He, L., Li, Q., Gilbert, M. orcid.org/0000-0003-4633-2839 et al. (4 more authors) (2022) Optimization-driven conceptual design of truss structures in a parametric modelling environment. Structures, 37. pp. 469-482.
Abstract
Structural optimization methods can be extremely powerful when used at the initial, conceptual, design stage of a building or bridge structure, potentially identifying materially efficient forms that are beyond the imagination of a human designer. This is particularly important at present, given the pressing need to reduce the carbon footprint associated with the built environment in the face of the current climate emergency. In this contribution, a computationally efficient global–local optimization framework is proposed, in which a linear programming-based truss layout optimization step is employed to generate initial (near-)optimal designs, with a non-linear optimization step then used to generate designs that take account of real-world complexity. To facilitate rapid exploration of design concepts, the proposed global–local optimization framework has been made available in the Peregrine plug-in for the popular Rhino-Grasshopper parametric modelling environment. The efficacy of the approach is demonstrated through its application to a range of case study problems.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 Institution of Structural Engineers. This is an author produced version of a paper subsequently published in Structures. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Structural optimization; Layout optimization; Topology optimization; Structural design; Parametric design |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Civil and Structural Engineering (Sheffield) |
Funding Information: | Funder Grant number Engineering and Physical Sciences Research Council EP/N023471/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 27 Jan 2022 08:02 |
Last Modified: | 18 Jan 2023 01:13 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.istruc.2021.12.048 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:182969 |