"Can programming of multi-core systems be easier, please? The ALMA Approach"
By Oliver Oey, Karlsruhe Institute of Technologie - KIT for ScilabTEC 2015
Modelica Tutorial with PowerSystems: A tutorial for Modelica simulation智哉 今西
A simulation for electricity transmission using Modelica language.
Since all the tools come from OpenModelica (a free tool), you can easily start and test the simulation in any OS.
See the following link about OpenModelica: https://www.openmodelica.org/
"Can programming of multi-core systems be easier, please? The ALMA Approach"
By Oliver Oey, Karlsruhe Institute of Technologie - KIT for ScilabTEC 2015
Modelica Tutorial with PowerSystems: A tutorial for Modelica simulation智哉 今西
A simulation for electricity transmission using Modelica language.
Since all the tools come from OpenModelica (a free tool), you can easily start and test the simulation in any OS.
See the following link about OpenModelica: https://www.openmodelica.org/
On The Evolution of CAEX: A Language Engineering PerspectiveLuca Berardinelli
CAEX is one of the most promising standards when it comes to data exchange between engineering tools in the production system automation domain. This is also reflected by the current emergence of AutomationML which uses CAEX as its core representation data format. Having such standards at hand, the question arises how to deal with the evolution of such standards as is currently happening with the transition from CAEX 2.15 to CAEX 3.0.
In this work, we take a language engineering point of view to the evolution of engineering data formats. In particular, we present how CAEX can be formulated in a model-based framework which allows to reason about evolution of the data format as well as its impact on the data stored in such evolving formats. By this, not only the migration process of existing data to the new format version is possible, but also a more theoretical investigation on information preservation is possible. We demonstrate the approach by the concrete case of the upcoming CAEX evolution.
Integrating Performance Modeling in Industrial Automation through AutomationM...Luca Berardinelli
Data exchange is a critical issue within the multi-disciplinary engineering process of cyber physical production systems (CPPS).
AutomationML (AML) is an emerging standard in the this field to represent and exchange artifacts between heterogeneous engineering tools used in different domains, such as mechanical, electrical, and software engineering. However, in addition, the interoperability of different exchange standards may be needed in order to integrate even further tools in current tool chains. For instance, the Performance Model Interchange Format (PMIF) is a common representation devised in the performance engineering domain for model-based system performance analysis and simulation based on Queueing Network Models (QNM). Of course, such aspects are also of particular interest when designing a CPPS.
This work investigates, with the help of a case study, the combination of AML and PMIF as an enabling step towards an early performance validation of CPPS. By this, we close the current gap between CPPS engineering and performance engineering standards.
"Keynote - Preserving Software: Challenges and Opportunities for Reproducibility of Science and Technology"
By Roberto Di Cosmo, Irill for ScilabTEC 2015
"Conventional and decentralized PID controllers applied to a multivariable aerothermic process"
By Mustapha Ramzi, LASTIMI Laboratory - University Mohammed V of Rabat for ScilabTEC 2015
Scilab/Xcos pour l'enseignement des sciences de l'ingénieurScilab
Ce livret, réalisé avec le soutien d'Inria et co-écrit par Scilab Enterprises et des enseignants, est une introduction pratique et didactique à l’utilisation de Scilab / Xcos pour l’enseignement et l’apprentissage des sciences de l’ingénieur en section S-SI ou STIDD, au lycée et dans l'enseignement supérieur.
"Material testing and hyperelastic material model curve fitting for Ogden, Polynomial and Yeoh models"
By Michael Rackl, Technische Universität München for ScilabTEC 2015
Modeling an ODE: 3 different approaches - Part 3Scilab
In this tutorial we show how to model a physical system described by ODE using the Modelica extensions of the Xcos environment. The same model has been solved also with Scilab and Xcos in two previous tutorials.
Customizing Xcos with new Blocks and PaletteScilab
In this tutorial, we show how to create and customize Xcos blocks and palettes. Moreover, we use the "Xcos toolbox skeleton" for a better result. The LHY model in Xcos scheme (already developed in other tutorials) is used as a starting point.
Despite significant scientific research, systematic performance engineering techniques are still hardly used in industry, as many practitioners rely on ad-hoc performance firefighting. It is still not well understood where more sophisticated performance modeling approaches are appropriate and the maturity of the existing tools and processes can be improved. While there have been several industrial case studies on performance modeling in the last few years, more experience is needed to better understand the constraints in practice and to optimize existing tool-chains.
I gave a talk summarizing six years of performance modeling at ABB. In three projects, different approaches to performance modeling were taken, and experiences on the capabilities and limitations of existing tools were gathered. The talk reports on several lessons learned from these projects, for example the need for more efficient performance modeling and the integration of measurement and modeling tools.
Pitfalls of machine learning in productionAntoine Sauray
Going from POC to production with Machine Learning can lead to many unexpected problems. We explore some of them in this presentation at the Nantes Machine Learning Meetup.
Команда Data Phoenix Events приглашает всех, 17 августа в 19:00, на первый вебинар из серии "The A-Z of Data", который будет посвящен MLOps. В рамках вводного вебинара, мы рассмотрим, что такое MLOps, основные принципы и практики, лучшие инструменты и возможные архитектуры. Мы начнем с простого жизненного цикла разработки ML решений и закончим сложным, максимально автоматизированным, циклом, который нам позволяет реализовать MLOps.
https://dataphoenix.info/the-a-z-of-data/
https://dataphoenix.info/the-a-z-of-data-introduction-to-mlops/
FutureLink | Strategic Tooling Decisions in ALM Engineering: Migrate or Coexi...Intland Software GmbH
This talk was presented by Taha Boulaguigue (FutureLink) at Intland Connect: Annual User Conference 2020 on 22 Oct 2020. To learn more, visit: https://intland.com/intland-connect-annual-user-conference-2020/
On The Evolution of CAEX: A Language Engineering PerspectiveLuca Berardinelli
CAEX is one of the most promising standards when it comes to data exchange between engineering tools in the production system automation domain. This is also reflected by the current emergence of AutomationML which uses CAEX as its core representation data format. Having such standards at hand, the question arises how to deal with the evolution of such standards as is currently happening with the transition from CAEX 2.15 to CAEX 3.0.
In this work, we take a language engineering point of view to the evolution of engineering data formats. In particular, we present how CAEX can be formulated in a model-based framework which allows to reason about evolution of the data format as well as its impact on the data stored in such evolving formats. By this, not only the migration process of existing data to the new format version is possible, but also a more theoretical investigation on information preservation is possible. We demonstrate the approach by the concrete case of the upcoming CAEX evolution.
Integrating Performance Modeling in Industrial Automation through AutomationM...Luca Berardinelli
Data exchange is a critical issue within the multi-disciplinary engineering process of cyber physical production systems (CPPS).
AutomationML (AML) is an emerging standard in the this field to represent and exchange artifacts between heterogeneous engineering tools used in different domains, such as mechanical, electrical, and software engineering. However, in addition, the interoperability of different exchange standards may be needed in order to integrate even further tools in current tool chains. For instance, the Performance Model Interchange Format (PMIF) is a common representation devised in the performance engineering domain for model-based system performance analysis and simulation based on Queueing Network Models (QNM). Of course, such aspects are also of particular interest when designing a CPPS.
This work investigates, with the help of a case study, the combination of AML and PMIF as an enabling step towards an early performance validation of CPPS. By this, we close the current gap between CPPS engineering and performance engineering standards.
"Keynote - Preserving Software: Challenges and Opportunities for Reproducibility of Science and Technology"
By Roberto Di Cosmo, Irill for ScilabTEC 2015
"Conventional and decentralized PID controllers applied to a multivariable aerothermic process"
By Mustapha Ramzi, LASTIMI Laboratory - University Mohammed V of Rabat for ScilabTEC 2015
Scilab/Xcos pour l'enseignement des sciences de l'ingénieurScilab
Ce livret, réalisé avec le soutien d'Inria et co-écrit par Scilab Enterprises et des enseignants, est une introduction pratique et didactique à l’utilisation de Scilab / Xcos pour l’enseignement et l’apprentissage des sciences de l’ingénieur en section S-SI ou STIDD, au lycée et dans l'enseignement supérieur.
"Material testing and hyperelastic material model curve fitting for Ogden, Polynomial and Yeoh models"
By Michael Rackl, Technische Universität München for ScilabTEC 2015
Modeling an ODE: 3 different approaches - Part 3Scilab
In this tutorial we show how to model a physical system described by ODE using the Modelica extensions of the Xcos environment. The same model has been solved also with Scilab and Xcos in two previous tutorials.
Customizing Xcos with new Blocks and PaletteScilab
In this tutorial, we show how to create and customize Xcos blocks and palettes. Moreover, we use the "Xcos toolbox skeleton" for a better result. The LHY model in Xcos scheme (already developed in other tutorials) is used as a starting point.
Despite significant scientific research, systematic performance engineering techniques are still hardly used in industry, as many practitioners rely on ad-hoc performance firefighting. It is still not well understood where more sophisticated performance modeling approaches are appropriate and the maturity of the existing tools and processes can be improved. While there have been several industrial case studies on performance modeling in the last few years, more experience is needed to better understand the constraints in practice and to optimize existing tool-chains.
I gave a talk summarizing six years of performance modeling at ABB. In three projects, different approaches to performance modeling were taken, and experiences on the capabilities and limitations of existing tools were gathered. The talk reports on several lessons learned from these projects, for example the need for more efficient performance modeling and the integration of measurement and modeling tools.
Pitfalls of machine learning in productionAntoine Sauray
Going from POC to production with Machine Learning can lead to many unexpected problems. We explore some of them in this presentation at the Nantes Machine Learning Meetup.
Команда Data Phoenix Events приглашает всех, 17 августа в 19:00, на первый вебинар из серии "The A-Z of Data", который будет посвящен MLOps. В рамках вводного вебинара, мы рассмотрим, что такое MLOps, основные принципы и практики, лучшие инструменты и возможные архитектуры. Мы начнем с простого жизненного цикла разработки ML решений и закончим сложным, максимально автоматизированным, циклом, который нам позволяет реализовать MLOps.
https://dataphoenix.info/the-a-z-of-data/
https://dataphoenix.info/the-a-z-of-data-introduction-to-mlops/
FutureLink | Strategic Tooling Decisions in ALM Engineering: Migrate or Coexi...Intland Software GmbH
This talk was presented by Taha Boulaguigue (FutureLink) at Intland Connect: Annual User Conference 2020 on 22 Oct 2020. To learn more, visit: https://intland.com/intland-connect-annual-user-conference-2020/
Automating Complex High-Volume Technical Paper and Journal Article Page Compo...dclsocialmedia
SAE International is a global association of more than 138,000 engineers and related technical experts in the aerospace, automotive and commercial-vehicle industries. Annually, SAE organizes and manages an industry conference, its World Congress and Exhibition, where thousands of technical papers and journal articles are presented as part of the conference program. Leading up to the Word Congress, the technical papers and journal articles are reviewed for compliance to SAE publishing requirements and published for print and made available online in a very short time-frame. This paper describes how SAE evolved the production cycle from a less than efficient XSL-FO based process to a highly automated process leveraging NLM XML, XSLT and Adobe InDesign resulting in productivity gains and higher quality output. This paper will take you through the evolution of this project and talk to future enhancements aimed at driving additional benefits.
Recording: https://meetups.mulesoft.com/e/mcws7r/
Speakers:
How to adopt Sustainable Engineering Practices with MuleSoft (Tereze Gaile)
Building an API Community that Developers actually want to visit (Dan Henry)
Host: Angel Alberici
Systematic decision support for architectural design decisions is a major concern for software architects of evolving service-oriented systems. In practice, architects often analyse the expected performance and reliability of design alternatives based on prototypes or former experience. Model-driven prediction methods claim to uncover the tradeoffs between different alternatives quantitatively while being more cost-effective and less error-prone. However, they often suffer from weak tool support and focus on single quality attributes. Furthermore, there is limited evidence on their effectiveness
based on documented industrial case studies. Thus, we have applied a novel, model-driven prediction method called Q-ImPrESS on a large-scale process control system consisting of several million lines of code from the automation domain to evaluate its evolution scenarios. This presentation reports our experiences with the method and lessons learned. Benefits of Q-ImPrESS are the good architectural decision support and comprehensive tool framework, while one drawback is the time-consuming data
collection.
In Information and Communication Technology (ICT) a ‘deliverable’ may be either software (perceived as an ‘output’) or a service (perceived as an ‘outcome’). On the one hand, the differences between software and service have led to the design of parallel models and lifecycles with more commonalities than differences, thereby not supporting the adoption of different frameworks. For instance, a software project could be managed applying best practices for services (e.g. ITIL), while some processes (e.g. Verification & Validation) are better defined in models of the Software Management domain. Thus, this paper aims at reconciling these differences and provides suggestions for a better joint usage of models/frameworks. To unify existing models we use the LEGO approach, which aims at keeping the element of interest from any potential model/framework for being inserted in the process architecture of the target Business Process Model (BPM) of an organization, strengthening the organizational way of working. An example of a LEGO application is presented to show the benefit from the joint view of the ‘software + service’ sides as a whole across the project lifecycle, increasing the opportunity to have many more sources for this type of improvement task.
Development to Operations (DevOps) is driving a profound impact on the global IT sector. IT vendors that realize DevOps’ full potential are more agile in providing new products and services under the label “DevOps inside” at an ever increasing pace. With the growing number of product choices, conflicting definitions and competing services, you may often encounter confusion while making complex decisions, delaying time to market. You at times may be unsure about how to deploy DevOps and get the most out of the solutions and tools available. Are you looking to master the DevOps "Fog?"
Learn new and trending innovations through the success of others during this informative session, and about tools and practices in the VMware world that will lead you to competitive advantage.
Why electric vehicles need model-based design?
Because of the rising complexity in new vehicles, model-based design & systems engineering is needed to cascade the requirements and trace back any modification along the engineering lifecycle. Find out more in this presentation of a customer case about electric motor optimization.
Keynote of the French Space Agency CNES on the Asteroidlander MASCOT boarding the Hayabusa2 mission in collaboration with the Japanese Space Agency JAXA and the German Aerospace Center DLR
Faster Time to Market using Scilab/XCOS/X2C for motor control algorithm devel...Scilab
Rapid Prototyping becomes very popular for faster algorithm development. With a graphical representation of the algorithm and the possibility to simulate complete designs, engineers can help to reduce the time to market. A tight integration with MPLAB-X IDE allows the combination with standard C-coding to easily get mass production code. This solution was used to optimise a sensorless field oriented controlled PMSM motor driven pump efficiency. A model for closed loop simulation was developed using X2C blocks [1][2] for the FOC algorithm based on the existing application note AN1292 [3]. Enhancements to the original version were implemented and verified with simulation. The X2C Communicator was used to generate code of the new algorithm. With the online debugging capabilities and the scope functionality the algorithm was further tuned and optimized to achieve the highest possible efficiency of the pump.
Scilab and Xcos for Very Low Earth Orbits satellites modellingScilab
Very Low Earth Orbits are orbits in altitudes lower than 450 km. The interaction between the atmosphere particles and the surfaces of the spacecraft is responsible for the aerodynamic torques and forces. Simulating several aspects of the performance of a satellite flying in VLEO is very important to make decisions about the design of the spacecraft and the mission.
X2C -a tool for model-based control development and automated code generation...Scilab
Peter Dirnberger, Stefan Fragner
Nowadays, the market demands compact, stable, easy maintain-and customizable embedded systems. To meet these requirements, afast, simple and reliable implementation of control algorithms is crucial. This paper demonstrateshow model-based design with the help of Scilab/Xcosand X2C, developed by LCM,simplifiesand speedsup the development and implementation of controlalgorithms. As an example, acontrol schemefor a bearingless motoris presented.
A Real-Time Interface for Xcos – an illustrative demonstration using a batter...Scilab
As part of an EU-founded research project, the Scilab based development tool LoRra (Low-Cost Rapid Control Prototyping Platform) was created. This allows the realization of the continuously model based and highly automated Rapid Control Prototyping (RCP) design process for embedded software within the Scilab / Xcos environment (cf. Figure 1). Based on the application battery management system (BMS), this paper presents a Real-Time interface for Scilab.
Aircraft Simulation Model and Flight Control Laws Design Using Scilab and XCosScilab
The increasing demand in the aerospace industry for safety and performance has been requiring even more resourceful flight control laws in all market segments, since the airliners until the newest flying cars. The de facto standard for flight control laws design makes extensive use of tools supporting numerical computing and dynamic systems visual modeling, such that Scilab and XCos can nicely suit this kind of development.
Multiobjective optimization and Genetic algorithms in ScilabScilab
In this Scilab tutorial we discuss about the importance of multiobjective optimization and we give an overview of all possible Pareto frontiers. Moreover we show how to use the NSGA-II algorithm available in Scilab.
Collapsing Narratives: Exploring Non-Linearity • a micro report by Rosie WellsRosie Wells
Insight: In a landscape where traditional narrative structures are giving way to fragmented and non-linear forms of storytelling, there lies immense potential for creativity and exploration.
'Collapsing Narratives: Exploring Non-Linearity' is a micro report from Rosie Wells.
Rosie Wells is an Arts & Cultural Strategist uniquely positioned at the intersection of grassroots and mainstream storytelling.
Their work is focused on developing meaningful and lasting connections that can drive social change.
Please download this presentation to enjoy the hyperlinks!
This presentation, created by Syed Faiz ul Hassan, explores the profound influence of media on public perception and behavior. It delves into the evolution of media from oral traditions to modern digital and social media platforms. Key topics include the role of media in information propagation, socialization, crisis awareness, globalization, and education. The presentation also examines media influence through agenda setting, propaganda, and manipulative techniques used by advertisers and marketers. Furthermore, it highlights the impact of surveillance enabled by media technologies on personal behavior and preferences. Through this comprehensive overview, the presentation aims to shed light on how media shapes collective consciousness and public opinion.
Mastering the Concepts Tested in the Databricks Certified Data Engineer Assoc...SkillCertProExams
• For a full set of 760+ questions. Go to
https://skillcertpro.com/product/databricks-certified-data-engineer-associate-exam-questions/
• SkillCertPro offers detailed explanations to each question which helps to understand the concepts better.
• It is recommended to score above 85% in SkillCertPro exams before attempting a real exam.
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• SkillCertPro assures 100% pass guarantee in first attempt.
4. CEA – FRENCH ALTERNATIVE ENERGIES AND ATOMIC ENERGY COMMISSION
Created in 1945 by the Général De GAULLE
! Its goal is to master the atom:
! Energy
! Defence
French government-founded technological research organization
juin 29, 2015 CEA | 10 AVRIL 2012 | PAGE 4
Technology for
health and
information
DefenceEnergy
Low
Carbon
Research
Technology for
health and
information
DefenceEnergy
Low
Carbon
ResearchResearch
5. CEA/CESTA
CEA/CESTA is an actor of the French Nuclear deterrence
Guaranty the performances of complex systems using simulation
Challenges :
! Many physics to study
! Mechanics
! Aerodynamics
! Electromagnetism
! …
! Many users
! Many different data and data types
! Comparison tests - computations/simulations
juin 29, 2015 CEA | 10 AVRIL 2012 | PAGE 5
6. DEVELOPMENT STRATEGIES
We used several software
! Internal development
! Well-known publishers (in scientific domains)
! And, more and more, Open-source Approach
Why the Open-source?
! “It’s the best choice” Roberto Di Cosmo
! Master the entire sources of our computing codes
! Sustainability
! Taking part of open-source software
development roadmap
juin 29, 2015 CEA | 10 AVRIL 2012 | PAGE 6
7. OPEN SOURCE EXEMPLES AT CEA/CESTA
! Most of GUI and simulation environment designed and developed from (and with) eclipse
[Paprika: Rapid UI Development of Scientific Dataset Editors for High Performance Computing – D.Nassiet, Y.Livet, M. Palyart and D.
Lugato, SDL Forum 2011: Springer, ISBN 978-3-642-25264-8 p 69-78]
! Scientific visualization
! but still missing Scilab ! J
juin 29, 2015 CEA | 22 MAY 2015 | PAGE 7
9. METHODOLOGY
CEA/CESTA in collaboration with Scilab Enterprises
conducted a study to assess the appropriateness of Scilab
software besides the use of Matlab ® by the users.
! This study has been divided into several tasks:
! Analysis of the current Matlab use (audit and interviews)
! Training
! Development of a prototype from an existing Matlab application (CASDEM)
! 6 months project
! 50+ engineers implicated
! Several domains addressed:
! Data processing
! Simulation
! Specific applications
juin 29, 2015 CEA | 10 AVRIL 2012 | PAGE 9
10. AUDIT & INTERVIEWS
3-months project schedule
! Presentation of Scilab and Scilab Enterprises
! Questionnaire sent to the 50 Matlab users
! Meetings & Interviews (by group or individually)
! Feedback reports
Objectives
! Understand the use of numerical computation and the applications at CEA/CESTA
! Evaluation of Matlab and the uses of Matlab toolboxes
! Check and evaluate the needs
! Check the possibilities given by Scilab to replace Matlab
! Identify the potential lacks of specific features
juin 29, 2015 | PAGE 10CEA | 22 MAY 2015
11. AUDIT & INTERVIEWS
Feedbacks (1/2)
! Noted differences between Matlab and Scilab:
! Scilab interesting capabilities (e.g. processing strings)
! Some missing functions and functionalities in Scilab for CEA/CESTA uses
● object-oriented programming
● 2.1 GB memory limitation
● no GUI modeler / builder
● no debugger
! A significant workload, if we choose to migrate the amount of small users-codes
! Positive feedback from engineers on using Scilab in response to their need of
development and migration
juin 29, 2015 CEA | 22 MAY 2015 | PAGE 11
12. AUDIT & INTERVIEWS
Feedbacks (2/2)
! Migration issues rely on:
! Change of habit more than a real difficulty
! Knowledge of the differences between Matlab and Scilab
! Differences between Matlab and Scilab can be reduced by:
! Using equivalent function in Scilab
! Developing new features for Scilab (development costs to estimate)
! Customized training
juin 29, 2015 CEA | 22 MAY 2015 | PAGE 12
13. TRAININGS
On-site trainings
40 trainees
2 trainers
8 training sessions
! Scilab Enterprises has conducted training sessions at CEA/CESTA for Matlab users to:
! Discover Scilab software environment and capabilities
! Discover Xcos modeling and simulation capabilities
! Develop Scilab and Xcos ATOMS modules
! Trainings have been customized to suit CEA/CESTA needs and have been oriented to
highlight best Scilab practices regarding former Matlab user’s habits
juin 29, 2015 CEA | 22 MAY 2015 | PAGE 13
14. AND TECHNICAL SUPPORT
Support to Scilab installation & deployment
! Support to package automatic Scilab deployment
! Support to install Scilab MPI (parallelization)
ATOMS Server
! Deployment of a private CEA/CESTA ATOMS server:
! Mirror of Scilab public ATOMS server,
! Making ATOMS modules available on the intranet CEA/CESTA networks,
! Possibility to upload and deploy private internal ATOMS modules.
! Support and assistance to network administrators.
juin 29, 2015 CEA | 22 MAY 2015 | PAGE 14
15. PROOF OF CONCEPT
Migrating CASDEM application
! Application developed in Matlab for test data processing field in thermomechanical
environments.
Work
! The differences in programming implied to:
! Redesign GUI
! Adapt graphical interactions
Results
! Scilab application with same functionalities
! Same numerical results up to 10 -13
! Scilab CASDEM module that can be published in ATOMS private network (not possible
with Matlab)
juin 29, 2015 CEA | 10 AVRIL 2012 | PAGE 15
19. BALANCE SHEET
Thanks to Scilab Enterprises and the proximity and
reactivity of their development team!
CEA/CESTA gains:
! A best knowledge of the different uses and user’s needs
! An effective skills transfer
! The migration of a comprehensive application conducted in a couple of months
! And last but not least: Scilab core evolutions!!! (new graphics interactions for example)
What could come next?
! Support
! Trainings
! Functions, functionalities and additional modules developments
! Other applications migrations
And what next next?
! Scilab 6.x with no memory limitation… … and debugger ?!? J
juin 29, 2015 CEA | 22 MAY 2015 | PAGE 19
20. Direction
Département
Service
Commissariat à l’énergie atomique et aux énergies alternatives
Centre de Saclay | 91191 Gif-sur-Yvette Cedex
T. +33 (0)1 XX XX XX XX | F. +33 (0)1 XX XX XX XX
Etablissement public à caractère industriel et commercial | RCS Paris B 775 685 019
juin 29, 2015
| PAGE 20
CEA | 10 AVRIL 2012
Thank You!