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Sakikhales, M.; Stravoravdis, S.
Publisher: Wessex Institute.
Languages: English
Types: Unknown
Subjects: TH
Identifiers:doi:10.2495/BIM150021
Architecture design practitioners typically generate and assess few design alternatives at the early stages of a project, before converging on a final design. Exploring design alternatives and understanding their impact on building energy performance leads to better performing building solutions. Therefore, any automatic process that gives the designer options to explore more alternatives and make decisions based on building performance would be of great benefit. If we look at the aerospace and automotive industries, they have developed multidisciplinary design optimization (MDO) methods, which are resulting in a significant reduction in the design cycle time and thus promoting more design iterations which then leads to improved product performance. MDO methods have been successfully applied in these industries, but their application to architecture practice has been comparatively modest. With the advent of BIM, however, it is now easier to facilitate the adoption of practices from other industries. This paper compares MDO processes in the Architecture, Aerospace and Automotive industries based upon data gathered on recent projects in each industry. It then reviews how iterative design and MDO process formalizes problem solving and coordination among groups working on the design of complex engineering systems. Finally, this paper investigates the feasibility of using BIM to facilitate an iterative design and MDO process which can result in the improvement in the number of design iterations of a building project.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • Azhar, S. Brown, J. & Farooqui, R., BIM-based Sustainability Analysis: An Evaluation of Building Performance Analysis Software, Proc. of the 45th Associated Schools of Construction International Conference, Gainesville, 2009.
    • Schlueter, A. & Thesseling, F., Building information model based energy/exergy performance assessment in early design stages. Automation in Construction, vol. 18, pp. 153-163, 2009.
    • Smeds, J & Wall, M., Enhanced energy conservation in houses through high performance design. Energy and Buildings, vol. 39, pp. 273-278, 2007.
    • Jansson, G. Schade, J. & Olofsson, T., Requirements management for the design of energy efficient building. Journal of Information Technology in Construction, vol. 18, pp. 321-337, 2013.
    • www.wbdg.org/resources/psheating.php Butler, J. Holden, K. & Lidwell, W. Universal Principles of Design, Revised and Updated, Beverly: Rockport Publishers, 2010.
    • Ballard, G., Positive vs negative iteration in design, Proc. of the 8th Conference of the International Group for Lean Construction, Brighton, 2000.
    • Pugh, S. Total Design Integrated Methods for Successful Product Engineering, Essex: Pearson Education Limited, 1991.
    • [9] Ulrich, K.T. & Eppinger, D. S., Product Design and Development, Fifth ed., New York: McGraw Hill, 2012.
    • [10] Cross, N. Engineering Design Methods Strategies for Product Design, Fourth ed., Sussex: John Willey & Sons, 2011.
    • [11] Stoll, H. W., Product Design Methods and Practices, New York: Marcel Dekker, 1999.
    • [12] RIBA, www.ribaplanofwork.com
    • [13] Pektasx, S. T. & Pultar, M., Modelling detailed information flows in building design with the parameter based design structure matrix, Design Studies, pp. 99-122, 2006.
    • [14] Hopfe, C. J., Struck, C., Hensen, J. & Böhms, M., Adapting advanced engineering design approaches to building design-potential benefits, Proc. of the 6th postgraduate research Conference in the built and human environment, Manchester, 2006.
    • [15] Mueller, V., Crawley, D. & Deb, P., Second iteration of cloud-based analysis and optimization framework, Proc. of the 13th Conference of International Building Performance Simulation Association, Chambéry, 2013.
    • [16] Flager, F. and Haymaker, J., A Comparison of Multidisciplinary Design, Analysis and Optimization Processes in the Building Construction and Aerospace, Standford University, 2009.
    • [17] Mujumdar, P. & Maheswari, J. U., A design iteration framework for construction project, Proc. of the RICS Cobra, New Delhi, 2013.
    • [18] 3ds, www.3ds.com
    • [19] Sheldon, A., Helwig, E. & Cho, Y.-B., Investigation and Application of Multi-Disciplinary Optimization for Automotive Body-in-White Development, Proc. of the 8th European LS-DYNA Users Conference, Strasbourg, 2011.
    • [20] Zanni, M., Soetanto, R. & Ruikar, K., Facilitating BIM-based sustainability analysis and communication in building design process, Proc. of the 6th Civil Engineering Conference in Asia Region, Jakarta, 2013.
    • [21] Welle, B., Haymaker, J. & Rogers, Z., ThermalOpt: A Methodology for Automated BIM-Based Multidisciplinary Thermal Simulation for Use in Optimization Environments, Stanford University, 2011.
    • [22] Rahmani Asl, M., Zarrinmehr, S. & Yan, W., Towards BIM-based Parametric Building Energy Performance Optimization, Proc. of the 33rd Annual Conference of the Association for Computer Aided Design in Architecture, Cambridge, 2013.
    • [23] Rahmani Asl, M., Bergin M., Menter, A. & W. Yan, BIM-based Parametric Building Energy Performance Multi-Objective Optimization, Proc. of the 32nd International Conference on Education and research in Computer Aided Architectural Design in Europe, Newcastle, 2014.
    • [24] Mueller, V., Second generation prototype of a design performance optimization framework, Proc. of the 7th International Conference of the Arab Society for Computer Aided Architectural Design, Jaddah, 2014.
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