TY - JOUR
T1 - Implementing data-driven parametric building design with a flexible toolbox
AU - Brown, Nathan C.
AU - Jusiega, Violetta
AU - Mueller, Caitlin T.
N1 - Publisher Copyright:
© 2020 Elsevier B.V.
PY - 2020/10
Y1 - 2020/10
N2 - Designers in architecture and engineering are increasingly employing parametric models linked to performance simulations to assist in early building design decisions. This context presents a clear opportunity to integrate advanced functionality for engaging with quantitative design objectives directly into computational design environments. This paper presents a toolbox for data-driven design, which draws from data science and optimization methods to enable customized workflows for early design space exploration. It then applies these approaches to a multi-objective conceptual design problem involving structural and energy performance for a long span roof with complex geometry and considerable design freedom. The case study moves from initial brainstorming through design refinement while demonstrating the advantages of flexible workflows for managing design data. Through investigation of a realistic early design prompt, this paper reveals strengths, limitations, potential pitfalls, and future opportunities for data-driven parametric design.
AB - Designers in architecture and engineering are increasingly employing parametric models linked to performance simulations to assist in early building design decisions. This context presents a clear opportunity to integrate advanced functionality for engaging with quantitative design objectives directly into computational design environments. This paper presents a toolbox for data-driven design, which draws from data science and optimization methods to enable customized workflows for early design space exploration. It then applies these approaches to a multi-objective conceptual design problem involving structural and energy performance for a long span roof with complex geometry and considerable design freedom. The case study moves from initial brainstorming through design refinement while demonstrating the advantages of flexible workflows for managing design data. Through investigation of a realistic early design prompt, this paper reveals strengths, limitations, potential pitfalls, and future opportunities for data-driven parametric design.
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U2 - 10.1016/j.autcon.2020.103252
DO - 10.1016/j.autcon.2020.103252
M3 - Article
AN - SCOPUS:85086365450
VL - 118
JO - Automation in Construction
JF - Automation in Construction
SN - 0926-5805
M1 - 103252
ER -