Paola Sanguinetti
ABSTRACT
Many commercial environmental analysis tools support the evaluation of a building model based on parameters assigned in the design process. However interoperability issues between different data exchange formats hinder the iteration between design and analysis. Because the engineering calculations involved in analysis and evaluation are not integrated with architectural design parameters, evaluation takes place after the design is already defined, and analysis in real-time is not possible. In this project we integrate architectural design and engineering constraints to support design evolution and decision making by using a set of performance objectives. We propose a framework for coupling performance knowledge with generative synthesis to address multidisciplinary design challenges in the Architecture, Engineering, and Construction (AEC) industry. We develop a tool to support design evaluation based on performance criteria: energy consumption, comfort, and cost. Results show real-time information exchange as links between architectural geometry and engineering parameters. The outcomes of this research describe workflows and methods to evaluate alternative design proposals at early stages in real time.
- Alfaris, A. and R. Merello (2008). The Generative Multi-Performance Design System. Silicon + Skin: Biological Processes and Computation. Proceedings of the 28th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) Minneapolis.Google Scholar
- Augenbroe, A., (2004) Developments in interoperability, in Ali Malawi and God fried Augenbroe (Eds.). Advanced Building Simulation, Spon Press, 2004 pp. 189--216Google Scholar
- Augenbroe, G., A, Malkawi, P. de Wilde, (2004). A Workbench for Structured Design Analysis Dialogues. Journal of Architectural and Planning Research, 21 (4), 321--330Google Scholar
- Eastman. C. and Kutay, A, (1991) "Transaction Management in Design Databases" in Sriram, D., R. Logcher and S. Fukada (eds.) Computer-Aided Cooperative Product Development, Springer-Verlag, N.Y, 1991 Google ScholarDigital Library
- Eastman. C, (1999) Building Product Models: Chapter 10: Information Exchange Architectures, pp. 321--349Google Scholar
- Eastman, C. M., Tiecholz, P., Sacks, R., Liston, K., (2008) BIM Handbook, John Wiley & Sons Inc.Google Scholar
- Foliente, G. C., (2000). Developments in performance-based building codes and standards, Forest Products Journal, 50(7/8), 12--21Google Scholar
- Hagentoft, C. E.(2003) Introduction to Building Physics, Studentlitteratur, LundGoogle Scholar
- IESNA (2000) Illuminating Engineering Society of North America, Mark Stanley Rea, ed. 9 edition (July 2000)Google Scholar
- Simon, H. (1996). The Sciences of the Artificial. The MIT Press. Google ScholarDigital Library
- Szokolay, S. V, (2008) "Introduction to Architectural Science", Architectural Press, Oxfor, UK.Google Scholar
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