Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.aei.2011.07.009
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dc.titleDesign explorations of performance driven geometry in architectural design using parametric modeling and genetic algorithms
dc.contributor.authorTurrin, M.
dc.contributor.authorVon Buelow, P.
dc.contributor.authorStouffs, R.
dc.date.accessioned2016-06-02T09:25:12Z
dc.date.available2016-06-02T09:25:12Z
dc.date.issued2011-10
dc.identifier.citationTurrin, M., Von Buelow, P., Stouffs, R. (2011-10). Design explorations of performance driven geometry in architectural design using parametric modeling and genetic algorithms. Advanced Engineering Informatics 25 (4) : 656-675. ScholarBank@NUS Repository. https://doi.org/10.1016/j.aei.2011.07.009
dc.identifier.issn14740346
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/124969
dc.description.abstractIn this paper we discuss the benefits derived by combining parametric modeling and genetic algorithms to achieve a performance oriented process in design, with specific focus on architectural design. The key role played by geometry in architecture is discussed in relation to performance oriented design, in which evaluations based on engineering criteria are integrated into the conceptual phase of the design. The performance attained by a specific geometric solution is considered along with its complexity in an interdisciplinarity process. A specific case study using large roofs is presented as an example. Enabling the designer to automatically generate a large range of alternative design solutions is a great advantage offered by parametric modeling in supporting geometric design explorations. However, this in turn presents the difficulty of how to evaluate the resulting myriad of generated alternatives. ParaGen is presented as a tool to support the exploration of the parametric design alternatives. ParaGen combines parametric modeling, performance simulation software and genetic algorithms, together with a database to store and retrieve the solutions for subsequent exploration. The design exploration is enhanced by means of the interaction of the designer with the process. This serves two objectives. Firstly, it addresses the genetic algorithm based creation of design solutions, while still focusing on a given fitness function. Secondly, it facilitates knowledge extraction from the generated solutions. A description of the tool and its possible uses by designers is provided. Applications of this tool are illustrated for both education and research, with specific reference to two examples in the field of modular long span roofs. The first case study has been developed as part of a teaching exercise in which ParaGen is used to explore the morphology of a dome based on structural performance. The second case study is derived from a research project which deals with solar energy transmission, and concerns the solar heat gain and daylight transmittance of a long span roof. © 2011 Elsevier Ltd. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.aei.2011.07.009
dc.sourceScopus
dc.subjectExploration
dc.subjectGenetic algorithms
dc.subjectIntegrated design
dc.subjectOptimization
dc.subjectParametric modeling
dc.subjectPerformance oriented design
dc.typeArticle
dc.contributor.departmentARCHITECTURE
dc.description.doi10.1016/j.aei.2011.07.009
dc.description.sourcetitleAdvanced Engineering Informatics
dc.description.volume25
dc.description.issue4
dc.description.page656-675
dc.identifier.isiut000296549100008
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