Implementing data-driven parametric building design with a flexible toolbox

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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Work Title Implementing data-driven parametric building design with a flexible toolbox
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Open Access
Creators Nathan Brown; Violetta Jusiega; Caitlin Mueller
Version number 1
License Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Work Type Article
Publication Date 2020
Deposited February 23, 2021 16:45

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Version 1
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  • Created
  • Added Creator Nathan Brown
  • Added Creator Violetta Jusiega
  • Added Creator Caitlin Mueller
  • Added AiC_Accepted_Manuscript_NCB_2020.pdf
  • Updated Work Title, License Show Changes
    Work Title
    • Implementing data-driven parametric building design with a flexible toolbox
    • Implementing data-driven parametric building design with a flexible toolbox
    License
    • https://creativecommons.org/licenses/by-nc-nd/4.0/
  • Published