CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
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id ijac201917106
authors Brown, Nathan C. and Caitlin T. Mueller
year 2019
title Design variable analysis and generation for performance-based parametric modeling in architecture
source International Journal of Architectural Computing vol. 17 - no. 1, 36-52
summary Many architectural designers recognize the potential of parametric models as a worthwhile approach to performance- driven design. A variety of performance simulations are now possible within computational design environments, and the framework of design space exploration allows users to generate and navigate various possibilities while considering both qualitative and quantitative feedback. At the same time, it can be difficult to formulate a parametric design space in a way that leads to compelling solutions and does not limit flexibility. This article proposes and tests the extension of machine learning and data analysis techniques to early problem setup in order to interrogate, modify, relate, transform, and automatically generate design variables for architectural investigations. Through analysis of two case studies involving structure and daylight, this article demonstrates initial workflows for determining variable importance, finding overall control sliders that relate directly to performance and automatically generating meaningful variables for specific typologies.
keywords Parametric design, design space formulation, data analysis, design variables, dimensionality reduction
series journal
email ncbrown@mit.edu
full text file.pdf ( bytes)
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100%; open Anderl R. and Mendgen R. (1995) Find in CUMINCAD Parametric design and its impact on solid modeling applications , Proceedings of the third ACM symposium on solid modeling and applications, Salt Lake City, UT, 17–19 May 1995, pp. 1–12. New York: ACM

100%; open Box G.E.P., Hunter J.S. and Hunter W.G. (2005) Find in CUMINCAD Statistics for experimenters: design, innovation, and discovery. 2nd ed. , Hoboken, NJ: John Wiley & Sons

100%; open Bradner E., Iorio F. and Davis M. (2014) Find in CUMINCAD Parameters tell the design story: ideation and abstraction in design optimization , Simul Ser; 46: 172–197

100%; open Brown N.C. and Mueller C.T. (2017) Find in CUMINCAD Designing with data: moving beyond the design space catalog , Proceedings of ACADIA 2017: disciplines and disruption, Cambridge, MA, 2–4 November 2017

100%; open Brown N.C. and Mueller C.T. (2017) Find in CUMINCAD Automated performance-based design space simplification for parametric structural design , Proceedings of the IASS annual symposium 2017, Hamburg, 25–28 September 2017

100%; open Chaszar A. and Joyce S.C. (2016) Find in CUMINCAD Generating freedom: questions of flexibility in digital design and architectural computa- tion , Int J Archit Comput; 14: 167–181

100%; open Chen K.W., Janssen P. and Schlueter A. (2015) Find in CUMINCAD Analysing populations of design variants using clustering and archetypal analysis , Proceedings of the 33rd eCAADe conference, Vienna, 16–18 September 2015, vol. 1, pp. 251–260

100%; open Conti Z.X. and Kaijima S. (2017) Find in CUMINCAD Enabling inference in performance-driven design exploration , De Rycke K, Gengnagel C, Baverel O, et al. (eds) Humanizing digital reality: design modelling symposium Paris 2017 . Singapore: Springer Nature, pp. 177–188

100%; open Cross N., Dorst K., Roozenburg N. et al. (1992) Find in CUMINCAD Research in design thinking , Delft: Delft University Press

100%; open Cross N., Naughton J. and Walker D. (1981) Find in CUMINCAD Design method and scientific method , Des Stud; 2: 195–201

100%; open Derix C. and Jagannath P. (2014) Find in CUMINCAD Near futures: associative archetypes , Archit Des; 84: 130–135

100%; open Dorst K. (2011) Find in CUMINCAD The core of “design thinking” and its application , Des Stud; 32: 521–532

100%; open Harding J. (2016) Find in CUMINCAD Dimensionality reduction for parametric design exploration , Adriaenssens S, Gramazio F, Kohler M, et al. (eds) Advances in architectural geometry 2016 . Zurich: vdf Hochschulverlag, pp. 204–221

100%; open Harding J. and Shepherd P. (2017) Find in CUMINCAD Meta-parametric design , Des Stud; 52: 73–95

100%; open Hardoon D.R., Szedmak S. and Shawe-Taylor J. (2004) Find in CUMINCAD Canonical correlation analysis: an overview with application to learning methods , Neural Comput; 16: 2639–2664

100%; open Haymaker J. (2012) Find in CUMINCAD Expanding Design Spaces , Frontiers of Engineering: Reports on Leading-Edge Engineering from the 2011 Symposium . Washington, DC: The National Academies Press, pp. 89–96

100%; open Holzer D., Hough R. and Burry M. (2008) Find in CUMINCAD Parametric design and structural optimisation for early design exploration , Int J Archit Comput; 5: 625–644

100%; open Kackar R.N. (1985) Find in CUMINCAD Off-line quality control, parameter design, and the Taguchi method , J Qual Technol; 17: 176– 188

100%; open Karhunen J. and Joutsensalo J. (1995) Find in CUMINCAD Generalizations of principal component analysis, optimization problems, and neural networks , Neural Networks; 8: 549–562

100%; open Khaled N. and Smaili A. (2005) Find in CUMINCAD Curve representation using principal component analysis for shape optimization of path generating mechanisms , Proceedings of IDETC/CIE 2005 ASME 2005 international design engineering techni- cal conferences & computers, Long Beach, CA, 24–28 September 2005, pp. 1–8. New York: ASME

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