully compressible Navier- perature was decreased to the optimal scale modelling is not as important. In Stokes equations with a spray source temperature window and SNCR process RANS/URANS simulations both Open- term are numerically solved by taking occurred. In Figure 1 (TUT/EPR) rate and FOAM and FINFLO have been used. The the full advantage of the OpenFOAM mole fraction of NO in SNCR process are OpenFOAM applications are so far in open source simulation code to car- shown. In Figure 2 (TUT/EPR) a momen- the field of room ventilation, the FINF- ry out massively parallel simulations tary temperature distribution of 13-tube LO cases in WP8 concerning impinging on the CSC supercomputers. Altogeth- case is presented using LES. jets. With the existing RANS models it er 70000 CPU hours of simulation time Largest effort in TKK/FLUID has has been found out that URANS does has been used to carry out tens of indi- been made in verification and valida- not improve the results in comparison vidual simulations. Experimental stud- ies on diesel spray formation and struc- Figure 1. (a) Rate and (b) mole fraction of NO in SNCR process (mol/(m3·s)n) usig RANS. ture are carried out. Prediction of thermal comfort in a) b) offices and other ventilated spaces de- pends on correct simulation of venti- lation jets. RANS-models tend to over- predict air velocities and draught risk in occupied zone. The aim was to com- pare LES with RANS-methods in order to gain better results. LES was found to give more realistic velocities when compared to measurement results in laboratory test room. Studied cases rep- resented office ventilation with chilled beams and jets in large enclosures from swirl diffuser and simple nozzle. Main advantage with LES was ability to sim- ulate time dependent fluctuations of room air flow pattern. Main difficulty of LES-simulation was in determining cor- rect turbulent boundary conditions for inlet jet.98
    • Figure 2. Momentary temperature distribution of 13-tube case using LES. fuel sprays including the random (but correlated) shape of the spray bound- ary. In this respect this research has greatly contributed to the state-of-the- art spray modelling: we are not aware of previous studies which would have succeeded in reproducing the physical droplet dispersion adequately in diesel fuel sprays. It should be mentioned that in the present simulations no spray sub- models were employed for e.g. droplet dispersion which is possible since in LES the energy containing scales of the flow are properly resolved. Noise generation by airflows inwith RANS. If the situation is known to pipe performance study flow struc- ventilation devices was studied by sim-be of an oscillatory nature, URANS will tures at the wake were investigated. To ulating simple flow obstacles and realusually predict steady results that do study the behaviour and the grid inde- air terminal devices. Noise and veloci-not differ from the RANS calculation. In pendence of the flow various proper- ty measurements were carried out fora case of the impinging jets the RANS ties were investigated in the sections the simulated cases for comparison.modelling used seems to be at least as depicted in Figure 4 (TKK/AERO). Since computer aided aero-acousticaccurate as the LES-based results. This Figure 5 (TKK/ICE) shows a qual- simulation is a new and emerging tool,is probably owing to the fact that in the itative comparison of LES and experi- it has not yet been exploited by venti-simulated case the computer resources mental fuel sprays. It is seen that it re- lation industry, despite its use in avia-required for a good LES where to high. produces well the transient aspects of tion and automotive industry. Currently,The work with the fuel bundle of a nu-clear reactor has revealed some prob- Figure 3. Flow inside exhaust pipe.lems in the simulation methods. Withthe very high aspect-ratio cells result-ed in the first grid arrangement theOpenFOAM solver did not converge.The work is still going on and the gridhas been modified, which resulted in ahigher number of grid points. 3-dimensional RANS simulationswere performed to investigate theflow inside exhaust pipe of a jet en-gine powered Unmanned Aerial Vehi-cle (UAV). Seven different exhaust pipegeometries were designed and exam-ined. High aerodynamic efficiency wasthe main requirement for the design.Typical flow velocity distribution insidethe exhaust pipe is shown in Figure 3(TKK/AERO). In addition to the exhaust 99
    • Figure 4. Kinetic energy of turbulence at the wake. and the code will be studied in some new research projects. At the moment open-source software provides the only means to apply massively parallel simu- lations. The results obtained are encour- aging, but much more work is required in order to build a descent computa- tional environment for a practical work. The simulations and experiments show that the fuel droplet size is the determining factor that leads to good/ poor mixture: even 50% of the air in- side the fuel spray may remain non-uti- lized if the droplets are large in compar- ison to the droplets being small. Hence, the results strongly support the exist- ing trends and developments towards higher fuel injection pressures (e.g. well over 2500 bar). International cooperation the most effective way of aero-acoustic silent designs it was demonstrated that During the project, working research simulation is to model the noise sourc- it is possible to recognize a noisy prod- visits to and from the following univer- es by incompressible LES flow simula- uct design and locate the noise sources sities were made: Stanford University tion, followed by acoustic simulation from the simulations. The results of the (USA), University of Rome Tor Vergata using special-purpose software to ob- study will give a basis for applying sim- (Italy), Norwegian University of Science tain the noise field. An alternative, but ulation tools in product development and Technology (Norway), Washington computationally much more laborious, of ventilation devices for avoiding flow University in St. Louis (USA), University approach is to perform flow simulation noise problems in products. of Southampton (UK), Royal Institute of alone, which then has to be compress- Technology (KTH, Sweden), Rheinisch- ible. This approach was nevertheless Impacts Festfälische Technische Hochschule (R- adopted in this research to provide data An impact made so far concerns the FTH, Germany). for judging the potential of genuine ae- application of the open-source soft- International co-operation has ro-acoustic simulation in ventilation in- ware OpenFOAM. The first applica- been made with the Stanford Universi- dustry. By simulating pairs of noisy and tions have been made in the industry ty and with the Univeristy of Rome Tor Figure 5. Qualitative comparison between LES and experiments (It is seen that LES reproduces the droplet dispersion and spray shape well).100
    • Vergata (TKK/FLUID). A three-month vis- Rahman, Md. M. & Siikonen, T. 2009. Project time scaleit was made to the Stanford University Compound wall treatment with low- 1.1.2008–31.12.2009(TKK/FLUID, TUT/EPR) during the spring Re turbulence model. Submitted for2008. The research topic was LES. In publication in the International Journal Project volume2009 a short visit followed by a three- for Numerical Methods in Fluids. Total 783 300 €, Tekes share 580 000 €month visit in 2010 to the University of Saarinen, P. 2009. Ilmastoinnin virtaus-Rome Tor Vergata was made. The mu- äänen laskenta. Työympäristötutki- Project participantstual research concentrates on the sim- muksen raporttisarja 39, Työterveys- • Tampere University of Technology,ulation and experimental activities in laitos. Dept. of Energy and Processjets. A co-operation in the application Saarinen, P., Koskela, H., Kosonen, R. & Engineering (TUT/EPR)of OpenFOAM is also made. Interna- Ruponen, M. Asymmetric Collisions • Helsinki University of Technology,tional collaboration within the Interna- of Two Attached Plane Jets. 11th Dept. of Applied Mechanics, Fluidtional Energy Agreement (IEA) consor- International Conference on Air Mechanics (TKK/FLUID)tium has been established during the Distribution in Rooms. Proceedings • Helsinki University of Technology,project. In specific, the annual IEA fuel of Roomvent 2009, Busan, Korea, 24– Dept. of Applied Mechanics,spray workshop in Detroit, organized 27May 2009. Aerodynamics (TKK/AERO)by TKK/ICE, has become widely pop- Tossavainen, V. 2009. Superheater Tube • Helsinki University of Technology,ular among the researchers from vari- Heat Transfer Simulations Using Large- Dept. of Energy Technology, Internalous countries including Japan, Germa- Eddy Simulation: Corrected Results Comb. Engine (TKK/ICE)ny, USA, Canada, Sweden, Finland, Chi- and Continuation Simulations. TUT • Finnish Institute of Occupational Health,na, and India. Two shorter research vis- Report, 12 p. Good Indoor Environment Team (FIOH/its to KTH/Stockholm supported the Vuorinen, V., Larmi M. & Fuchs, L. 2010. GIET)long term collaboration between TKK/ Effect of Droplet Size and AtomizationICE and KTH. Visits to R-FTH (FIOH/GI- on Spray Shape: A Priori Study Using Helsinki University of Technology (TKK) isET) were done also during the project Large-Eddy Simulation. Chosen since 1.1.2010 The Aalto University School ofperiod. to a special edition from THMT-09 Science and Technology. conference (Rome) to Flow, TurbulencePublications and Combustion, in review. Contact informationKauppi, M. 2009. Modelling Turbulent Vuorinen, V., Larmi M. & Fuchs, L. 2010. Antti Oksanen Combustion of Test Reactor. Master of Large-Eddy Simulation of Droplet Tampere University of Technology Sci. Thesis, 60 p. Stokes Number Effects on Turbulent Tel. +358 400 753 088Koskela, H., Häggblom, H., Kosonen, R. & Spray Shape. Accepted for publication antti.oksanen@tut.fi Ruponen, M. 2010. Air Distribution in in Atomization and Sprays. Office Environment with Asymmetric Workstation Layout using Chilled Beams. Accepted to Building and Environment, Feb 9, 2010. 101
    • Modelling interfacial partitioning in multi-phase systems (INTER) – MASIT29 Background tors. Particular emphasis was laid on the ture that can be used for both Industrial processes occur most often multiphase thermochemical approach. thermal and reverse osmosis de- in multi-phase systems, which include Experimental investigation of elec- salination processes. suspensions, gas dispersions, melts tro-wetting phenomena was carried • 1-dimensional two-phase flow with solid inclusions or slag compo- out both in aqueous and molten slag simulation program for a flashing nents. Surfaces and interfaces appear systems for model validation. black liquor spray nozzle. in all industrial systems as success keys, • Model for surface tension of mol- setting the conditions for smooth and Results ten oxide slags and the effect of economic operation, endurance of ma- In the INTER project the participants de- applied external electric potential terials as well as key criteria for product veloped new methods for modelling in- on it. quality. terfacial and partitioning phenomena. • Constrained Free Energy models Specific applications were: for liquid-liquid interfaces and ad- Objectives • Model for heat transfer through a sorption processes on aqueous- Objective of the project was to devel- running slag flow deposit, applica- solid and molten metal-gas inter- op new innovative approaches partic- ble to metallurgical processes and faces. ularly for interfacial effects on segre- recovery boilers. Implemented in a • Subprograms for calculation of ther- gation of particulates or bubbles, their CFD code. modynamic properties of aqueous nucleation, growth and transport in • Toolbox for calculation of materi- electrolyte solutions based on the industrial systems. The earlier devel- al properties of the H2O-NaCl mix- Pitzer formalism. oped Constrained Free Energy meth- od was used to quantify surface and Figure 1. Black liquor nozzle and principles of the main flow model. interface layer compositions and their phase stability and to evaluate interfa- cial potentials for partitioning process- es. Thermodynamic multiphase mod- els were to be implemented for aque- ous solutions and interfaces. The aim was to use these new models in Fin- land based commercial software and service products for multi-phase and CFD simulation businesses. Methods Interfacial and partitioning phenomena and properties were modelled by vari- ous computational techniques and the resulting models or computational rou- tines were applied in programmes such as thermodynamic equilibrium solvers or CFD and chemical process simula-102
    • Several methods proved to be ap- Figure 2. HSC 7.0 showing the new aqueous solution property estimator.propriate for industrial purposes andwork has commenced for their imple-mentation in practical applications. Theuse of external electric potential yetproved unpractical for effective inter-face control in high temperature proc-esses.Application in commercial productsIn co-operation with Process Flow OyLtd the first application specific mod-els were developed for the AFROK ro-tary kiln simulator, which combines themultiphase chemistry calculation withcomputational fluid dynamics. The da-tabase developed for the electrolyte ac-tivities in aqueous systems could be im-plemented at Outotec Research Oy as Figure 3. AFROK rotary kiln simulator.a specific Aqua module of the HSC Sim7.0 process simulator. The database wasalso used for the modelling of new in-dustrial suspension processes in co-op-eration with the industrial members ofthe INTER consortium. The dynamic re-verse osmosis model developed in theproject is also appropriate for practi-cal utilization within the Apros dynam-ic simulator (VTT and Fortum NuclearServices Oy).International cooperationDuring the project research exchangewas commenced between VTT and De-partment of Materials Science in OsakaUniversity for the development of hightemperature interfacial models. Twopost-graduates from Osaka Universityvisited VTT in a weekly seminar seriesheld in August–September 2008. M.Sc.Risto Pajarre worked as a visiting scien-tist at the University of Osaka for threemonths in 2009. 103
    • Selected publications Kangas, P. & Kangas, P. 2009. Multi-phase Project volume Hakkarainen, V. 2008. Master’s thesis. chemistry in Process Simulation. Total 749 644 €, Tekes share 558 996 € Ulkoisen potentiaalin vaikutus Licentiate thesis. Helsinki University of elektrolyyttipisaran kostutukseen, Technology. Project participants Prosessi- ja ympäristötekniikan osasto, Koukkari, P. (ed) 2009. Advanced Gibbs • Åbo Akademi University University of Oulu. Energy Methods for Functional • Aalto University, School of Science and Hakkarainen, V., Riipi, J., Fabritius, T., Materials and Processes. VTT research Technology Mattila, O. & Mattila, R. 2009. Control notes 2506. • Oulu University of surface phenomena and separation Li, B., Brink, A. & Hupa, M. 2009. Simplified • VTT Technical Research Centre of technologies by external electric Model for Determining Local Heat Flux Finland potentials. Final report, Report 339. Boundary Conditions for Slagging Wall. • Andritz Oy Prosessimetallurgian laboratorio, Energy&Fuels, 23, 3418–3422. • Fortum Nuclear Services Oy University of Oulu, 58. Pajarre, R. & Koukkari, P. 2009. • Metso Power Oy Heikkinen, E., Riipi, J., Fabritius, T., Pajarre, R. Thermodynamics of adsorption at • Outokumpu Stainless Oy & Koukkari, P. Computational modeling the aqueous-air interface. Journal of • Outotec Oyj of oxide’s surface tension in secondary Colloid and Interface Science, 337, • Process Flow Ltd Oy metallurgy and continuous casting. VIII 39–45. • UPM-Kymmene Oyj International Conference on Molten Pajarre, R. & Koukkari, P. Calculation of Slags, Fluxes & Salts, Chile. liquid-liquid interfacial energies with a Contact information Järvinen, M. P., Kankkunen, A. P., Heikkilä, multilayer Gibbsian model. CALPHAD Pertti Koukkari V. P. & Miikkulainen, P. H. A One- 2008 Conference, Saariselkä, Finland. VTT Technical Research Centre of Finland Dimensional Flow Model of a +358 40 583 4092 Flashing Black Liquor Gun. ICRC 2010 Project time scale pertti.koukkari@vtt.fi Conference, Williamsburg, Virginia, 1.1.2008–31.3.2010 USA.104
    • Ice-structure interaction modelling and simulation (STRUTSI) – MASIT30Background ers, winter navigation and road traffic. between the segments. Material failureThere is a wide demand in many appli- There is also large international demand controls the segments so that model iscations for the modelling of the contin- by the oil companies and by wind en- updated after each crack propagationuous failure process, and there are no ergy industry. segment. This approach allows analysis3D-models available. With the help of continuation after complete failure andthe modelling it is possible to determine Modelling of the continuous the creation of separate segments yield-how the ice forces develop against off- failure process ing to e.g. material separation or pileup.shore structures, how the shape of the The aim was to develop material mod- In this paper a laboratory-scale ice blockstructure should be optimised to mini- els to be suitable for describing the con- crushing experiment is simulated usingmize the loads or how the winter tyres tinuous failure. The main challenge was the presented approach. The numeri-should be designed to achieve prop- to model solid to crushed aggregate cal model was implemented into theer grip. The challenge is, among others, transition during the failure process as ABAQUS finite element software.the modelling of the crushed aggregate shown in Figure 1. The contribution of the depart-which is created in due to the materi- An advanced approach for the ment of the Applied Mechanics at theal failure and the accumulation of the modelling of ice-structure interaction Aalto University School of Science andcrushed material in front of the struc- was developed by VTT. In the proposed Technology is the preparation of a ma-ture. The understanding of these basic approach material behaviour and brit- terial model of ice and the implementa-phenomena can also be used to inten- tle failure is modelled using continuum tion of the derived material model intosify experimental research. The simula- damage mechanics (CDM). Crack prop- Abaqus finite element code. The materi-tion and modelling know-how can be agation path prediction is obtained al model describes the following mecha-applied widely also in other fields and from the CDM model and a model up- nisms of ice: Elastic distortion of ice crys-for other materials and in product de- date technique is utilized to propagate tals, grain boundary sliding causing for-velopment as well. the crack explicitly in the mesh. Explicit mation of microcrack nucleus, growth of cracks are created in the mesh by split- microcrack nucleus into microcracks andObjectives ting the damaged elements based on the influence of microcracks on the elas-The main objective of the project was the internal crack born inside the ele- tic properties of ice. The following newto develop and to adapt theoretical and ment. The crack propagation process innovations were developed in this task:numerical models for the ice failure and is modelled by dividing the analysis in- The influence of microcracks on the elas-the friction to be suitable for modelling to segments and updating the model tic properties is described in a more re-of the continuous failure. Both the finiteelement method (FEM) and discrete el-ement method (DEM) were developed Figure 1. Material transition from continuous to discontinuous in crushing.in the project. The numerical methodswere verified by comparing simulationresults and experiments. Developedsimulation tools can be used to simu-late ice loads against any 3D-structuresin different ice conditions. Some of thepotential users of the results are the off-shore industry, winter tyre manufactur- 105
    • alistic way as before. The internal varia- laboratory tests were compared with was the experimental part of this the- ble associated into microcracks is a vec- those predicted by the improved com- sis. Before finding the right ice making torial quantity having a clear physi- prehensive thermodynamic friction method which produced the desired cal meaning. Although in real physical model. The results show good qualita- ice properties many different meth- world the formation of microcracks is a tive agreement, but indicate that fur- ods were tested. Ice making methods discrete process (they are formed one ther improvements are required to ob- and the circumstances which affect the by one) the model describes the micro- tain accurate quantitative modelling ice properties are introduced. The chal- crack formation as a continuous proc- under all conditions. lenge was to produce ice on a surface ess in space and time. This allows to use The developed ice friction mod- which is not flat. In this thesis a method a more straightforward mathematical el was implemented into the commer- to melt ice of the drum surface without derivation and computational imple- cial ABAQUS element method soft- defreezing the whole cold room is in- mentation. The drawback of the mod- ware. This introduces the behaviour of troduced. el is that it takes much computational crushed ice powder into the compre- The friction between road and resources. To solve this problem is the hensive modelling of the total ice loads. rubber surface is greatly dependent on task of future projects. rubber properties. Rubber properties Experimental friction studies influencing road-rubber friction are in- Modelling of ice friction At Aalto University School of Science troduced. Also the friction components Friction of ice against ice is an impor- and Technology (previously Helsin- and the mechanisms of friction in road tant and poorly known factor in the ki University of Technology) in the re- and rubber interaction were studied. crushing process of ice. The friction co- search group for Vehicle Engineering efficient of ice varies between 0.005 the main task for 2009 was to complete Experimental study of and 0.8 depending mainly on the slid- development of measurement appa- ice failure process er material, sliding speed and temper- ratus called ice drum. This was done The influence of structural flexibility on ature. Due to this wide range estima- via Master’s Thesis project (Loponen, ice failure and ice load distribution was tion of ice friction calls for modelling 2009). The objective of this thesis was studied experimentally to introduce a of the frictional process. Previously de- to start up a small scale testing appara- verification case for the simulations. A veloped friction models have been de- tus for ice breaking and compare pow- new test set-up shown in Figure 2 was veloped further by improving the the- er rating data to mini-μ-road which is al- developed. The basic design of the oretical treatment particularly as it re- ready in use. loading frame and instrumentation was lates to contact mechanics and friction It is very important for reliable lab- done by Insto Lujari Oy. The device ena- of ice on ice. Related background work oratory measurement results that the bled a simple way to change the struc- has also been made in order to under- properties of the ice sample are ho- tural stiffness in ice contact. The chas- stand better the stress state of a surface mogenous and the production proc- sis of the test equipment was manu- and microstructure of growing ice (Bot- ess has good reproducibility. A litera- factured by Technip Offshore Finland tomley et al. 2009, Makkonen 2010a) ture study concerning the properties Oy. The instrumentation of strain gaug- A laboratory study was planned at of water and ice was done. The knowl- es and tactile sensors was done by VTT. VTT and measurement on ice-ice fric- edge on the molecular properties of The operating staff and the test facilities tion made under various sliding veloc- water helps to understand ice forma- were provided by Aker Arctic who also ities, normal forces and temperatures tion process and its properties. The lit- was responsible for ice sample manu- by the Vehicle Engineering at the Aalto erature showed that the properties facturing and preparation. This joined University School of Science and Tech- of ice depend greatly on the prevail- coalition did several successful and nology in a cold room using the modi- ing conditions. Ice making process on promising ice crushing tests for the ice fied “mini-µ-road” device. The ice-on-ice the testing apparatus in cold chamber blocks with different speeds.106
    • Figure 2. At left: Photograph of test set-up in ice crushing experiment. Ice block is pushed left against the vertical wall. At right:Pressure and force distributions in ice-structure interaction measured and analyzed by Tekscan Tactile Pressure System.Simulation of ice crushing date procedure applied to simulation crete element method (DEM) has beenexperiment of pushing an ice block against a ver- developed (Polojärvi & Tuhkuri, 2009). tical structure produces a similar failure Within the MASI programme, theThe model update procedure com- shape as described in literature and de- method has been applied to the anal-bined with damage mechanics consti- picted in Figure 1. Ice near the contact ysis of the interaction between uncon-tutive modelling of ice failure was uti- region is broken into rubble and flows solidated ice rubble and a conical ma-lized in simulating ice crushing exper- vertically on both sides of the block. Al- rine structure. Figure 4 shows an exam-iment. Numerical model represents a so two larger separated blocks can be ple of a simulation run (Haase, Polojärvithin sheet from the middle of the actu- observed. In the last snapshot of Figure & Tuhkuri 2010). The simulation meth-al specimen. The vertical plate and sup- 3 the intact region of the block is in con- od allows analysis of the failure processport plates on both sides of the block tact with the structure and similar fail- of the ice rubble and ice loads on theare modelled with rigidity much high- ure process would commence again. structure.er than that of the ice block. Effectsof water buoyancy and gravity are in- Discrete element modelling International cooperationcluded in the model. Ice block is thick- At the Department of Applied Mechan- Dr. Jaakko Heinonen accomplished re-ness in the simulation is 20 cm with a ics of the Aalto University, ice loads on searcher exchange in Fraunhofer IWMslight wedge shape towards the end in structures caused by ice ridges and ice in Germany (The Fraunhofer Institutecontact with the structure. The block is rubble, have been studied by modelling for Mechanics of Materials).pushed horizontally against the rigid- the ice features as discontinuous media. Docent Lasse Makkonen acted inlike wall at a velocity of 15 cm/s. Plane When rubble is assumed to be discon- December 2008 as an Opponent for astrain state is achieved by constraining tinuous, the deformation of the rubble Ph.D. Thesis “Runway operability in arc-the model in the second horizontal di- pile becomes modelled through dis- tic conditions” by A. Klein-Paste at therection. Figure 3 shows snapshots of placements of the individual ice blocks Technical University of Norway, Trond-the crushing simulation. The model up- within it. For this modelling, a 3D dis- heim. 107
    • Figure 3. Snapshots of the ice block crushing simulation. Colour indicates amount of damage blue being zero damage and red being fully damaged. Elements that have completely detached are shown as white. Publications Haase, A., Polojärvi, A. & Tuhkuri, J. Heinonen, J. & Schmidt, J. Analysis of the Bottomley, D.J., Makkonen, L. & Kolari 3D Discrete Numerical Modelling Stress State in a Green Part During K. 2009. Incompatibility of the of Conical Structure-Ice Rubble Ejection from the Die, EURO PM2009, Shuttleworth equation with Interaction. Submitted to the 12–14 October 2009, Copenhagen, Hermann’s mathematical structure of proceedings of the 20th IAHR Denmark. thermodynamics. Surface Science 603, International Symposium on Ice, Lahti, 97–104. Finland, June 2010.108
    • Figure 4. Snapshot of a discrete element simulation, where ice rubble is moving from Project time scaleleft to right and interacting with a conical marine structure. Scale of the box is in 1.1.2008–30.6.2010meters. Colour code shows the normalised velocity v of the ice blocks; v=1 is the farfield velocity of the ice rubble. Project volume Total funding 655 600 €, Tekes share 400 000 € Other sponsors: Nokian Renkaat Oyj, Fortum Heat and Power Oy, Aker Arctic Technology Oy, Technip Offshore Finland Oy, Finnish Maritime Administration Project participants • VTT Technical Research Centre of Finland, Structural Performance Knowledge Center (coordinator) • Vehicle Engineering at the Aalto University School of Science and Technology (previously Helsinki University of Technology) • Applied Mechanics at the Aalto University School of Science and TechnologyKolari, K., Kuutti, J. & Kurkela, J. 2009. FE- Makkonen, L. 2010a. Solid fraction in Contact information Simulation of Continuous Ice Failure dendritic solidification of a liquid. Jaakko Heinonen Based on Model Update Technique. Applied Physics Letters (accepted, in VTT Technical Research Centre of Finland Proceedings, 20th International press). Tel. +358 20 722 6907 Conference on Port and Ocean Makkonen, L. 2010b. Ice adhesion jaakko.heinonen@vtt.fi Engineering under Arctic Conditions – theory, measurements and http://strutsi.vtt.fi (POAC), Luleå, Sweden. countermeasures. Journal of AdhesionKuutti, J. & Kolari, K. Simulation of Ice Science and Technology (submitted Crushing Experiment Using Fe- upon invitation). model Update Technique, Submitted Polojärvi, A. & Tuhkuri, J. 2009. 3D discrete to the proceedings of the 20th IAHR numerical modelling of ridge keel International Symposium on Ice, Lahti, punch through tests. Cold Regions Finland, June 2010. Science and Technology, 56: 18–29.Loponen, M. 2009. Pienimittakaavaisen jään lujuustestauslaitteiston käyttöönotto. Master’s Thesis (in Finnish). Helsinki University of Technology. 109
    • Automatic testing of control systems in the integration phase of intelligent mobile machines (TINAT) – MASIT31 Background Objectives tor based testing of control systems. A The level of automation and built-in in- Based on industrial and academic comprehensive survey was also carried telligence of mobile work machines in- needs the following objectives were out to determine the requirements and creases continuously. Control systems set to the development of control sys- restrictions set by legislation and stand- and their software are key components tem testing in TINAT project: ards for the use of HIL-simulation to ver- in the development and operation of • Development of concept and test ify the compliance of control systems. modern mobile work machines. They system to enable automatic test- Work Package 2: Development of enable in addition to the basic opera- ing of entire control systems of in- concept and test system for automat- tion of machine for example the per- telligent mobile work machines ic testing of control systems. In WP2 a forming of fully or partly autonomous without mechanical structures of modular concept and the interfaces tasks and the monitoring and diagno- machines by utilizing HIL-simula- between different modules for the test sis of machine operation and condition. tion. system were defined. The functionali- Thus new characteristics and improve- • Definition of a modular test sys- ty of test system was verified in sever- ments to performance are mainly real- tem structure and its components al technology demonstrations. Devel- ized through the development of con- (HW and SW) that can be easily oped and tested functions included trol system. Work machines are in this adapted to different types of ma- test administration, test sequence def- context for example forestry harvest- chines and their subsystems. inition in simulator environment and ers, rock drilling machines, cranes, fork- • Development of methods to de- analysis of test results. lifts and excavators. scribe operating conditions and Work Package 3: Industrial case stud- Currently the testing of control sys- fault conditions of real machines ies. In WP3 two case studies were car- tems and verification of their properties in simulator environment. ried out. In case 1 the wiring of the con- poses a major challenge to the manu- • Development of methods to sup- trol system of Sandvik loader was test- facturers due to the following proper- port the analysis and visualization ed. In case 2 the control system of au- ties: of test data. tonomous GIM machine was tested in • The distributed structure of con- • Development of meters for the a test environment, which enabled al- trol system and large number of evaluation of test acceptance in so the use of fault injection methods. independent subsystems with simulator environment. This WP included the following tasks: embedded software. the set up of two test systems, integra- • The large number of controlled Project implementation tion of control systems, the coding of machine functions and connected Work Package 1: Procedures, require- needed real-time simulation models components (e.g. sensors, actua- ments and challenges related to control and test drives. tors and devices of control panel). system testing. In WP1 the current pro- • The extent and complexity of cedures and needs of manufacturers of Results control software. The software of mobile machines and application pro- Summary of main results: modern work machine may con- viders were determined by interview- • Report: Software, hardware and tain millions of rows of code. ing numerous company experts. Liter- application providers for the test- ature and market reviews were carried ing of control systems. The content and objectives of TINAT out to define the current status of soft- • Report: HIL in regards to safety project was defined in close co-opera- ware and hardware products, and ap- regulations of control systems. tion with the companies of FIMA (Fo- plication providers on the market sup- • Industrial requirements for the rum for Intelligent Machines). porting or enabling automatic simula- testing of control systems.110
    • • Concept for automatic testing of Figure 1. Concept for automatic simulator based testing of control systems. control systems. (Hyvönen et al. 2009)• Technology demonstrations for the proof of concept. Administration for tests• Methods for the test administra- – Definition of test cases, database tion, definition of test sequences – Generation of test sequences and analysis of test results in a sim- – Definition of data collection ulator environment. – Database for stored data – Report generation• Industrial case studies: 1) Control system wiring of Sandvik loader 2) Control system operation of au- tonomous GIM machine and fault Controlling of test operation Analysis and visualization injection. of test data – Loading of simulation models to• Research exchange visit to RWTH real-time PC’s – Data retrieval from database Aachen University. – Data recording – Filtering – Test sequence control – Data analysis, transfer to databaseIn Figure 1 are presented the main partsof the concept, their interaction and al-so the functions of each part. In Figure 2 is presented the sche- Real-time operation of testsmatic structure of possible hardware – Simulation in real time Real control systemsolution for the test system. – Data collection In Figure 2 computer 1 is for up-per level control of the simulation sys-tem and it provides administration, testplan, control and analysis software’s.Computer 2 provides an interface to Figure 2. Example of simulator structure for automatic testing of control systems.the real control system. Depending on (Multanen et al. 2009)the application, several types of hard-ware cards can be connected to it. Incomputer 3 dynamic real-time simula-tion models of machine are performed.The hard real-time execution unit canconsists of several (1…n) standard PCsconnected through a local area net-work (LAN). The distribution of simula-tion models to parallel PCs enables ef-fective simulation of large systems in re-al-time. (Multanen et al. 2008)ImpactsResults of the TINAT project can be ex-ploited widely within the manufactur-ing companies of mobile machines andthe developers of their control systems. 111
    • The automatic testing by utilizing HIL- Publications Project volume simulation will improve the efficiency Hyvönen, M., Multanen, P., Mantere, P., Total 600 000 €, Tekes share 450 000 € and reliability of control system testing. Kolu, A., Vallas, A., Alanen, J. & Rantala, This will make the development of new S. Towards Automatic Testing of Project participants characteristics more efficient and also Control Systems for Intelligent Mobile • Tampere University of Technology, IHA the testing work becomes more mo- Machines. The 11th Scandinavian • Tampere University of Technology, MEC tivating and safe. The concept will be International Conference on Fluid • VTT Technical Research Centre of utilized also in academic research with- Power, Linköping, Sweden, 2–4 June Finland in GIM-project (Generic Intelligent Ma- 2009. Linköping University. 12 p. chines). Multanen, P., Hyvönen, M., Saarinen, J. Contact information & Vilenius, M. 2008. Dynamic real- Petteri Multanen International cooperation time simulation of intelligent mobile Tampere University of Technology, IHA During the TINAT project research ex- machines. Proc. of the 27th IASTED Tel. +358 50 599 4329 change visit was made to Institut für International Conference of Modelling, petteri.multanen@tut.fi Kraftfahrzeuge in the RWTH Aachen Identification, and Control. February www.iha.tut.fi University in Germany. 11–13, Innsbruck, Austria. 6 p. Seppo Rantala Dissemination Project time scale VTT Technical Research Centre of Finland Project and its results were disseminat- 1.1.2008–31.12.2009 Tel. +358 40 501 5816 ed in several national seminars and in seppo.rantala@vtt.fi the design theme group of FIMA. The results were also promoted in two in- ternational conferences.112
    • Design and modelling of printable electronics applications (DEMOprint) – MASIT32Background • Gain expertise in printable with thermogravimetry (TG) and differ-Future electronics manufacturing proc- electronics design and modelling ential scanning calorimetry (DSC) andess will consist of a single flexible pro- (materials, design tools) an improved sintering process was de-duction line utilizing a direct-depo- • Application of knowledge gained veloped in co-operation with PRINTsition technique such as printing. The to practical printable electronics project. The suitability of radio-fre-technology allows fast implementation design tasks quency (RF) circuit simulation softwareof modifications to the manufacturing AWR Microwave Office (MO) and elec-process, enabling rapid customization Project implementation tromagnetic (EM) simulator CST Micro-of the products for the consumers or The project concentrated on charac- wave Studio (MWS) for printable elec-change to another product. To fulfil the terization and modelling of printable tronics design were evaluated. A char-potential of the technology, the design electronics materials and structures. A acterization-based design approach forprocess to implement the changes to wide-band electrical characterization critical printable high-frequency ap-the products must match the speed test setup was developed and applied plications was developed. As a practi-and versatility of the manufacturing to printable electronics materials (Fig- cal design application, antenna feed in-process. To aid the printable electron- ure 2). Electrical characterization was cluding antenna placement and match-ics design process, a characterization complemented scanning-electron mi- ing circuit were designed for a printabletest setup for printable electronics ma- croscope (SEM) and profilometer anal- wrist application (Figure 3). Also print-terials was developed, material proper- ysis. In addition, sintering behaviour of able antennas for wrist environmentties were determined, and the suitabili- silver nano-particle inks was studied were developed (Figure 4).ty of design tools for printable electron-ics was evaluated. Figure 1. iTi XY MDS 2.0 pilot line / R&D inkjet system at TUT/ELE.ObjectivesThe main goal of the project is to gainprintable electronics design exper-tise and to establish design guidelinesfor printable electronics. These includetypical material properties of printa-ble materials and design and analysisof basic structures in modern consum-er electronics applications includinghigh-speed interconnections, RF signalpaths, and printable antennas for wire-less applications. The objectives of theproject:• Develop characterization test setup for printable electronics materials and structures 113
    • Figure 2. Determination of high-frequency conductivity by fitting simulation terization test setup developed in the data to characterization results. Inset: measurement test coupon. project. The test procedure can be uti- lized in manufacturing process devel- opment as well as evaluation of new materials and process parameters for them. Knowledge of dimensions for the basic structures in modern consumer electronics applications including high- speed interconnections, RF signal paths and printable antennas for wireless ap- plications was gained. Antenna feed and matching circuit was designed for printable wireless wrist application. The expertise gained in the project can be exploited to successfully design printa- ble electronics applications. Impacts The project provided fundamental in- formation on electrical characterization, modelling, and design of printable elec- Results of commercial design and modelling tronics. The expertise gained assists in As a result of the project, printable tools were evaluated. Typical material the design of novel product concepts electronics design expertise and de- properties of printable materials with based on new technology. sign guidelines for printable electronics the emphasis on nano-particle conduc- were gained. Limitations and strengths tors were established using the charac- Figure 3. Wrist application developed in the PRINT project at Figure 4. Inkjet-printed antenna and artificial hand model in TUT/ELE. The inkjet-printed antenna balun/matching circuit Satimo Starlab measurement system at UO/MIC. designed in DEMOprint is shown in the white box.114
    • International cooperation Mäkinen, R., Sillanpää, H., Östman, K., Application of wide-band materialInstitut für Theorie Elektromagnetischer Palukuru, V., Pynttäri, V., Kanerva, T., parameter extraction techniques toFelder (TEMF), Technische Universität Hagberg, J., Lepistö, T. & Jantunen, H. printable electronics characteriza-Darmstadt (TUD), Darmstadt, Germany, 2009. Application of Jacobi-Davidson tion. 59th Electronic Components and1.9.–30.11.2007 algorithm to 2-D eigenmode problems Technology Conf., San Diego, CA, p. Conductor loss of inkjet-print- in printable electronics. Proc. Int. Conf. 1342–1348.ed nano-particle conductors needs to on Electromagnetics in Advanced Sillanpää, H., Pynttäri, V., Palukuru, V.,be considered in printable electronics Applications (ICEAA 2009), Turin, Italy, Östman, K., Hagberg, J., Kanerva, T.,modelling and design. The researcher p. 122–125. Jantunen, H., Lepistö, T., Mäntysalo,visit by Dr. R. Mäkinen (TUT/ELE) con- Östman, K. 2009. Sintering of silver M. & Mäkinen, R. 2009. Design andcentrated on modelling of conductor nanoparticle inks for printable modeling approach for critical RF partsloss in time-domain EM simulations. electronics. M. Sc. Thesis, Tampere in printable electronics applications. University of Technology. Proc. IMAPS ATW Printed Devices andPublications Palukuru, V., Pekonen, A., Pynttäri, V., Applications, Orlando, FL, 4 p. The bestSummary of essential publications Mäkinen, R., Hagberg, J. & Jantunen, student paper award.Lilja, J. 2009. Application of a modern H. 2009. An inkjet-printed inverted-F modeling environment for printable antenna for 2.4 GHz wrist applications. Project time scale electronics design. M. Sc. Thesis, Microwave Opt. Technol. Lett., Vol. 51, 1.1.2008–30.6.2009 Tampere University of Technology. No. 12, p. 2936–2938.Lilja, J., Mäkinen, R., Pynttäri, V., Pekonen, A. 2008. Printable antennas for Project volume Mansikkamäki, P. & Kivikoski, M. 2.4 GHz wrist application. M. Sc. Thesis, Total 354 196 €, Tekes share 329 196 € 2008. Application of thin-film RCLG University of Oulu. model for the modeling of inkjet Pynttäri, V., Mäkinen, R., Lilja, J., Pekkanen, Project participants printed microstrip lines. 12th IEEE V., Mansikkamäki, P. & Kivikoski, M. • Tampere University of Technology, Workshop on Signal Propagation on 2008. Significance of conductivity Department of Electronics Interconnects, Avignon, France, 4 p. and thickness of thin inkjet printed • University of Oulu, Microelectronics andLilja, J., Sillanpää, H., Mäkinen, R., microstrip lines. 12th IEEE Workshop Material Physics Laboratories Palukuru, V., Östman, K., Hagberg, on Signal Propagat. on Interconnects, • Tampere University of Technology, J., Kanerva, T., Lepistö, T., Jantunen, Avignon, France, 4 p. Department of Materials Sciences H. & Mansikkamäki, P. 2009. Wide- Pynttäri, V., Mäkinen, R., Palukuru, V., • AWR-APLAC band characterization of printable Östman, K., Sillanpää, H., Kanerva, T., • Elektrobit electronics materials: the effect of Lepistö, T., Hagberg, J. & Jantunen, H. • Nokia Research Center conductor loss and internal inductance Application of wide-band material • Suunto on relative permittivity. Proc. European characterization methods to printable Conf. on Antennas and Propagat., electronics. IEEE Trans. Electronics Contact information Berlin, Germany, p. 3869–3873. Packaging Manufacturing, (accepted). Dr. Riku MäkinenMäkinen, R., Sillanpää, H., Östman, K., Sillanpää, H. 2009. Wide-band electrical TTY-säätiö (TUT Foundation), Department Palukuru, V., Pynttäri, V., Kanerva, T., material characterization in printable of Electronics Hagberg, J., Lepistö, T., Jantunen, H., electronics with application to radio- Tel. +358 40 849 0087 Yang, M., Laxton, P., Arimura, H. & frequency design. M. Sc. Thesis, riku.makinen@tut.fi Rönkkä, R. 2009. Wide-band electrical Tampere University of Technology. characterization of printable nano- Sillanpää, H., Lilja, J., Mäkinen, R., Östman, particle copper conductors. Proc. Asia- K., Palukuru, V., Virtanen, J., Pynttäri, Pacific Microwave Conf. (APMC 2009), V., Kanerva, T., Hagberg, J., Lepistö, T., Singapore, p. 2455–2458. Jantunen, H. & Mansikkamäki, P. 2009. 115
    • Industrial application of PhaseField modelling – MASIT33 Background Another advantage of phase field Objectives The phase field method is current- models is that they are physically mo- The phase field project will develop a ly considered the state-of-the-art ap- tivated from a thermodynamic free en- novel paradigm for integrating knowl- proach to modelling phase transforma- ergy. In other words, phase field mod- edge generated from basic fundamen- tion problems, especially solidification. els are thermodynamically consist- tal research into new industrial software It is used by several groups in the US ent models in the sense that the gen- that will be used to better understand, and Germany and Switzerland for in- eralized free energy, which appears as design, optimize and operate the man- dustrial applications in steel and alu- the generator of the dynamics, will in ufacturing processes in industry. At the minium manufacturing. In the power the course of the time evolution try heart of this goal lies in the quintessen- industry and more generally in mod- to reach its minimum value consist- tial problem of being able to generate elling of industrial flow problems the ent with traditional equilibrium ther- and then self-consistently link together phase field method are not nearly as modynamics. The generalized free en- – in an efficient manner – information commonly known as various volume ergy contains the necessary informa- across multiple length and time scales. averaged fluid dynamics models such tion about the microscopic physics re- To do this requires new mathematical as the ones used in oil extraction or hy- quired to reproduce various phenom- models of physical processes, innova- draulic networks. The reason for this ena on larger, hydrodynamic time and tions in multi-scale numerical meth- primarily derives from the fact that the length scales important for the industri- ods, as well as an entirely new software diffuse interface methods such as the al applications. For example, for solidifi- technological approach for the process phase field technique have not yet had cation problems it is possible to include modelling and simulation platform that enough time to propagate from the such relevant phenomena as the equi- will be able to interface with these new more fundamental physics research to librium interface partitioning and phase approaches. The team members assem- the applied engineering world. thermodynamics at low undercooling. bled in the project have recently made One of the main advantages of the Even at high undercooling it has recent- innovations in all these key areas. phase field method is that it allows one ly become possible to model the solute The viability and versatility of the to model numerically complicated mul- drag and solute trapping due to a finite new modelling approach will be dem- ti-phase flow and phase transformation interface width between the different onstrated by prototyping it in three dynamics without the need for tracking phases of the solidifying material. specific areas of industrial modelling: the position of the phase boundaries. Owing to the thermodynamic con- in power generation, quality control in Already in two spatial dimensions the sistency built into the phase field mod- steel sheet manufacturing and in mod- front tracking makes the solution of the els they can be easily coupled with ther- elling of layered casts in polymer indus- Navier-Stokes equations for a liquid-gas modynamic (equilibrium) databases try. These test cases have been identified flow very difficult if one tries to explicitly such as CalPhad, Dictra and the kinds on the basis of the significant amount of impose the appropriate boundary con- of databases that are developed at Met- work on multi-scale modelling and proc- ditions, e.g. the pressure jump, at the allurgy Laboratory of TKK. Hence the ex- ess simulation software that has already extremely convoluted phase bound- perimentally known equilibrium phase been developed by the present research aries of two-phase flow. For the same diagrams can be readily made use of team. The project will be used also as an reason numerical simulations of large in the construction of the dynamical instrument to disseminate information scale solidification become problemat- phase field model describing the relax- about phase field method to the Finn- ic without a method that frees the user ation towards this equilibrium state. ish research community both in univer- from explicit front tracking. sities and in industry.116
    • Project implementation Results of the research they are associated with.The project was divided in six work General On the other hand, the industrial part-packages: The three major results produced dur- ners will be granted an access to a sim-1. Applying PhaseFields in steel ing the project are: ple-to-use web-based environment for industry (1) a data bank method for practi- utilizing the results produced by re-2. Applying PhaseFields for multi- cal multi-scale modelling; (2) interfac- search institutes and universities. phase process metallurgy/ ing of the data banks and solidification Let us comment the result (1) in chemistry simulators with the Simantics platform, more detail. Data banks are not new, of3. Applying PhaseFields in the which allows industrial operators to course, but what is new is the way they power industry easily view and compare the results of are produced in this project. Traditionally,4. Modelling of crystallization of simulation based microstructure anal- data banks (look-up tables, fitting forms, layered casts in polymer industry ysis with experimentally performed etc.) are produced by experimental5. Modelling and simulation measurements (Figure 1); (3) construc- measurements. In this project they were framework tion of a new web environment for com- produced by computer simulation. The6. Management, coordination and municating results of any project dealing information content of the microscopic dissemination with numerical simulations to decision level simulations can be packaged into makers and industrial partners. This new a data bank, which can be used just likeGoals method has the potential to revolution- an experimental data bank, as a look-upWork packages 1, 2 and 5: Develop cast- ize the communication of the research table providing information for the largeing simulator that predicts the effect achievements for the industrial collabo- scale analysis. During the project it be-of the microstructure of crystallized rators in a more intuitive and more con- came clear that the construction of themelt on the large scale properties of crete way as before. Institutions, such as data banks is essential for all the workthe cast as a function of the process VTT can utilize the framework both in packages (WP1 and WP4 in particular).parameters. the communication of the results and Otherwise it had not been possible to Work packages 3 and 5: Devise a in demonstrating the policy relevance satisfy the requirement of real time in-method which allows packing dynam- formation passing between the microic 3D fluid flow information from a fine- Figure 1. Solidifying dendrites. and the macro level models.ly structured grid on a coarse-grained As a summary, the data banksone, which ultimately can be reduced for solidification (WP1) are formed byto a 1D pipe flow solver. Interface the PhaseField simulations on small scales,Open Source CFD solver OpenFOAM and they can now be simply visualized,with Simantics platform for direct 3D browsed and computed using an easy-flow simulations. to-use web interface produced in the Work package 4: Develop a mul- project. In order to make the process asti-scale model that will communicate automatic as possible, a lot work has al-information from a new microscopic so been invested in the areas of improv-PhaseField model describing the solid- ing the numerical stability of the phaseification of polymer melt into a macro- field solvers and their efficiency. Thescopic scale viscous polymer flow solv- fruits of this work are now at the dis-er (CAD-MOULD). Perform case study posal of the industrial project partnerson the effect of the microstructure on through a web interface, which utilizesreleased latent heat to be used on the the Simantics platform. The data banklarge scale flow solvers. production is also essential for WP4 where we have performed a feasibility 117
    • study showing the benefits of the data gy for the 2-component alloy model (Ref. el and (Redlich-Kister-Muggianu poly- bank philosophy (Ref. 6) for large scale 2). In the process we have utilized some nomial). Besides interfacial tension and polymer injection moulding. The data of the results produced in WP2 (Surfer de- equilibrium composition, surfer can be bank in this case gives the latent heat velopment), which allowed us to bench- used to calculate several state variables of solidfication needed for the macro- mark our results. Surfer development is that can be derived from the Gibbs en- scopic solver in terms of the spherulit- described in more detailed in the next ergy (entropy, enthalpy, heat capacity). ic seed density, macroscopic melt flow section. Also, in collaboration with the These can be calculated for the whole velocity, and the local undercooling. McMaster group a new PhaseField mod- system, selected phase(s) and/or select- Once these parameters are fed into the el has been developed (Ref. 10) which ed phase constituent(s). data bank, the latent heat of solidifica- enables the numerical modelling of vary- tion, whose calculation is performed us- ing grain orientation. Moreover, new nu- Work packages 3 and 5 (specific results) ing the microscopic PhaseField model, merical solution methods that reduce the can be obtained for the next time step computation time of PhaseField models We have developed a novel coarse- of the macroscopic (CAD-MOULD) sim- substantially have been developed. All graining method for flows in restricted ulation. A data bank can also be formed these achievements will now be available geometry (e.g. pipes in power plants) for the purposes of WP3. In this case the for our industrial partners among others, based on the so-called maximum in- parameters utilized by a macroscopic 1D through the user environment and web formation entropy approach. Coarse- flow solver, which is derived from a mi- interface which has been developed in graining of the flow means that we croscopic 3D PhaseField model for two- the project. It enables the visualization of want to device a technique that allows phase flow, will depend on the geome- the contents of the data bank, the auto- us to use many fewer grid points to de- try of the tube element as well as on the mated generation of the data bank, and scribe the flow than in the original mi- boundary conditions of the flow at the the usage of the microscopic PhaseField croscopic model while at the same time boundaries of the element. In WP3, the solvers over the internet without prior we must keep the overall features of the time constraints did not allow us to take knowledge of the physics, numerical or flow intact. The results derived in WP3 the exercise as far as the actual construc- information theoretical intricacies. The so- can be used as a basis for further devel- tion of a working data bank. This is be- lution works on top of the Simantics inte- opments for coarse-graining of gener- cause other hurdles in the coarse-grain- gration platform. al flow problems. We have used the Fi- ing process itself needed to be removed In WP2 we have developed Surf- nite Element technique to demonstrate first, as we emphasized in the original er thermodynamic library contains rou- the general features and the feasibility action plan, and as will be explained in tines to calculate interfacial tension of of the methodology. Analytical results Work packages 3 and 5 (specific results). multi-component gas/liquid and gas/ have also been obtained by using a solid (surface tension) systems as well as control volume method which works Work packages 1, 2 and 5 interfacial tension of multi-component better for numerical implementation. (specific results) liquid/liquid system. The needed inputs A modified control volume method for Microscopic PhaseField simulations are the standard Gibbs energies, surface the coarse-graining of flow solvers has need some parameters that can be tak- tensions and molar volumes of pure spe- been presented in the internal report en in some cases from experimental da- cies as well as binary interaction terms for (Ref. 7). Our analytical scheme is com- ta banks, or they can be derived theoret- the excess Gibbs energies of the phases patible with numerical OpenFOAM- ically. One of these important input pa- in question. All these are temperature type solvers. It enables a direct com- rameters is the surface tension between dependent equations. Surfer also con- parison with the finer and the coarser the various phases present in the prob- tains Gibbs energy minimization routine scale descriptions with mapping for nu- lem. We have derived theoretically the to solve the equilibrium composition of merical values of parameters (e.g what form of the surface tension tensor for an- multi-component, multi-phase system. is the viscous dissipation on a coars- isotropic crystallized pure material (Ref. 1) Currently supported excess models are er grid based on the viscous dissipa- as well as the form of the interfacial ener- ideal mixing and regular solution mod- tion known on the finer grid). In the fu-118
    • ture work we will consider the ultimate International cooperation Formation in Polymer Casting.limit of dimensional reduction from 3D The original developer of the PFC-mod- Technische Mechanik, to be published.to 1D, which was still left open at this el, Professor Ken Elder from the Oakland 7. Laurila, T. 2009. Notes on phase-field/stage. One of our more theoretical re- University, visited Finland two times diffuse interface model for liquid-gassults presented in the internal report during the project. Professor Niko- flows with phase transfer and finite Re.indicates the necessity of further the- las Provatas from McMaster Universi- Internal project report.oretical studies if stable and controlled ty spent two months as a visiting pro- 8. Kortelainen, J. 2009. Meshing Tools3D to 1D reduction scheme is to be de- fessor at VTT during the project. Two for Open Source CFD – A Practicalrived. A controlled approximation in the graduate students of Professor Provatas Point of View. VTT Research Reportcoarse-graining process is necessary joined the visits. Three members of the VTT-R-02440-09.for a seamless interfacing of 3D solvers project team from VTT and TKK visited 9. Gayer, M. & Karhela, T. 2010. CFD(such as OpenFOAM) and more macro- McMasters University several times dur- modelling as integrated part of multi-scopic 1D solvers (such as APROS). ing the project. Collaboration with the level simulation of process plants. SCS In parallel with the more theo- Simcon Gmbh from Germany was done 2010 Summer Simulation Conferenceretical work a direct integration of the in the polymer work package. (submitted).OpenFOAM solver into the Simantics 10. Ofori Opoku, N. & Provatas, N. 2009. Aplatform has been performed. Detailed Publications Quantitative Multi-Phase Field Modelstudy on the open source mesh gener- Summary of essential publications of Poly-crystalline Alloy Solidification,ators was carried out (Ref. 8). Further- produced in the project In Press, Acta. Materiala.more a prototype of the integration of 1. Majaniemi, S. & Provatas, N. 2009.OpenFoam to Simantics platform was Deriving surface-energy anisotropy Project time scalecarried out (Ref. 9) for phenomenological phase-field 1.1.2008–30.4.2010 models of solidification, Phys. Rev. EWork package 4 (specific results) 79, 011607. Project volumeWe have developed a data bank ap- 2. Provatas, N. & Majaniemi, S. A Total 737 000 €, Tekes share 600 000 €proach to the multi-scale modelling of Phase Field Crystal Approach forinjection moulding of polymer melts. Approximating Interface Energy in Project participantsThe data bank has been tested for a sim- Binary Alloys. Preprint 2010. • VTT Technical Research Centre of Finlandple parametrization which includes the 3. Tegze, G., Gránásy, L., Tóth, G. I., • Helsinki University of Technologyeffects of seed density, injection flow Podmaniczky, F., Jaatinen, A., Ala- • McMaster Universityvelocity and supersaturation on the la- Nissila T. & Pusztai, T. 2009. Diffusion- • Fortumtent heat production from a microscop- Controlled Anisotropic Growth • Outokumpuic PhaseField model. For a more com- of Stable and Metastable Crystal • Rautaruukkiplete parametrization a more systemat- Polymorphs in the Phase-Field Crystal • Ovakoic study is needed but we have already Model Phys. Rev. Lett. 103, 035702. • Luvatabeen able to establish certain universal 4. Jaatinen, A., Achim, C. V., Elder, K. R. & • Elastopoliscaling features with the simple model Ala-Nissila, T. 2009. Thermodynamicsused. For example, large enough initial of bcc metals in phase-field-crystal Contact informationseed density of spherulites will render models Phys. Rev. E 80, 031602. Tommi Karhelalatent heat production rate independ- 5. Jaatinen, A., Achim, C. V., Elder, K. R. & VTT Technical Research Centre of Finlandent of the velocity, which decreases the Ala-Nissila T. Phase Field Crystal Study Tel. +358 20 7226 246size of the data bank. In future work, we of Symmetric Tilt Grain Boundaries of tommi.karhela@vtt.fiwill also study other possibilities of re- Iron Technische Mechanik (submitted). http://www.vtt.fi/research/technology/ducing the size of the data bank, includ- 6. Pikänen, T., Majaniemi, S. & Ala-Nissilä, T. simulation_optimisation_and_manag_ing scaling functions. Multiscale Modelling of Microstructure of_ind_inf_contents.jsp?lang=en 119
    • Qualitative methods in virtual design of machines (KVALIVE) – MASIT34 Background types through virtual interfaces by hap- • To build a pilot simulator for se- Human-machine interaction has been tic tools. The test users get the feedback lected mobile machine including under intensive research during the from the machine dynamics by a mo- virtual interface, process visualiza- last decades. The drawback of existing tion base. This makes it possible to use tion, real-time machine simulator research environments is that the real human centered design through the and motion base. The pilot simu- products or their physical prototypes whole R&D process. It also combines in- lator is used to collect user expe- are needed in order to carry out tests terface and cabin design with more tra- riences when driving the pilot ma- with real human users. It is then expen- ditional machine design which makes it chine with optional interface and sive and slow to carry out modifica- possible to approximate human effect constructional solutions. tions leading to better usability and us- in the machine durability, energy con- er comfort and, on the other hand, bet- sumption, etc., and in reverse the effect Project implementation ter durability, lower energy consump- of machine dynamics and ergonomics The load hauling machine (LHD) sim- tion etc. There are some immersive vir- in human operators. ulator developed for Sandvik Mining tual environments for visualizing cab- The sub-goals of the project to be and Construction Oy was utilized in ins and user-interfaces, but in those carried out can be listed as follows: the project. The simulator was deliv- systems, it is hard for the test persons • To develop existing virtual envi- ered to LUT, TUT and VTT to be used in to figure out the real functionality and ronments such that it is possible their virtual environments. The simula- constraints of the cabin and interface. In to connect the test user and the tor was successfully implemented and addition to this it is hardly possible for virtual user interface by haptic de- the environments developed during a test person to practise realistic work vices. A generic library based vir- the project. All research partners used cycles to be carried out by the real ma- tual interface simulator is devel- Dassault VIRTools-program for 3-screen chine. A user interface that looks good oped. The library includes com- visualization of the LHD-machine and and ergonomic is not necessarily that monly used control devices such working environment. LUT used 6-DOF when performing the work to be car- as steering wheels, joysticks but- electrical motion platform to repeat the ried out by the machine which is to be tons etc. and monitoring devices machine motions calculated by the re- constructed. such as PC-panels, lamps, leds, etc. al-time simulator for the driver’s seat. • To carry out further develop- TUT developed 6-DOF Stewart platform Objectives ments in existing real-time simu- type of motion base using pneumatic The project proposes novel methods lation algorithms, models, solvers muscle actuators. Also 3-D sound envi- and tools for R&D of human operated and software to intensify the quick ronments were implemented in the all multi-technical machines. The methods construction of models for multi- simulators. Two user tests were carried utilize tools such as real-time simulation, technical machines such as con- out during the project firstly in Sandvik visualization, haptics and motion bas- tainer handling machines, wheel factory in Turku and secondly, in TUT es. Real-time simulation has traditionally loaders, forestry machines, etc. Tampere. Experienced test drivers were been used in user training simulators of • To develop low cost motion base used. The first tests were carried out various machines and testing of control technology based on pneumat- without motion base while in the sec- hardware. The project attempts to take ic muscles and low cost electrical ond tests the pneumatic Stewart Plat- a significant step towards a R&D sys- actuators. The filtering and con- form was used. In addition to previous- tem in which the test drivers are able to trol methods are also developed ly mentioned technologies in LUT, the participate the R&D process by operat- to improve the platform motion usability of a haptic mechanism in con- ing dynamically adequate virtual proto- capabilities. trol of the loader’s bucket was studied.120
    • In addition to development of the bile working machines was taken. All Publicationsvirtual testing environments and the subgoals were reached and improve- Summary of essential publicationsuser centered design studies, the fol- ments in real-time modelling and sim-lowing modelling and simulation meth- ulation of complex mechatronic sys- Heikkinen, J. 2009. Integration of Real-ods were developed: tems were achieved. Three compati- time simulator, motion platform and• Real-time modelling of stress and ble virtual environments were devel- haptics. Master’s Thesis, LUT. strain in beam type of structures by oped in participating research organ- Liu, J., Handroos, H. & Wu, H. Modeling of floating frame of reference method izations (Figure 1). Hydraulic Servo Valve Using Statistical• Robustness analysis of a model for Method. Bath/ASME Symposium on an electrohydraulic servosystem Impacts Fluid Power & Motion Control (FPMC by using Markov Chain Monte Car- During the project understanding of 2010). September, 2010. (In review) lo-method. the capabilities of virtual technology in Liu, J., Handroos, H., Haario, H. & Nishiumi,• Pseudo-dynamic solver for pres- user centered R&D in the participating T. Improving the Robustness of sures in small fluid volumes in flu- companies was significantly strength- Simulation Models for Hydraulic id power circuits. ened. Components and Circuits by a Statistical Method. SICFP09, The 11thResults International cooperation Scandinavian International ConferenceA significant step towards apply- Co-operation and research exchange on Fluid Power, 2–4 June 2009,ing real-time simulator assisted us- with UNIMORE (Italy) and Salford Uni- Linköping, Sweden.er centered R&D methods in real mo- versity (UK).Figure 1. Virtual technology laboratory at LUT demonstrating the LHD simulator with motion platform. 121
    • Liu, J., Handroos, H., Haario, H. & Wu, H. Yousefi, H., Soleimani, A. & Handroos, H. Project time scale Modeling Servo Hydraulic System by Human Centered Design of Mobile 1.1.2007–31.12.2009 Markov Chain Monte Carlo Method. (In Machines by a Virtual Environment. review in Mechatronics) Human Centered Design: First Project volume Liu, J., Handroos, H., Haario, H. & Wu, International Conference, HCD Total funding 501 282 €, H. Reliability Analysis of a Model 2009, San Diego, CA, USA. July 2009, Tekes share 420 000 € for Servo Hydraulic System by Springer. Utilizing Markov Chain Monte Carlo Åman, R. & Handroos, H. Comparison Project participants Method. Proceedings of the Seventh on Numerical Effectiveness of Three • Institute of Mechatronics and Virtual International conference on Fluid Methods for Modelling 2-way Flow Engineering, Lappeenranta University of Power Transmission and Control (ICFP Control Valves. Proceedings of the Technology 2009). 6–10 April 2009, Hangzhou, Seventh International conference • Department of Mechanics and Design, China. World Publishing Corporation. on Fluid Power Transmission and Tampere University of Technology Yousefi, H. & Handroos, H. Human Control (ICFP 2009), 6–10 April 2009, • VTT Technical Research Centre of Centered Design of Mobile Machines Hangzhou, China. World Publishing Finland, Industrial Systems Organization by a Virtual Environment, International Corporation. • Industrial Forum of Virtual Design Journal of Human-Computer Studies. Åman, R. & Handroos, H. Method for (In review) Improving Stability of an Explicit Contact information Yousefi, H., Handroos, H. & Soleymani, A. Integration Method in Fluid Power Heikki Handroos Usability Test in a Virtual Environment, Circuit Simulation, IMechE. (In review Lappeenranta University of Technology, A Case Study Based On a Mining in SIMRA Journal) Laboratory of Intelligent Machines Machine. Proceedings of the ASME Åman, R. & Handroos, H. Optimization of Tel. +358 40 510 7599 2010 10th Biennial Conference on Parameters of Pseudo-Dynamic Solver heikki.handroos@lut.fi Engineering Systems Design and for Real-Time Simulation of Fluid Analysis, ESDA2010, 12–14 July 2010, Power Circuits. 7th International Fluid Istanbul, Turkey. Power Conference (IFK), 22–24 March 2010 in Aachen.122
    • Combining simulation and optimisation with building draft and HVAC planning – MASIT35Project background and goals 2007). The internal gains due to peo- ment size. An existed Office buildingThe project is focusing in developing ple, lighting and electric appliances are (Kiinteistö Oy Lintulahdenvuori) is tak-new tools and business opportunities assumed according to annual values en as a case study. Only two typical of-for companies working with BSE sys- specified by the Finnish building code fice rooms are studied as representa-tem planning, deliveries, maintenance (D5) and inserted in the calculation as a tive zones for two different orientationsand manufacturing. profile with hourly values. The building (north and south). The office building The goal of the project is to pro- energy simulation was carried out using consists of eight floors (1490 m2 permote the development of computation- IDA-ICE 3.0 software and Helsinki-2001 floor) and basement, see Figure 2. Theal optimisation tools suitable for planning hourly weather data. CO2-eq emissions height of the building is 33 m above theof HVAC and other building services sys- of the heating energy and the invest- ground. The basement is –1.1 m downtems as well as construction related ener- ment cost were selected as two objec- the ground. Different types of spacesgy solutions and to support the introduc- tive functions to be minimised. A two- are existed in this building such as officetion of these tools and the new business phase multi-objective optimisation rooms, meeting rooms, kitchenettes, toi-concepts they enable in the Finnish build- solver that works under MATLAB envi- lets, corridors, and garages. Water radia-ing and building services sector. ronment was developed by the authors tors and cooling beams are installed to and used for the optimisation. remove the heating and cooling loadsProject actions The office building case focuses from the different building’s zones. TheThe work contains identification of ap- mainly to achieve a higher level of ther- office building is served by the most typ-plications, development of computa- mal comfort with minimum primary en- ical AC and ventilation system in Finlandtion tools, testing the optimisation ap- ergy consumption and cooling equip- shown in Figure 1. The HVAC system is aproach and support actions for intro-duction of optimisation. Internation-al cooperation plays a vital role in the Figure 1. Ventilation system of the office building.project as well. During year 2009 the work hasbeen focusing in developing optimisa-tion tools for building energy optimisa-tion and on finalising two cases, a low-rise building case and an office build-ing case. In the low-rise building case a typ-ical Finnish two-floor semi-detachedhouse, located in Helsinki, Finland, isconsidered as a case study. The totalfloor area of the house is 143 m2. Theinternal height is 2.5 m. The two floorsare connected by a staircase. In the in-itial design, the construction materialsare selected in order to achieve U-val-ues equal to the maximum values stat-ed in the Finnish building code (C3- 123
    • Figure 2. The low-rise building case pareto front. constant-pressure and mainly CAV sys- tem with active cooling beams. Rooms 40 000 are heated with hot-water radiators us- Case 1: Pareto Front ing district heating. The water radiator Heat Pump (sys.4) 35 000 Conceptual designs set-point, night set-back, and control- ler dead band as well as the supply air IC ( for 8 design variables in Euro ) District (sys.3) Fuel. Boiler (sys.2) temperature are taken as design varia- 30 000 bles through the optimization scheme. The objectives of this scheme are 25 000 to maximize the thermal comfort lev- Ele. Rad (sys.1) el and to minimize the primary energy 20 000 consumption as well as cooling equip- ment size. These objectives are consid- 15 000 ered to find the optimal solutions for the three thermal comfort categories (S1, 10 000 1 000 2 000 3 000 4 000 5 000 6 000 7 000 8 000 9 000 10 000 11 000 S2, and S3) of National Finnish Classifica- CO2_eq Emissions (Kg/a) tion-2008. The three categories require maintaining the indoor operative air temperature (Top) at certain set-points Figure 3. The office building trade-off relation between the primary energy which depend on the 24 hr’s mean aver- consumption and the deviations based on S1-definition. age outdoor air temperature (ODT24hr average). Different percentages of ac- ceptable deviation are defined for each category. Results In the low-rise building case the pare- to front of the best solutions is shown in Figure 2. The objectives are energy CO2 emissions and investment cost for the eight design variables. Very clearly can be seen the dominating role of the heating system. The blue points are rep- resenting the initial design. For the office building case Figure 3 shows the trade-off between the pri- mary energy consumption and the vi- olations of the S1-indoor climate clas- sification. The solutions fulfilling the S1 conditions are only few and the demand of them is higher than for the solutions fulfilling the S2 conditions. So the ener- gy need and the quality of the indoor cli- mate are clearly in a conflict.124
    • Impact of the results Publications Project participantsThe impact of the results comes Hamdy, M., Hasan, A. & Sirén, K. 2009. • Aalto University, School of Science andthrough the application of optimisa- Combination of optimisation Technologytion and simulation techniques in the algorithms for a multi-objective • Department of Energy Technologydraft and HVAC planning stage of the building design problem. Proceedings • Loughborough Universitycompanies. This approach opens totally of Building Simulation 2009 • Department of Civil and Buildingnew possibilities into planning and cre- conference, Glasgow. p. 173–179. Engineeringates new business opportunities, not Hamdy, M., Hasan, A. & Sirén, K. 2009. • Norwegian University of Science andonly for planning consultants but also Optimum design of a house and its Technologyfor companies working with BSE sys- HVAC systems using simulation-based • Department of Energy and Processtem deliveries, maintenance and man- optimisation. Proceedings of SET 2009 Engineeringufacturing. During the project one of conference, Aachen.the supporting companies has recruit- Palonen, M., Hasan, A. & Sirén, K. 2009. A Contact informationed a person who is able to start and de- genetic algorithm for optimization of Kai Sirénvelop the optimisation activities in the building envelope and HVAC system Aalto University School of Science andcompany. Also other companies have parameters. Proceedings of Building Technology, Dept. of Energy Technologyplans for educating their selected plan- Simulation 2009 conference, Glasgow. kai.siren@tkk.finers to import optimisation knowledge p. 159–166.and to develop this sector in their plan-ning and business. Time scale 1.1.2008–30.5.2010International cooperationThree European universities are includ- Project volumeed in the project group: Helsinki Uni- 220 000 €, Tekes share 170 000 €versity of Technology, LoughboroughUniversity and Norwegian Universityof Science and Technology. Research-er exchange has been implemented inthe form of mutual exchange visits be-tween the partners. 125
    • Annex 1. The projects of the MASI programmeAnnex 1 MASIT06 Modelling and simulation of coupled problems Research projects in mechanics and electrical engineering (KOMASI) Rolf Stenberg MASIT01 Multiobjective optimization and Helsinki University of Technology, multidisciplinary decision support Institute of Mathematics Kaisa Miettinen P.O. Box 1100, FI-02015 HUT Helsinki School of Economics, Tel. +358 9 4515576 Dept. of Business Technology Email: rolf.stenberg@tkk.fi P.O. Box 1210, FI-00101 Helsinki Tel. +358 50 3732247 MASIT07 Modeling and simulation of dissolved and Email: kaisa.miettinen@hse.fi colloidal substance flows in the TMP- and DIP-processes Martti Mäkinen MASIT02 Symbiosis between plant and computational Lappeenranta University of Technology, models (Simbiot) Fiber Technology Center Tommi Karhela P.O. Box 20, FI-53851 Lappeenranta VTT Technical Research Centre of Finland Tel. +358 40 7787737 P.O. Box 1301, FI-02044 VTT Email: martti.makinen@lut.fi Tel. +358 40 5822274 Email: tommi.karhela@vtt.fi MASIT08 Scientific computing and optimization in multidisciplinary application (SCOMA) MASIT03 Inverse problems and reliability of modelling Pekka Neittaanmäki Heikki Haario University of Jyväskylä, Lappeenranta University of Technology, Dept. of Mathematical Information Dept. of Mathematics and Physics P.O. Box 35, FI-40014 University of Jyväskylä P.O. Box 20, FI-53851 Lappeenranta Tel. +358 40 5507005 Tel. +358 400 814092 Email: pn@mit.jyu.fi Email: heikki.haario@lut.fi MASIT09 Automated generation of 3D topographic MASIT04 Multiphase chemistry in process simulation (VISTA) visualisations Pertti Koukkari Eija Parmes VTT Technical Research Centre of Finland VTT Technical Research Centre of Finland P.O. Box 1602, FI-02044 VTT P.O. Box 1000, FI-02044 VTT Tel. +358 40 5834092 Tel. +358 20 7226284 Email: pertti.koukkari@vtt.fi Email: eija.parmes@vtt.fi MASIT05 Statistical phenomena in virtual design of MASIT10 Improvement of evacuation safety in large buildings machines (MARTSI) by the combined simulation of fire and human behaviour Markus Hirvonen Simo Hostikka Lappeenranta University of Technology VTT Technical Research Centre of Finland P.O. Box 20, FI-53851 Lappeenranta P.O. Box 1803, FI-02044 VTT Tel. +358 50 3453171 Tel. +358 20 7224839 Email: markus.hirvonen@lut.fi Email: simo.hostikka@vtt.fi 126
    • MASIT11 Modeling and simulation of manufacturing MASIT17 Combining multiblock and CFD modelling (LOVI) Annex 1systems for value networks (MS2Value) Ville AlopaeusAntti Soini Helsinki University of Technology,Satakunta University of Applied Sciencies Laboratory of Chemical EngineeringTekniikantie 2, FI-28600 Pori P.O. Box 1000, FI-02015 HUTTel. +358 2 6203174 Tel. +358 9 4512630Email: antti.soini@samk.fi Email: ville.alopaeus@tkk.fiMASIT12 Modeling and simulation of manufacturing MASIT18 Utilisation of simulation in industrial design andsystems for value networks (MS2Value) resulting business opportunities (SISU)Ricardo Velez Markus OlinTampere University of Technology, VTT Technical Research Centre of FinlandInstitute of Production Engineering P.O. Box 1000, FI-02044 VTTP.O. Box 589, FI-33101 Tampere Tel. +358 400477 244Tel. +358 44 3100063 Email: markus.olin@vtt.fiEmail: ricardo.velez@tut.fi MASIT19 Multi-scale flow modelling (MUSCA)MASIT13 In silico models of disease pathogenesis and Jari Hämäläinentherapy (TRANSCENDO) University of Kuopio, Dept. of PhysicsMarko Sysi-aho P.O. Box 1627, FI-70211 KuopioVTT Technical Research Centre of Finland Tel. +358 17 162279P.O. Box 1000, FI-02044 VTT Email: jari.hamalainen@uku.fiTel. +358 20 7224491 MASIT20 Nonlinear temporal and spatial forecasting:Email: marko.sysi-aho@vtt.fi modeling and uncertainty analysis (NoTeS)MASIT14 From discrete to continuous models for Risto Ritalamultiphase flows Tampere University of Technology,Ilkka Turunen Institute of Measurement and Information TechnologyLappeenranta University of Technology, P.O. Box 527, FI-33101 TampereDept. of Information Technology Tel. +358 40 8490922P.O. Box 20, FI-53851 Lappeenranta Email: risto.ritala@tut.fiTel. +358 40 5692450 MASIT21 Genuinely three-dimensional user interfacesEmail: ilkka.turunen@lut.fi in product design and animation (HandsOn)MASIT15 Virtual engineering in design, training and Tapio Takalacompletion of demanding maintenance work tasks (VIRVO) Helsinki University of Technology, Telecommunications SoftwareKaj Helin and Multimedia LaboratoryVTT Technical Research Centre of Finland P.O Box 1000, FI-02015 HUTP.O. Box 1300, FI-33101 Tampere Tel +358 50 5513222Tel. +358 40 8479351 Email: tapio.takala@tkk.fiEmail: kaj.helin@vtt.fi MASIT22 Transcendo-ICSI collaborationMASIT16 Modeling changing needs of consumers (KULTA) Matej OresicTimo Honkela, Tanja Kotro VTT Technical Research Centre of FinlandHelsinki University of Technology P.O Box 1000, FI-02044 VTTP.O. Box 5400, FI-02015 HUT Tel. +358 40 7055156Tel. +358 50 3841578 Email: matej.oresic@vtt.fiEmail: timo.honkela@tkk.fi, tanja.kotro@ncrc.fi 127
    • MASIT23 Developing chemometrics with the tools of MASIT29 Modelling interfacial partitioning in multi-phaseAnnex 1 information sciences (CHESS) systems (INTER) Olli Simula Pertti Koukkari Helsinki University of Technology, VTT Technical Research Centre of Finland Adaptive Informatics Research Centre P.O. Box 1000, FI-02044 VTT P.O. Box 5400, FI-02015 HUT Tel. +358 20 7226366 Tel. +358 9 4513271 Email: pertti.koukkari@vtt.fi Email: olli.simula@hut.fi MASIT30 Ice-structure interaction modelling and MASIT24 Modelling and simulation in software simulation (STRUTSI) engineering (MoSSE) Jaakko Heinonen Timo Varkoi VTT Technical Research Centre of Finland Tampere University of Technology, Pori P.O. Box 1000, FI-02044 VTT P.O. Box 300, FI-28101 Pori Tel. +358 20 7226907 Tel. +358 2 6272844 Email: jaakko.heinonen@vtt.fi Email: timo.varkoi@tut.fi MASIT31 Automatic testing of control systems in the MASIT25 Innovative simulation method of multi-phase integration phase of intelligent mobile machines (TINAT) chemistry (InnoSim) Petteri Multanen Pertti Koukkari Tampere University of Technology, VTT Technical Research Centre of Finland Department of Intelligent Hydraulics and Automation P.O.Box 1000, FI-02044 VTT P.O. Box 589, FI- 33101 Tampere Tel. +358 40 5834092 Tel. +358 50 5994329 Email: pertti.koukkari@vtt.fi Email: petteri.multanen@tut.fi MASIT26 Researcher exchange of Virvo project with MASIT32 Design and modeling of printable electronics the University of Malaga applications (DEMOprint) Simo-Pekka Leino Riku Mäkinen VTT Technical Research Centre of Finland, ROViR Centre Tampere University of Technology, Department of Electronics P.O. Box 1300, FI-33101 Tampere P.O. Box 692, FI-33101 Tampere Tel. +358 40 7377 184 Tel. +358 40 8490087 Email: simo-pekka.leino@vtt.fi E-mail: riku.makinen@tut.fi MASIT27 Development of the 3D power plant simulator MASIT33 Industrial application of PhaseField modelling Samu Urpalainen (PhaseField) Kymenlaakso University of Applied Sciences Tommi Karhela P.O Box 9, FI-48401 Kotka VTT Technical Research Centre of Finland Tel. +358 44 702 8256 P.O. Box 1000, FI-02044 VTT Email: samu.urpalainen@kyamk.fi Tel. +358 20 7226246 Email: tommi.karhela@vtt.fi MASIT28 Flow physics and modelling (FloPhy) Antti Oksanen MASIT34 Qualitative methods in virtual design of machines Tampere University of Technology (KVALIVE) P.O. Box 589, FI-33101 Tampere Heikki Handroos Tel. +358 400 753088 Lappeenranta University of Technology, Email: antti.oksanen@tut.fi Institute of Mechatronics and Virtual P.O. Box 20, FI-53851 Lappeenranta Tel. +358 40 5107599 E-mail: heikki.handroos@lut.fi 128
    • MASIT35 Combining simulation and optimisation MASIY05 Simulation of continuous cooking systems Annex 1with building draft and Aki MuhliHVAC planning Andritz OyKai Sirén Tammasaarenkatu 1, FI-00180 HelsinkiHelsinki University of Technology, Tel. +358 40 8605360Department of Energy Engineering Email: aki.muhli@andritz.comP.O. Box 4400, FI-02015 HUT MASIY06 Plasma combustion process prototypeTel. +358 40 5741871 Heikki MononenEmail: kai.siren@tkk.fi HR-Nugat OyMASIT36 Modeling and simulation of the changing Huumantie 5, FI-48230 Kotkaneeds of consumers (KULTA2) Tel. +358 5 2255700Tanja Kotro Email: heikki.mononen@finex.fiKuluttajatutkimuskeskus MASIY07 Management of sulfur balanceP.O.Box 5, 00531 Helsinki Kurt SirénTel. +358 50 3028275 Oy Keskuslaboratorio-Centrallaboratorium AbEmail: tanja.kotro@ncrc.fi P.O. Box 70, FI-02151 Espoo Tel. + 358 9 4371322Enterprise projects Email: kurt.siren@kcl.fi MASIY08 Simulation-aided control of mechanical pulpingMASIY01 Digital enterprise simulation framework Tomi KulomaaCraig Lybeck Stora Enso Oyj, Imatra millVisual Components Oy P.O. Box 309, FI-00101 HelsinkiKorppaanmäentie 17 CL6, FI-00300 Helsinki Tel. +358 40 8274158Tel. +358 9 3232250 Email: tomi.kulomaa@storaenso.comEmail: craig.lybeck@visualcomponents.com MASIY09 Profitable insurance businessMASIY02 Simulation models in building and construction Pasi SaarikoskiAntti Peltola Profit Software OyCreanex Oy Meritullinkatu 11 C, FI-00170 HelsinkiNuolialantie 62, FI-33900 Tampere Tel. +358 40 5708400Tel. +358 50 3110301 Email: pasi.saarikoski@profitsoftware.comEmail: antti.peltola@creanex.com MASIY10 Process chemistry in FlowMac and KraftMacMASIY03 Coupled model systems simulatorJussi Heikonen Xiaoning LiCSC-Tieteellinen laskenta Oy ÅF-CTS OyP.O. Box 405, FI-02101 Espoo P.O. Box 193, FI-45101 KouvolaTel. +358 9 4572065 Tel. +358 20 7567494Email: jussi.heikonen@csc.fi Email: xiaoning.li@afconsult.comMASIY04 Aquaplaning MASIY11 HSC Chemistry® -based simulation and modellingMikko Liukkula Antti RoineNokian Renkaat Oyj Outokumpu Research OyP.O. Box 20, FI-37101 Nokia P.O. Box 60, FI-28101 PoriTel. +358 3 3407722 Tel. +358 2 6265067Email: mikko.liukkula@nokiantyres.com Email: antti.roine@outokumpu.com 129
    • MASIY12 Proactive business model in automobile sales MASIY18 Market research on modelling andAnnex 1 Mikael Teerilahti simulation service business Grey-Hen Oy Janne-Pekka Mäkinen P.O. Box 84, FI-02280 Espoo Platom Oy Tel. +358 40 5918802 P.O. Box 300, FI-50101 Mikkeli Email: mikael.teerilahti@grey-hen.com Tel. +358 44 5504309 Email: janne-pekka.makinen@platom.fi MASIY13 Control of process chemistry in a paper machine MASIY19 Reducing risks in next generation dryer Jutta Nuortila-Jokinen fabric manufacturing UPM-Kymmene Oyj, Research centre Lars Fagerholm P.O. Box 380, FI-00101 Helsinki Albany International Oy Tel. +358 20 4154717 Rosasvägen 10, FI-00390 Helsingfors Email: jutta.nuortila-jokinen@upm-kymmene.com Tel. +358 9 5478507 Email: lars_fagerholm@albint.com MASIY14 Paper machine process modeling Matti Kurki MASIY20 NeOil modelling 2005-6 Metso Paper Oy Isto Eilos P.O. Box 1220, FI-00101 Helsinki Neste Oil Oyj, Technology centre Tel. +358 20 4825941 P.O. Box 95, FI-00095 Nesteoil Email: matti.kurki@metso.com Tel. +358 50 4583142 Email: isto.eilos@nesteoil.com MASIY15 Metamodel based simulation and integration Juha-Pekka Tolvanen MASIY21 Multi-physics simulations MetaCase Consulting Oy Asta Kärkkäinen Ylistönmäentie 31, FI-40500 Jyväskylä Nokia Oyj, Nokia Research Center Tel. +358 400 648606 P.O. Box 407, FI-00045 Nokia Group Email: jpt@metacase.com Tel. +358 50 4837310 Email: asta.karkkainen@nokia.com MASIY16 Development of an equipment selection software tool MASIY22 Customer friendly simulation tools in power Johannis Likos Antti Komulainen Fincoil-teollisuus Oy Endat Oy Ansatie 3, FI-01740 Vantaa Tekniikantie 12 C, FI-02150 Espoo Tel. +358 9 8944289 Tel. +358 9 25172519 Email: johannis.likos@fincoil.fi Email: antti.komulainen@endat.fi MASIY17 Towards Finnish HPC excellence MASIY23 Modeling and simulation software for Jan Åström micro-electro-mechanical systems and microfluidics CSC-Tieteellinen laskenta Oy Pasi Marttila P.O. Box 405, FI-02101 Espoo Comsol Oy Tel. +358 9 4572255 Lauttasaarentie 52, FI-00200 Helsinki Email: jan.astrom@csc.fi Tel. +358 9 25104051 Email: pasi.marttila@comsol.fi 130
    • MASIY24 FSI-networking of process flow MASIY31 Simulation platform Annex 1Arttu Kalliovalkama Santeri KorriProcess Flow Ltd Oy Cesim OyVerstaankatu 7, FI-33100 Tampere Arkadiankatu 21 A, FI-00100 HelsinkiTel. +358 3 2619900 Tel. +358 400 607073Email: arttu.kalliovalkama@processflow.fi Email: santeri.korri@cesim.comMASIY25 Development of SimBus bus simulator MASIY32 Development of 3D/cut-out hybrid techniqueTeppo Tenkanen Mikael WahlforssSTC Simulator Training Oy Zot OyPuhaltajankatu 35, FI-11910 Riihimäki Sepänkatu 15 B, FI-00150 HelsinkiTel. +358 400 452356 Tel. +358 40 5442490Email: teppo.tenkanen@simulatortraining.fi Email: wahlforss@epidem.pp.fiMASIY26 APROS containment model MASIY33 Simulation models in building and constructionMika Harti Pasi JulkunenFortum Nuclear Services Oy Sandvik Tamrock OyP.O. Box 100, FI-00048 Fortum, Finland P.O. Box 100, FI-33311 TampereTel. +358 10 4532406 Tel. +358 4 5271000Email: mika.harti@fortum.com Email: pasi.julkunen@sandvik.comMASIY27 Linking of thermal hydraulics and structure MASIY34 Simulation of production processesanalysis codes in fluid-structure systems Mika MustajärviVille Lestinen Outokummun Metalli OyFortum Nuclear Services Oy P.O. Box 8, FI-83501 OutokumpuP.O. Box 100, FI-00048 Fortum Tel. +358 13 563230Tel. +358 50 4532427 Email: mika.mustajarvi@outokummunmetalli.fiEmail: ville.lestinen@fortum.com MASIY35 Optimization of wastewater treatment byMASIY28 Development of methods for real-space, process modelling and simulationreal-time electronic structure simulations of nanostructures Kristian SahlstedtJussi Enkovaara Maa ja Vesi OyCSC-Tieteellinen laskenta Oy P.O. Box 50, FI-01621 VantaaP.O. Box 405, FI-02101 Espoo Tel. +358 9 6826748Tel. +358 9 4572935 Email: kristian.sahlstedt@poyry.fiEmail: jussi.enkovaara@csc.fi MASIY36 PredictorMASIY29 Dynamic thermal modelling of air-core reactors Sampsa LaineJari Kotiniitty Data Rangers OyNokian Capacitors Oy Tekniikantie 21, FI-02150 EspooP.O. Box 4, FI-33331 Tampere Tel. +358 50 5497893Tel. +358 3 3883255 Email: sampsa.laine@datarangers.fiEmail: jari.kotiniitty@nokiancapacitors.fi MASIY37 Development of time-dependent simulationMASIY30 Nassim properties of the Optimaze.net service productMikko Kittilä Pekka TalaskiviProwledge Oy Rakennuttajapalaute Rapal OyTekniikantie 14, FI-02150 Espoo HTC Tammasaarenkatu 7 A, FI-00180 HelsinkiTel. +358 9 25177385 Tel. +358 50 5620116Email: mikko.kittila@prowledge.com Email: pekka.talaskivi@rapal.fi 131
    • MASIY38 Simulation of business and logistics MASIY45 Competitiveness from technologyAnnex 1 Juha Munne Mika Sippola Fenestra Oy Efore Oyj P.O. Box 95, FI-30101 Forssa P.O. Box 260, FI-02601 Espoo Tel. +358 40 8220777 Tel. +358 9 47846412 Email: juha.munne@fenestra.fi Email: mika.sippola@efore.fi MASIY39 Multi-phase chemistry in process simulation MASIY46 Developing property portfolio analysis and Matti Sirviö management Simtech Systems Inc Oy Hanna Kaleva Kukkaromäki 6 C 5, FI-02770 Espoo KTI Kiinteistötieto Oy Tel. +358 500 514531 Eerikinkatu 28, FI-00180 Helsinki Email: matti.sirvio@fonet.fi Tel. +358 20 7430124 Email: hanna.kaleva@kti.fi MASIY40 Modelling and optimization of an EPS process Matti Ilanti MASIY47 Identification of wood behavior and modeling of mechanical defibration StyroChem Finland Oy Mikael Lucander P.O. Box 360, FI-06101 Porvoo Oy Keskuslaboratorio-Centrallaboratorium Ab Tel. +358 19 5418334 P.O. Box 70, FI-02151 Espoo Email: matti.ilanti@styrochem.fi Tel. +358 20 7477328 MASIY41 5D infra view Email: mikael.lucander@kcl.fi Jarkko Sireeni MASIY48 Run Away research on catalytic bed reactor Vianova Systems Finland Oy Johan Grönqvist Hannuntie 6, FI-02360 Espoo Neste Oil Oyj Tel. +358 9 23132100 P.O. Box 95, FI-00095 Porvoo Email: jarkko.sireeni@viasys.com Tel. +358 10 4585210 MASIY42 Modeling and performance of Email: johan.gronqvist@nesteoil.com mobile computing MASIY49 Numerrin 4.0 - Expert system in modeling Ari P. Ahtiainen Numerola Oy Nokia Oyj Kai Hiltunen P.O. Box 226, FI-00045 Nokia Group Väinönkatu 11 A, FI-40100 Jyväskylä Tel. +358 71 8036426 Tel. +358 14 3340433 Email: ari.p.ahtiainen@nokia.com Email: kai.hiltunen@numerola.fi MASIY43 Sumulation model for timber drying MASIY50 Modelling of operation optimization of telenetworks Markku Lehtonen Veli-Pekka Luoma Wood Focus Oy Nokia Oyj, Nokia Networks/Managed Services P.O. Box 284, FI-00171 Helsinki P.O. Box 300, FI-00045 Nokia Group Tel. +358 9 68654521 Tel. +358 40 5743489 Email: markku.lehtonen@woodfocus.fi Email: veli-pekka.luoma@nokia.com MASIY44 Optimization of production flow MASIY51 Abrasion control of processing industry equipment Jyrki Leppäaho Jari Liimatainen Metsä Tissue Oyj Metso Powdermet Oy Itälahdenkatu 15-17, FI-00210 Helsinki P.O. Box 237, FI-33101 Tampere Tel. +358 20 484120 Email: jari.liimatainen@metso.com 132
    • MASIY52 Multiphysical modeling of electrolyse MASIY58 Medical 3D models Annex 1Olli Järvinen Ismo MäkeläOutokumpu Technology Oy DeskArtes OyP.O. Box 86, FI-02201 Espoo Särkinementie 5 C 13, FI-00210 HelsinkiTel. +358 9 4212384 Tel. +358 400 707042Email: olli.jarvinen@outokumpu.com Email: ismo.makela@deskartes.fiMASIY53 Analysis and models aiming for zero errors MASIY59 A parametric simulation modelTaisto Tinttunen Reijo HautalaAWR-APLAC Oy Härmä Air OyP.O. Box 284, FI-02601 Espoo Köykkärintie 418, FI-62310 VolttiTel. +358 9 54045000 Tel. +358 40 5571554Email: taisto.tinttunen@aplac.com Email: rh@harmaair.comMASIY54 Numerical modelling for plate heat MASIY60 Optimization of design and production ofexchanger design flow componentsJukka Hyvärinen Hannu TeiskonenOy Danfoss Ab Alamarin-Jet OyTeollisuustie 15, FI-79100 Leppävirta Tuomisentie 16, FI-62300 HärmäTel. +358 40 3092238 Tel. +358 40 5036378Email: jukka.hyvarinen@danfoss.com E-mail: sales@alamarinjet.comMASIY55 Software development for computational MASIY61 Utilizing wireless LAN modelling and simulationEMF dosimetry (EMSOFT) processes for advanced real-time location systemKimmo Kärkkäinen Salla HeinoNokia Oyj Ekahau OyP.O. Box 301, FI-00045 Nokia Group Tallberginkatu 2, FI-00180 HelsinkiTel. +358 50 4860305 Tel. +358 20 7435910Email: kimmo.karkkainen@nokia.com Email: sales-europe@ekahau.comMASIY56 Validation of the Apros containment model MASIY62 Development of a virtual work machineMika Harti Joona MäkiraatikkaFortum Nuclear Services Oy John Deere Forestry OyP.O. Box 100, FI-00048 Fortum PL 511, 33101 TampereTel. +358 50 4532406 Tel. +358 20 5846 823Email: mika.harti@fortum.com Email: makiraatikkajoonaj@johndeere.comMASIY57 Modern control and monitoring of enrichment MASIY63 Improvement of the in ternational competitivenessprocesses of the Ekahau RTLS systemKari Saloheimo Salla HeinoOutokumpu Technology Minerals Oy Ekahau OyP.O. Box 84, FI-02201 Espoo Tallberginkatu 2, FI-00180 HelsinkiTel. +358 9 4213562 Tel. +358 20 7435910Email: kari.saloheimo@outokumpu.fi Email: salla.heino@ekahau.com 133
    • MASIY64 Engine noise 2 MASIY70 Real option valuation and strategic solutionsAnnex 1 Kari Saine Johan Grön Wärtsilä Finland Oy Kemira Oyj P.O. Box 252 , FI-65101 Vaasa P.O. Box 330, FI-00101 Helsinki Tel. +358 10 7092526 Tel. +358 40 5464186 Email: kari.saine@wartsila.com Email: johan.gron@kemira.com MASIY65 Development of a prediction model for lift MASIY71 Improving pressurised water reactor knowledge transport with renewed testing equipment (PAOLA) Harri Hakala Jari Tuunanen KONE Oyj Teollisuuden Voima Oy Eliel Saarisen tie 2, FI-00400 Helsinki FI-27160 Olkiluoto Tel. +358 204 752764 Tel. +358 2 83813250 Email: harri.hakala@kone.com Email: jari.tuunanen@tvo.fi MASIY66 Natural gas technology for clean er future: MASIY72 Print and paper process designer Nanoscale particles in CNG-catalyst chemistry Ismo Laukkanen Toni Kinnunen UPM-Kymmene Oyj Ecocat Oy P.O. Box 380, FI-00101 Helsinki P.O.Box 20 , FI-41331 Vihtavuori Tel. +358 204 150218 Tel. +358 10 6535792 Email: ismo.laukkanen@upm-kymmene.com Email: toni.kinnunen@ecocat.com MASIY73 Modelling of spouts and radiation in furnaces MASIY67 Fast and cost-effective conversion of ferritic and Lauri Pakarinen Mn-alloy stainless steels Andritz Oy Pentti Kupari P.O. Box 500, FI-48600 Kotka Outokumpu Stainless Oy Tel. +358 40 8605064 Tornion tehtaat, FI-95400 Tornio Email: lauri.pakarinen@andritz.com Tel.+358 16 452840 MASIY74 Research and development of RAM software Email: pentti.kupari@outokumpu.com Timo Lehtinen MASIY68 NesteOil multiphase modelling Ramentor Oy, c/o Hervannan tilitoimisto Isto Eilos Lindforsinkatu 4, FI-33720 Tampere Neste Oil Oyj, Development and Laboratories Tel. +358 40 7466585 P.O. Box 310, FI-06101 Porvoo Email: timo.lehtinen@ramentor.com Tel. +358 50 4583142 MASIY75 Controlling freshness in supply chain of short Email: isto.eilos@nesteoil.com lifespan products MASIY69 Numerical modelling techniques for Ville Ruuskanen electric furnace processes Atria Suomi Oy Kaj Eklund P.O. Box 900, FI-60060 Atria Outotec Research Oy Tel. +358 40 5445066 P.O. Box 69, FI-28101 Pori Email: ville.ruuskanen@atria.fi Tel. +358 40 8297305 Email: kaj.eklund@outotec.com 134
    • MASIY76 Competitiveness from technology – PHase III MASIY82 Simulator-assisted testing Annex 1Mika Sippola Ari KananenEfore Oyj Ponsse OyjP.O. Box 260, FI-02601 Espoo Ponssentie 22, FI-74200 VieremäTel. +358 9 47846412 Tel. +358 20 768 800Email: mika.sippola@efore.fi Email: ari.kananen@ponsse.comMASIY77 Model based decision-making and optimization MASIY83 Knowledge-intensive business services basedsystem on airborne laser scanning of forestlandRisto Talja Tuomo KauranneMetso Paper Oyj Oy Arbonaut LtdP.O. Box 587, FI-40101 Jyväskylä Koskikatu 5 B, FI-80100 JoensuuTel. +358 40 5859307 Tel. +358 40 5300622Email: risto.talja@metso.com Email: tuomo.kauranne@arbonaut.comMASIY78 Real time product development simulators in MASIY84 Utilizaton of CFD in product development anddesigning and testing of underground mining gear customer applicationsArto Vento Reima MäkirantaSandvik Mining and Construction Oy Oilon International OyP.O. Box 100, FI-33311 Tampere P.O. Box 5, FI-15801 LahtiTel. +358 40 7601728 Tel. +358 3 85761Email: arto.vento@sandvik.com Email: reima.makiranta@oilon.comMASIY79 Understand and predict coupledfracturing/ fluid MASIY85 Simulator-assisted testingflow/ thermal process of rocks Antti PeltolaMikael Rinne Creanex OyFracom Oy Nuolialantie 62, FI-33900 TampereVaarinpiha 14, FI-02400 Kirkkonummi Tel. +358 50 3110301Tel. +358 9 22300950 Email: antti.peltola@creanex.comEmail: mikael.rinne@fracom.fi MASIY86 Single Run simulation in papermakingMASIY80 M&S research in the development of peristaltic Risto Taljahose pumps Metso Paper OyjJukka Aaltonen P.O.Box 587, FI-40101 JyväskyläLarox Flowsys Oy Tel. +358 40 5859307P.O. Box 338 , FI-53101 Lappeenranta Email: risto.talja@metso.comTel. +358 201 113330 MASIY87 Single run simulation in paper makingEmail: jukka.aaltonen@larox.fi Roger MöllerMASIY81 Tools for large scale computational fluid dynamics Albany International OyPeter Råback Rosasvägen 10, FI-00390 HelsingforsCSC-Tieteellinen laskenta Oy Tel. +358 400 258504P.O. Box 405, FI-02101 Espoo Email: roger.moller@albint.comTel. +358 9 4572080Email: peter.raback@csc.fi 135
    • MASIY88 Simulation-based optimization of gear MASIY95 Innovation and technology development ofAnnex 1 assembly dynamics eccentric screw pumps Totte Virtanen Risto Ruutiainen Valtra Oy Ab Larox Flowsys Oy Valmetinkatu 2, FI-44200 Suolahti P.O. Box 338, FI-53101 Lappeenranta Email: totte.virtanen@valtra.com Tel. +358 400 986520 MASIY89 Simulator-assested testing for steerign system Email: risto.ruutiainen@larox.fi Jyrki Hämäläinen MASIY96 Research methods for multi physical CAE Sandvik Mining and Construction Oy applications P.O.Box 100, FI-33311 Tampere Hannu Karema Tel. 040 5700033 Process Flow Ltd Oy Email: jyrki.hamalainen@sandvik.com Puolalanpuisto 1 b A 21, FI-20100 Turku MASIY90 Simulation of washing ja bleaching Tel. +358 40 9004584 Aija Korhonen Email: hannu.karema@processflow.fi ÅF-Consult Oy MASIY97 Development of welded heat exchangers for P.O.Box 61, FI-01601 Vantaa high design pressure and gas applications Tel. +358 40 3485617 Jyrki Sonninen Email: aija.korhonen@afconsult.com Vahterus Oy MASIY91 Development and launching of a material handling Pruukintie 7, FI-23600 Kalanti process simulation and customer profit configuration Tel. +358 44 7427040 Reijo Viinonen Email: jyrki.sonninen@vahterus.com Actiw Oy MASIY98 Development of simulator production Voimapolku 2, FI-76850 Naarajärvi Tero Eskola Tel. +358 40 7439999 MeVEA Oy Email: reijo.viinonen@actiw.com Laserkatu 6, FI-53850 Lappeenranta MASIY92 Audio distortion Tel. +358 500 150003 Timo Avikainen Email: tero.eskola@mevea.com Nokia Oyj, Nokia Devices R&D MASIY99 Development of CFD calculation technology P.O.Box 266, FI-00045 Nokia Group for modelling of fibre suspensions and exhaust air Tel. +358 50 4836760 Pekka Purho Email: timo.avikainen@nokia.com Mekateam Oy MASIY93 Training simulator for mobile frame crane Tel. +358 15 510052 Tuomo Raami Email: pekka.purho@mekateam.fi Cargotec Finland Oy MASIY100 Dynamic cost structre simulation of a pulp mill Valmetinkatu 5, FI-33900 Tampere Vesa Timonen Tel. +358 40 7756417 POHTO Oy Email: tuomo.raami@kalmarind.com Vellamontie 12, 90500 Oulu MASIY94 Better money Tel. +358 50 5438440 Tuomas Pinomaa Email: vesa.timonen@pohto.fi Mint of Finland Ltd. P.O. Box 100, FI-01741 Vantaa Tel. +358 50 492256 Email: tuomas.pinomaa@mint.fi 136
    • Annex 2. MASI steering group Annex 2Turpeinen Harri Halttula Heikki Pienimaa SeppoChairman Vianova Systems Finland Oy Nokia Research CenterNeste Oil Oyj Hannuntie 6, FI-02360 Espoo P.O. Box 407, FI-00045 Nokia GroupP.O. Box 310, FI-06101 Porvoo Tel. +358 40 547 2440 seppo.pienimaa@nokia.comCurrent contact information: heikki.halttula@vianova.fiturpeinen.consult@bastu.net Pulkkinen Pentti Huovila Jyrki Academy of FinlandKotipelto Arto Metso Paper, Inc. P.O. Box 99, FI-00501 HelsinkiProgramme Manager P.O. Box 587, FI-40101 Jyväskylä Tel. +358 40 5477 654Tekes, the Finnish Funding Agency for Tel. +358 40 551 9237 pentti.pulkkinen@aka.fiTechnology and Innovation jyrki.huovila@metso.fiP.O. Box 69, FI-00101 Helsinki Syrjänen TimoTel. +358 44 712 4138 Knuutila Kari Pöyry Application Services Oyarto.kotipelto@tekes.fi Outotec Oyj P.O. Box 4, FI-01621 Vantaa P.O. Box 60, FI-28101 Pori Tel. +358 40 733 6186Taskinen Pekka Tel. +358 40 7799 566 timo.syrjanen@poyry.fiProgramme Coordinator kari.knuutila@outotec.comVTT Technical Research Centre of FinlandP.O. Box 1603, FI-40101 Jyväskylä Pekonen OlliTel. +358 40 558 4954 National Board of Patents andpekka.taskinen@vtt.fi Registration of Finland Arkadiankatu 6 A,Eriksson Kenneth FI-00100 Helsinki FinlandProcess Flow Ltd Oy Tel. +358 9 6939 5231Puolalanpuisto 1 b A 21, FI-20100 Turku olli.pekonen@prh.fiTel. +358 40 900 4595kenneth.eriksson@processflow.fi 137
    • Tekes’ Programme Reports in English 3/2010 MASI Programme 2005–2009. Niina Holviala (ed.). Final Report. 137 p. 2/2010 FinnWell – terveydenhuollon ohjelma 2004–2009. Loppuraportti. 50 s. 1/2010 SISU 2010 – Uusi tuotantoajattelu. Loppuraportti. 246 s 4/2009 ClimBus – Business Opportunities in the Mitigation of Climate Change 2004–2008. Final Report. 564 p. 6/2008 Finnish participation in the EU 6th Framework Programme – Evaluation of Participation and Networks. Soile Kuitunen, Katri Haila, Ilpo Kauppinen, Mikko Syrjänen, Juha Vanhanen, Paavo-Petri Ahonen, Ilkka Tuomi, Pekka Kettunen & Teemu Paavola. Evaluation Report. 91 p. 2/2008 Impact Evaluation of the Wood Material Science and Engineering Research Programme. Evaluation Report. Kimmo Halme, Sami Kanninen, Kimmo Viljamaa, Erik Arnold, Tomas Åström and Tommy Jansson. 79 p. 11/2007 DENSY – Distributed Energy Systems 2003–2007. Final Report. 155 p. 2/2007 FENIX – Interactive Computing 2003–2007. Final Report. 136 p. 1/2007 FUSION Technology Programme Report 2003–2006. Final Report. 184 p. Seppo Karttunen and Karin Rantamäki (Eds) 17/2006 PINTA – Clean Surfaces 2002–2006. Final and Evaluation Report. 228 p. 13/2006 Finnish National Evaluation of EUREKA and COST. Evaluation Report. 95 p. Sami Kanninen, Pirjo Kutinlahti, Terttu Luukkonen, Juha Oksanen and Tarmo Lemola. 11/2006 Competitiveness through Integration in Process Industry Communities. Evaluation of Technology Programme “Process Integration 2000–2004”. Evaluation Report. 17 p. 8/2006 AVALI – Business Opportunities from Space Technology 2002–2005. Final Report. 79 p. 6/2006 New Knowledge and Competence for Technology and Innovation Policies – ProACT Research Programme 2001–2005. Final Report. 137 p. Edited by Pekka Pesonen. 3/2006 ELMO – Miniaturising Electronics 2002–2005. Final Report. 238 p. Subscriptions: www.tekes.fi/english/publications138
    • Further informationArto KotipeltoTekesMobile +358 44 712 4138arto.kotipelto@tekes.fiTekes – Finnish Funding Agency forTechnology and InnovationTel. +358 10 191 480Fax +358 9 694 9196Kyllikinportti 2, P.O. Box 69FIN-00101 Helsinki, FinlandE-mail: tekes@tekes.fiwww.tekes.fiApril 2010ISSN 1797-7347ISBN 978-952-457-498-3