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Implementing data-driven parametric building design with a flexible toolbox
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DOI：10.1016/j.autcon.2020.103252.png)
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摘要
En 中文
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.
Keyword:
Multi-objective optimization
Design space exploration
Interactive optimization
Structural design
Sustainable design
Conceptual design
Surrogate modeling
Energy simulation
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期刊
IF:
11.5
论文数:
6.3K
被引数:
4.2W
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引用论文
Toolbox for super-structured and super-structure free multi-disciplinary building spatial design optimisation超结构和超结构自由多学科建筑空间设计优化工具箱OAAI
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Design for structural and energy performance of long span buildings using geometric multi-objective optimization基于几何多目标优化的大跨度建筑结构与节能性能设计.png)
ENERGY AND BUILDINGSOAAI
ENERGY AND BUILDINGSIF7.1
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