Geometric complexity and energy simulation

Open Systems - Proceedings of the 18th International Conference on Computer-Aided Architectural Design Research in Asia, CAADRIA 2013

Volumn , Issue , 2013, Pages 87-96

  Gerber, David J ^a   Lin, Shih Hsin ^a  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

Design decision support; Generative; Optimisation; Parametric

Indexed keywords

EID: 84894156801     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (27)

1. Augenbroe, G.: 2002, Trends in building simulation, Building and Environment, 37(8-9), 891-902.
2. Coello Coello, C. A., Lamont, G. B. and Van Veldhuisen, D. A.: 2007, Evolutionary algorithms for solving multi-objective problems, Genetic and evolutionary computation series, 2nd ed., Springer, New York.
3. Crawley, D. B., Hand, J. W., Kummert, M. and Griffith, B. T.: 2008, Contrasting the capabilities of building energy performance simulation programs, Building and Environment, 43(4), 661-673.
4. Eastman, C. M.: 1970, On the analysis of intuitive design processes, in G. T. Moore (ed.), Emerging Methods in Environmental Design and Planning, MIT Press, Cambridge, MA.
5. Frazer, J.: 1995, An evolutionary architecture, Architectural Association, London.
6. Gerber, D. J. and Lin, S.-H. E.: 2012, Designing-in performance through parameterization, automation, and evolutionary algorithms: 'H.D.S. BEAGLE 1.0?, in T. Fischer, K. De Biswas, J. J. Ham, R. Naka and W. X. Huang (eds.), CAADRIA 2012: Beyond Codes and Pixels, Chennai, India, 141-150.
7. Gero, J. S.: 1990, Design prototypes: A knowledge representation schema for design, AI Magazine, 11(4), 26-36.
8. Gero, J. S., D'Cruz, N. and Radford, A. D.: 1983, Energy in context: Amulticriteria model for building design, Building and Environment, 18(3), 99-107.
9. Geyer, P.: 2009, Component-oriented decomposition for multidisciplinary design optimization in building design, Advanced Engineering Informatics, 23(1), 12-31.
10. Glymph, J., Shelden, D., Ceccato, C., Mussel, J. and Schober, H.: 2004, A parametric strategy for free-form glass structures using quadrilateral planar facets, Automation in Construction, 13(2), 187-202.
11. Goldberg, D. E.: 1989, Genetic algorithms in search, optimization, and machine learning, Addison-Wesley, Reading, MA.
12. Holland, J. H.: 1992, Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence, A Bradford Book, Ann Arbor.
13. Huang, H., Kato, S. and Hu, R.: 2012, Optimum design for indoor humidity by coupling Genetic Algorithm with transient simulation based on contribution ratio of indoor humidity and climate analysis, Energy and Buildings, 47, 208-216.
14. Keough, I. and Benjamin, D.: 2010, Multi-objective optimization in architectural design, in A. Khan (ed.), SimAUD 2010, Orlando, FL, 5-12.
15. Krish, S.: 2011, A practical generative design method, Computer-Aided Design, 43(1), 88-100.
16. Magnier, L. and Haghighat, F.: 2010, Multiobjective optimization of building design using TRNSYS simulations, genetic algorithm, and artificial neural network, Building and Environment, 45(3), 739-746.
17. Malkawi, A.: 2005, Performance simulation: research and tools, in B. Kolarevic and A. Malkawi (eds.), Performative architecture: beyond instrumentality, Spon Press, New York, 85-96.
18. Menges, A.: 2011, Integrative design computation: Integrating material behaviour and robotic manufacturing processes in computational design for performative wood constructions, ACADIA 2011 - Integration through Computation, Banff, Alberta, 72-81.
19. Poloni, C. and Pediroda, V.: 1997, GA coupled with computationally expensive simulations: tools to improve efficiency, in D. Quagliarella, J. Périaux, C. Poloni and G. Winter (eds.), Genetic algorithms and evolution strategy in engineering and computer science: recent advances and industrial applications, John Wiley & Sons, West Sussex, England, 225-243.
20. Ren, Z., Yang, F., Bouchlaghem, N. M. and Anumba, C. J.: 2011, Multi-disciplinary collaborative building design - A comparative study between multi-agent systems and multi-disciplinary optimisation approaches, Automation in Construction, 20(5), 537-549.
21. Sanguinetti, P., Bernal, M., El-Khaldi, M. and Erwin, M.: 2010, Real-time design feedback: Coupling performance-knowledge with design, in A. Khan (ed.), SimAUD 2010, Orlando, FL, 23-30.
22. Schlueter, A. and Thesseling, F.: 2009, Building information model based energy/exergy performance assessment in early design stages, Automation in Construction, 18(2), 153-163.
23. Shea, K., Aish, R. and Gourtovaia, M.: 2005, Towards integrated performance-driven generative design tools, Automation in Construction, 14(2), 253-264.
24. Toth, B., Salim, F. D., Drogemuller, R., Frazer, J. H. and Burry, J.: 2011, Closing the loop of design and analysis: Parametric modelling tools for early decision support, CAADRIA 2011: Circuit Bending, Breaking and Mending, Newcastle, Australia, 525-534.
25. Turrin, M., von Buelow, P. and Stouffs, R.: 2011, Design explorations of performance driven geometry in architectural design using parametric modeling and genetic algorithms, Advanced Engineering Informatics, 25(4), 656-675.
26. USGBC: 2003, Building momentum: National trends and prospects for high-performance green buildings, U.S. Green Building Council (USGBC), Washington, DC.
27. Yi, Y. K. and Malkawi, A. M.: 2009, Optimizing building form for energy performance based on hierarchical geometry relation, Automation in Construction, 18(6), 825-833.