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  • 1. Mohamed Nour, Ossama Hosny and Ahmed Elhakeem / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 6, November- December 2012, pp.411-418 A BIM based Energy and Lifecycle Cost Analysis/Optimization Approach Mohamed Nour, Ossama Hosny and Ahmed Elhakeem The American University in CairoAbstract This paper reports on ongoing research building design(s), i.e. a library of objects. Thesework within the area of building lifecycle cost alternatives include different types of walls,analysis including energy optimization. It windows and slabs that constitute the buildingsaddresses the interoperability problem between external envelopedifferent AEC domain applications within thecontext of a BIM based lifecycle cost analysis /optimization at the design stage of a building. Itdiscusses the available interoperability optionsbetween existing mainstream softwareapplications and identifies areas where there areneeds for further interoperability tools thatfacilitate the production of energy efficient andsustainable designs. A double solution strategy(short and long term) is adapted to achieve theobjectives of the lifecycle costanalysis/optimization process for developedprototype building(s). The short term strategyaims at optimizing the design parameters ofsuggested building(s) prototypes within thecollaborative multidisciplinary teamworkenvironment with architects, structural andHVAC engineers. In the meantime, it points outthe interoperability shortcomings and proposesthe development of missing interoperability Figure 1: The BIM based data exchange through asolutions. The long term strategy targets the central IFC/BIM data hubdevelopment of such solutions to be deployedamong mainstream software applications with In return, the research team has set up athe aim of reaching an automated BIM based BIM-platform (central data hub) [1] forround-trip lossless data exchange by bridging the manipulating the IFC/BIM model in terms ofgap between existing interoperability islands. reading, writing and visualization together with an optimization engine that is capable of manipulatingKeywords: BIM, Lifecycle Cost Analysis, Energy energy simulation software input files and parsingSimulation, Genetic Algorithm its output files. Several architectural designs are evaluated according to building energy consumption1. Introduction cost dimension and results are incorporated to the The research work in this paper is related to lifecycle cost model to reach an optimum trade-offa BIM- approach for optimizing the total lifecycle between energy and cost resulting in an optimumcost of a building. It focuses on the energy design.component of the building lifecycle cost parameters. Lifecycle cost analysis is considered to be aIt is based on a BIM based data exchange scenario, powerful tool that facilitates the proper evaluationwhere the architect sends a request through an open and optimization of different building/systemBIM platform (model server) to the lifecycle cost designs. Traditionally, evaluation of such systems isteam to analyze/optimize the lifecycle costs carried out on the basis of its investment costattributed to his building design as shown in figure neglecting other costs such as operation,1. All communication between project disciplines maintenance and repair costs [2] from the Nationaltake place through the central model server in the Institute of Standards and technology has presentedform of IFC files. The architectural team provides a description and a methodology for applyingthe LCC team with a set of predefined alternatives lifecycle cost analysis. As building lives areof the building components. These alternatives considered virtually long, all their life associatedrepresent a main selection pool to configure a costs are to be considered. These costs are: (1) 411 | P a g e
  • 2. Mohamed Nour, Ossama Hosny and Ahmed Elhakeem / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 6, November- December 2012, pp.411-418Initial costs; (2) Utilities Costs; (3) Operation, number of possibilities will increase dramaticallymaintenance and repair costs; (4) Replacement many folds showing the need for not only ancosts; and (5) Residual Values [2]. Details about the optimization technique but also to a non-traditionalimportance of lifecycle cost analysis and the need one. GAs is used in this research as one of thefor optimization and its modeling challenges can be evolutionary approaches that proved to be efficientfound in [3], [4], [5]. The importance regarding in such type of combinatorial problems.sustainability and energy efficient solutions with 2.2. Interoperability Challengesrelevance to lifecycle cost is discussed by [3], [6]. The main objective of the LCC team in this paper is to incorporate the total annual energy cost of the2. Building design optimization prototype building(s) in the LCC model using the2.1. Modeling options and optimization BIM/IFC input and share results for decision challenges making with other project team members. Predicting Trying to optimize a building design from the annual energy however, is a challenging taskenergy/cost point of view -within the context of a that needs energy simulation using weather data,specific architectural form- can be seen as a thermal properties of used materials for differentselection problem for the optimum types of its building components and information regarding theenvelop components. These components are mainly HVAC and other appliances and their expectedthe roof, exterior walls and windows where the schedule of use. It was envisaged that the outputselection is from a pre-defined list of available from BIM authoring tools such as Revit [7] wouldalternatives for each envelop component. As a be taken as an input to the energy analysis tool usedcommon practice, architects most probably select all by the Architectural team (Energy Plus) in the formwindows from the same type and all wall segments of an IFC STEP-21 file [8]. Despite the existence offrom one type too. Such a design approach an increasing number of Building Information(modeling option) from optimization point of view Models that are linked to energy performanceresults in three variables that need to be determined simulation models and the existence of models thatnamely the roof type, the windows type and the are linked to BIM authoring tools (CAD) withinexterior walls type. The corresponding optimum proprietary environments, there are still limitationsdesign to this modeling option can be reached to the current BIM tools for energy analysis in termsthrough exhaustive search by trying all possible of interoperability and quality of the results. [9].combinations, which are limited. With the fact that By investigating the interoperability status of such athe windows and wall segments in the building are data exchange process, the following shortcomingsdistributed over various building facades and floors, were found:they are subjected to different degrees of weather 94 wall elements 24 windowsseverities and solar impacts. Accordingly, theoptimum solution might result when using acombination of different types of windows and walls +within the building. Wall segments or windows that Possible Designsare less subjected to the sun might need lessinsulation compared to those that are subjected to = 943 x 243 =more sun. This may result in cost saving which is 13824 x 830584 =significant over the building’s lifecycle. Consideringsuch modeling option which handles each window 11,481,993,216or wall segment as a separate entity (i.e., variable)that can be assigned any type will result in a hugenumber of possible combinations or building Wall Types Window Typesdesigns. Even with few alternatives for each envelop Variables: 94 Variables: 24component, this will results in a number of (individual elements) (individual windows)combinations that cannot be examined, raising the Options: 3 for each Options: 3 for eachneed for a true optimization procedure. Figure 2shows an illustration with only three window element windowalternatives and three wall alternatives using a real Figure 2: Illustration: need and optimizationtwo-story building with 24 windows and 94 wall challengessegments. The number of possible designs will be11,481,993,216 designs. As shown in the figure the 1. Often BIM models need to be complemented ornumber of possible designs equals to the number of even recreated to add information required forwall segments raised to the power of possible wall energy analysis.alternatives multiplied by the number of windows 2. Software like AutoDesk Green Building Studio/raised to the power of possible window alternatives. Revit or Graphisoft Eco Designer / ArchiCADAccordingly with any additional alternative the 412 | P a g e
  • 3. Mohamed Nour, Ossama Hosny and Ahmed Elhakeem / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 6, November- December 2012, pp.411-418 are proprietary developments that are hardly The implementation of the optimization interoperable outside their own environments. process is discussed in this paper through a real case3. There is no typical and well established analysis study example. A two-story building was provided method and guidelines for the BIM/IFC based by the Architecture team and three alternatives for energy performance assessment. walls and another three for windows were also4. Energy simulation tools like EnergyPlus do not determined by the team. The building consists of 24 accept IFC files as a direct input. windows and 94 wall segments. The IDF file5. All workarounds using gbXML[10] as an corresponding to the initial design was created from intermediate exchange format result in a one way the building IFC through gbXML manual communication channel to the Energy simulation transformation as discussed earlier. tool (EnergyPlus) where results are not integrated or further communicated to other design team members through the BIM model.6. The one way communication channel is not suitable for optimization which requires a structured procedure that enables continuous changes (back and forth) in the design variables and the assessment of corresponding LCC including the impact on energy consumption. Figure 3: Mapping IFC data to EnergyPlus IDF3. Solution Approach format The solution approach to the problemsmentioned in the previous sections was to adapt twostrategies. 1) A short term strategy to keepmultidisciplinary collaborative work going on withother project teams without time delays due towaiting for software developments to end. Thisstrategy provides short term instant solutions andworkarounds to the previously mentionedinteroperability problems to maintain the pace ofwork delivery. 2) A long term strategy based ondeveloping software tools that are capable of being Figure 4: G.A. manipulation of references tointegrated to the mainstream software applications construction & fenestration types in IDF filesto bridge the gaps between existing islands of using unprocessed markersautomation. After adding the HVAC data to the IDF file, it3.1. Short term strategy becomes a representation for the building design in The short term strategy depends on making the format that suits the energy assessment usinguse of what is currently available by mainstream Energy Plus. From the case dependent IDF file, thesoftware applications and developing interfaces and LCC team created a generic IDF file by adding allsoftware tools that are capable of managing alternatives as a selection library. The LCC teaminformation exchange specific to this research assessed the unit LCC for the different envelopproject. A main problem was the integration of the components’ alternatives. The quantities of theenergy simulation tool (EnergyPlus) inside the GA different components are extracted from the IDF filebased cost optimization environment. A user basic geometrical information. Once a design or aninterface had to be developed on top of EnergyPlus IDF file is adapted during the optimization process,in order to be integrated to the GA routine of work. energy simulation will be responsible for providingMeanwhile, to keep on with the work delivery pace, the annual energy demand in kWh which can easilythe BIM/IFC model was converted in a be converted to equivalent building operating cost.unidirectional way through gbXML to an IDF file asillustrated in figure 3. It was necessary to add all 3.1.2. Mapping the GA procedure in Energymissing HVAC and energy simulation relevant Plus simulationproperties of materials and their layering systems to First, a GA java generic library wasthe generated IDF file which are added with the help developed as the core optimization engine as aof the Architectural team. The optimization package of abstract classes that need to bemechanism can be schematically viewed in figure 4. implemented on specific optimization problems through inheritance. It was tested and verified using3.1.1.Optimization Implementation known solutions of mathematical equations. The java classes of the GA tool were extended as shown 413 | P a g e
  • 4. Mohamed Nour, Ossama Hosny and Ahmed Elhakeem / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 6, November- December 2012, pp.411-418in the UML diagram in figure 5 to conduct energysimulations of automatically generated IDF filesusing EnergyPlus at both the initial populationcreation stage and at the evolution stages. GA functions through three main entities:(1) genes to represent the variables; (2) achromosome which represents a solution in view ofvariables values. Hence, a chromosome consists of anumber of genes; and (3) an initial population ofrandomly created solutions (i.e., chromosomes).These three entities are then used in the GAevolution process by calculating the relative fitnessof the population and accordingly randomlyselecting parents for crossover/mutation. For thecase study on hand, each chromosome contained118 genes representing the elements of the buildingenvelop (24 for windows and 94 for wall segments).The values of these genes are integers between 1and 3 corresponding to the three possiblealternatives of walls and windows. Within the EnergyPlus simulation, each Figure 6: The representation of the set ofchromosome is represented as an IDF file and each alternative elements constituting the buildinggene within a chromosome represents an element on envelop through an imbedded IDF librarythe building outer envelope as shown in figure 6 andfigure 7.The IDF GA Energy optimization tooldepends on putting non processed markers in theIDF file at places where variables (genes) arerequired to be changed during the optimizationprocess as shown in figure 4. An initial populationof 200 chromosomes was generated using thedifferent wall and window types. Thesechromosomes(designs) were then evaluated. Figure 7: The representation of GA chromosomes by IDF files and genes by building outer envelope elements The population was further refined using a minimization objective function representing the annual energy consumption of the building design undergoing simulation as well as Lifecycle Cost of the envelop of the building components. The overall fitness of the chromosome was calculated by aggregating all Lifecycle costs together with the average annual energy consumption of the building in monetary units. It is also worth mentioning that all monetary figures are aggregated in their NPVs (Net Present Value). As the lifecycle costs for the building elements are provided in the form of annualFigure 5: A UML diagram showing the Java based price / unit area, it was inevitable to make a quantityG.A. engine library architecture take off from the model to be able to get the cost for each building element (Gene). Consequently the 414 | P a g e
  • 5. Mohamed Nour, Ossama Hosny and Ahmed Elhakeem / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 6, November- December 2012, pp.411-418overall life cycle cost for the building configuration names) according to their relative fitness as shown(Chromosome) is calculated. This quantity take off in figure 8. The best chromosome with the bestcould not be done from the IFC model due to the relative fitness score is chosen and considered thelack of identification of objects in the IFC model best candidate and its gene sequence represents thewith their counterpart objects in the IDD/IDF best reached configuration of the building’s outerEnergyPlus Model. As a solution, quantities were envelope. This configuration is a subset of thecalculated from the geometrical description of the available options provided originally by the designerobjects in the IDF file (3D Cartesian points (architect).constituting polygons). Furthermore, anotherproblem was the calculation of net areas of wallsconstituting the outer envelope of the building giventhat some of such walls included one or morewindow openings. Each window had to be related toits containing wall in order to be able to calculatethe containing walls net surface area. At the process of each chromosomecreation either by random generation or throughcrossovers / mutations GA routines, a correspondingnew IDF is generated for each chromosome. EachIDF file contains assigned references at markersplaces to corresponding genes values determined bythe GA. The experimental prototype started with theinitial random population of 200 chromosomes thatwere evaluated by a multi-core batch simulation ofEnergyPlus that is controlled through a developedinterface linked to the GA tool. Mutations andCrossovers were then conducted at ratios 0.15 : 0.85 Figure 8: Making use of cumulative G.A. runsrespectively. For normal crossover, directed randomselection of the population chromosomes was used. The next main problem was toAt each mutation or crossover process the communicate the simulation results back to theevaluation of the chromosome is done through the designers through an IFC STEP-21 model. This wasgeneration of a new IDF file containing the achieved by making use of two elements:corresponding genes values followed by an 1- The VRML output file of the EnergyPlusEnergyPlus simulation to integrate the annual simulation tool.average total energy consumption cost of the 2- An IFC Java3D based visualization toolbuilding with the rest of the life cycle cost and IFC toolbox by [11].parameters. The GA controlled EnergyPlus engine undergoes simulation iterations until a stopping condition is All GA optimization/ simulation results reached due to nonexistence of further improvementproduced at runtime are kept afterwards in the form of chromosomes fitness as shown in figure 9. Theof chromosomes represented as IDF files together best chromosome represented as an IDF file is thenwith all EnergyPlus simulation output files and a list passed over to a Java3D package that is capable ofcontaining the gene sequence of each chromosome visualizing the IFC model together with theas shown in figure 8. Since EnergyPlus simulation VRML/DXF files (output from EnergyPlus). Bothruns have proven to be a time consuming process, it the IFC/CAD model and the IDF VRML model arewas decided that the results of any simulation run visualized concurrently next to each other on theare kept for later use when starting a new same screen as shown in figure 10 to mapoptimization run to select the best fitting population corresponding elements in both the IDF and IFCfrom all previous runs. If the GA creates a new models. A workflow approval notation is createdchromosome with a gene sequence of values that within the IFC file as shown in appendix “A” &typically coincides with a previously simulated Figure 11 to indicate the need for change that shouldchromosome, then the resulting scores of such a be performed in the CAD model by the designerschromosome are taken over without the need to (architects).repeat the simulation process. The chromosomefitness (evaluation) is obtained through a developed 3.2. The long term strategy*.mtr (EnergyPlus meter file) parser that is capable The long term strategy represents the futureof reading the fitness scores of all chromosomes and development work that aims at developingarranging them in a list (of chromosomes/ IDF file 415 | P a g e
  • 6. Mohamed Nour, Ossama Hosny and Ahmed Elhakeem / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 6, November- December 2012, pp.411-418interoperability tools that can be deployed among 3. There is a need to develop an EnergyPlusthe mainstream software applications to reach an IDD (Input Data Dictionary) / IDF tool box that isAutomated BIM based round-trip data exchange. capable of producing new instances of the IDDThe long term strategy is carried out separately in objects in the IDF file together with relevantorder to have enough time and resources for properties in addition to any HVAC systemdevelopments to be mature enough to be deployed definition and EnergyPlus output variables/metersby people other than its own developers among that represent the output from the carried outmainstream software tools. The discovered simulations.shortages of interoperability tools using open 4. There is a need to enable thestandards like the IFC are considered to be the main communication of simulation results within the IFCkey drivers within the scope of the long term model. In other words, all changes in the buildingstrategy. Among these tools that are being due to changes of simulation parameters have to bedeveloped are: reflected on the BIM model and communicated1. A Java3D based geometry abstraction tool through the IFC STEP-21 exchange format. There is a lack of a software tool that is However, this matter should be carefully managedable to correctly calculate all necessary 2nd, 3rd, 4th and regulated thorough the “Workflow Approval”and 5th level space boundaries [12] [13]. The system dominating the entire design and decisionIFC2X3 utility for ArchiCAD 13 was the only making team communicating through an open BIMcapable commercial software tool of carrying out based platform.this task. In the meantime, Graphisoft did notsupport this in it subsequent versions. Hence, thereis a need for a tool that can generate higher levelspace boundaries from the geometry provided in thecoordination view of the IFC model to generate theneeded IFC space boundaries objects. These objectsare transferred to energy simulation software whilekeeping references to objects in the IFC modelthrough the management of the objects’ GUIDs(Global Unique Identifiers) for later reversemapping of attributes and properties to the IFCmodel.2. An IFC Editor This tool is envisaged to be a graphical userinterface to add all necessary information related tothe HVAC domain and energy simulation. Thisprocess can also be done through the IFC viewer [1][11] before the geometry abstraction stage. In themeantime, there is also a need to manage the layersof materials and their properties in the IFC modeland instantiate their property sets with relevance to Figure 10: Mapping objects between thethe HVAC and energy domains. IDF/VRML model and IFC Figure 11: Returning optimization results using the BIM/ IFC Approval entity as a workflow approval procedureFigure 9: The envisaged BIM based energyanalysis and optimization process 416 | P a g e
  • 7. Mohamed Nour, Ossama Hosny and Ahmed Elhakeem / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 6, November- December 2012, pp.411-418 Cairo), PreProc - IFC Toolbox Version 2.xConclusions (00/11/07), Windows System,Mohamed NOUR.); The paper confirmed the effect of FILE_SCHEMA ((IFC2X3));buildings energy performance on their Life Cycle ENDSEC;Cost and the need for optimization. This was done DATA;using a GA/BIM based solution that has the ability #5 = IFCCALENDARDATE (8, 03, 2011);to select suitable building components among the #10 = IFCAPPROVAL ( windows material layersavailable alternatives to formulate a building in rooms 1,7,15 and 23, have to be changed to typeconfiguration with minimum lifecycle costs 1001, #5, REQUESTED, PreliminaryDesign,including energy consumption. Although the solution should be energy certified,envisaged interoperability potential through current SecondApproval, AP 123XY);ICT technologies seems to be high enough to #530 = IFCWINDOWconduct round-trip data exchange between BIM (0sL9z45hDDsxc4rO4qvf7C, #1275, 1 Vantail -based software applications, this seems not to be the Droit:0.60 m xcase within open BIM environments and is still 0.95 m - Appui en aluminium:0.60 m x 0.95 m -limited to proprietary commercial software Appui en aluminium:182803, $, 0.60environments away from the IFC/BIM model. m x 0.95 m - Appui en aluminium, #16390, #16395,Moreover, this seems to coincide with the 182803, 1.079999999999999,commercial interest of software vendors and their 0.6999999999999991);own market share of such software tools that benefit #550 = IFCWINDOWonly from the integrity of their own proprietary (0sL9z45hDDsxc4rO4qvfV2, #1275, 1 Vantail -environments. Droit:0.60 m xWith relevance to energy simulation with 0.95 m - Appui en aluminium:0.60 m x 0.95 m -EnergyPlus, there is still a need for open tools that Appui en aluminium:183325, $, 0.60are both capable of creating higher level space m x 0.95 m - Appui enboundaries and in the meantime capable of aluminium, #20615, #20620, 183325,managing the IFC-GUID (Global Unique IDs) in 1.079999999999999, 0.6999999999999991);order to enable the reverse mapping process of #575 = IFCRELASSOCIATESAPPROVALenergy relevant data back to corresponding IFC (c72afa6aA31aaA41eeAa31, #570, $, $,model objects and their attributes. (#16020, ), #10);Enabling GA to manipulate energy simulation #580 = IFCACTORROLEparameters related to the BIM objects that constitute (.ELECTRICALENGINEER., ThermalEngineer, the external envelop of buildings proves to be a MFE Thermal Jobsvaluable process that needs to be further developed );and standardized with the aim of incorporating it #590 = IFCAPPROVALACTORRELATIONSHIPinto mainstream software applications. Furthermore, (#585, #10, #580);there are needs to standardize both the developed #595 = IFCPOSTALADDRESS ($, Americantools and the energy simulation process itself as a University Building Main Campus Cairo, $, $,workflow routine in order to be able to harvest the (Main Building,gains behind adopting the BIM technology. Ground Floor, ch. 04), PO BOX 2422, CAIRO, New Cairo, 78065,Acknowledgements Egypt);This publication is based in part on work supported #570 = IFCOWNERHISTORY (#600, #605, $,by Award No. UK - C0015, made by King .NOCHANGE., $, $, #605, 1331512806038Abdullah University of Science and Technology );(KAUST). #585 = IFCPERSON (Architect, KHALED, DEEB, (F., M.), $, $, $,Appendix A: IFC – STEP-21 Extract of the (#595));BIM communication workflow #610 = IFCORGANIZATION (AUC, Arch, $,IFC – STEP-21 Extract of the BIM communication (#580), (#595));workflow #600 = IFCPERSONANDORGANIZATION (#585,ISO-10303-21; #610, (#580));HEADER; #605 = IFCAPPLICATION (#610, 1.0, KAUSTFILE_DESCRIPTION ((AUC_Egypt.,Build Prototype, BUILD-ID);Number of the Ifc 2x interface: 00088 (02-02- …2012)), 2;1); ENDSEC;FILE_NAME (North.ifc, 2012-03-02T13:53:21 END-ISO-10303-21;,(Mohamed Nour), (American University in 417 | P a g e
  • 8. Mohamed Nour, Ossama Hosny and Ahmed Elhakeem / International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 6, November- December 2012, pp.411-418References [12] C. Rose, T. Maile, J. O’Donnell, N. [1] M. NOUR, K. BEUCKE, An open Mrazović, V. Bazjanac, The geometry of platform for processing IFC model thermal zone space boundaries for building versions, Tsinghua Journal of Science and energy performance simulation, Submitted Technology 13 NoS1 ELSEVIER (2008) for publication to Transactions on 126-131. Retrieved from Modeling and Computer Simulation, a http://linkinghub.elsevier.com/retrieve/pii/ publication of the Association for S100702140870138X Computing Machinery (2011). [2] F. Sieglinde, Life cycle cost analysis, [13] V. Bazjanac, Space boundary requirements National Institute of Standards and for modeling of building geometry for Technology (2007). Retrieved from energy and other performance simulation, http://ironwarrior.org/ARE/Materials_Meth CIB W78, Proc. 27th conference, ods/Life-Cycle Cost Analysis.pdf Applications of IT in the AEC Industry [3] T. Nielsen, S. Svendsen, Life-cycle cost Cairo (2010) optimization of buildings with regard to energy use thermal indoor environment and daylight, International Journal of Low Energy and Sustainable Buildings (2002) 1-16. [4] H. Winkler, R. Fecher, L. Tyani, K. Matibe, Cost-benefit analysis of energy efficiency in urban low cost housing, Journal of Development Southern Africa (2002) 593-614. [5] N. Huberman, D. Pearlmutter, A life-cycle energy analysis of building materials of Negev desert, Journal of Energy and Buildings (2007) 837-849. [6] S. Jung, M. Dan, Cost-reliability interaction in life-cycle cost optimization of deteriorating structures, Journal of Structural Engineering, ASCE 130 No. 11 (2007). [7] Autodesk Revit Architecture (2012) http://usa.autodesk.com/adsk/servlet/item?s iteID=123112&id=16841348 [8] ISO 10303 – 21 STEP 2002 Industrial automation systems and integration, Product data representation and exchange part 21: Implementation methods: Clear text encoding for exchange structure (2002). [9] V. Bazjanac, T. Maile, J. ODonnell, N. Marzovic, October Data Environments and processing in semi-automated simulation with EnergyPlus, Proceedings of the CIB W78-W102 2011: International Conference –Sophia Antipolis, France, (2011) 26-28 October. [10] Green Building XML schema gbXML: http://www.gbxml.org. [12.03.2012] [11] M. Nour, K. Beucke, Manipulating IFC model data in conjunction with CAD, Proceedings of CIB w78-2005 22nd Conference on Information Technology in Construction (2005) 253–260: http://itc.scix.net/data/works/att/w78-2005- D4-1-Nour.pdf 418 | P a g e

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