Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.aei.2011.07.009
Title: Design explorations of performance driven geometry in architectural design using parametric modeling and genetic algorithms
Authors: Turrin, M.
Von Buelow, P.
Stouffs, R. 
Keywords: Exploration
Genetic algorithms
Integrated design
Optimization
Parametric modeling
Performance oriented design
Issue Date: Oct-2011
Citation: Turrin, 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
Abstract: In 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.
Source Title: Advanced Engineering Informatics
URI: http://scholarbank.nus.edu.sg/handle/10635/124969
ISSN: 14740346
DOI: 10.1016/j.aei.2011.07.009
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