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Python scripts for vault layout optimization

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Bibliographic Details
Title: Python scripts for vault layout optimization
Authors: Linwei He, Helen Fairclough, Matthew Gilbert, Andrew Liew, Karol Bołbotowski
Publication Year: 2024
Collection: The University of Sheffield: Figshare
Subject Terms: Architectural computing and visualisation methods, Data visualisation and computational (incl. parametric and generative) design, Structural engineering, Optimisation, form-finding, layout optimization, vaults, truss topology optimization, ground structure method
Description: Simple Python script, as described in the paper 'Minimum material vault designs generated via adaptive layout optimization', Engineering Structures, by Linwei He, Helen Fairclough, Matthew Gilbert, Andrew Liew & Karol Bołbotowski. Vaults are commonly used to form lightweight long-span roof structures, allowing flexible internal spaces with minimal associated embodied carbon. The precise shape of the vault should be chosen to reduce or eliminate bending effects, so as to promote more-efficient structures that work in pure compression. Many existing form-finding methods can identify bending-free designs; however, these are restricted to operate on predefined layouts and therefore cannot generally achieve optimal material-efficiency. This paper presents a numerical layout optimization method that uses the 'ground structure' approach to simultaneously optimize a vault's form and force flow topology. By formulating the problem as a conic programming problem, minimum volume designs that are globally optimal for any given numerical discretization can be obtained. To enhance computational efficiency, an adaptive 'member adding' technique is employed, enabling the solution of large-scale problems while also allowing rapid exploration of smaller-scale scenarios. The proposed method is applied to a range of examples, demonstrating the ability of the proposed procedure to generate more materially efficient vault designs, compared to traditional Force Density Method (FDM) designs.
Document Type: software
Language: unknown
Relation: https://figshare.com/articles/software/Python_scripts_for_vault_layout_optimization/27187602
DOI: 10.15131/shef.data.27187602.v2
Availability: https://doi.org/10.15131/shef.data.27187602.v2
https://figshare.com/articles/software/Python_scripts_for_vault_layout_optimization/27187602
Rights: MIT
Accession Number: edsbas.2CD4E28D
Database: BASE
Description
Abstract:Simple Python script, as described in the paper 'Minimum material vault designs generated via adaptive layout optimization', Engineering Structures, by Linwei He, Helen Fairclough, Matthew Gilbert, Andrew Liew & Karol Bołbotowski. Vaults are commonly used to form lightweight long-span roof structures, allowing flexible internal spaces with minimal associated embodied carbon. The precise shape of the vault should be chosen to reduce or eliminate bending effects, so as to promote more-efficient structures that work in pure compression. Many existing form-finding methods can identify bending-free designs; however, these are restricted to operate on predefined layouts and therefore cannot generally achieve optimal material-efficiency. This paper presents a numerical layout optimization method that uses the 'ground structure' approach to simultaneously optimize a vault's form and force flow topology. By formulating the problem as a conic programming problem, minimum volume designs that are globally optimal for any given numerical discretization can be obtained. To enhance computational efficiency, an adaptive 'member adding' technique is employed, enabling the solution of large-scale problems while also allowing rapid exploration of smaller-scale scenarios. The proposed method is applied to a range of examples, demonstrating the ability of the proposed procedure to generate more materially efficient vault designs, compared to traditional Force Density Method (FDM) designs.
DOI:10.15131/shef.data.27187602.v2