Human-Informed Topology Optimization: interactive application of feature size controls
Abstract This paper presents a new topology optimization framework in which the design decisions are made by humans and machines in collaboration. The new Human-Informed Topology Optimization approach eases the accessibility of topology optimization tools and enables improved design i...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer Berlin Heidelberg
2023
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| Online Access: | https://hdl.handle.net/1721.1/148295 |
| _version_ | 1811086004086374400 |
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| author | Ha, Dat Q. Carstensen, Josephine V. |
| author2 | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Ha, Dat Q. Carstensen, Josephine V. |
| author_sort | Ha, Dat Q. |
| collection | MIT |
| description | Abstract
This paper presents a new topology optimization framework in which the design decisions are made by humans and machines in collaboration. The new Human-Informed Topology Optimization approach eases the accessibility of topology optimization tools and enables improved design identification for the so-called ‘everyday’ and ‘in-the-field’ design situations. The new framework is based on standard density-based compliance minimization. However, the design engineer is enabled to actively use their experience and expertise to locally alter the minimum feature size requirements. This is done by conducting a short initial solution and prompting the design engineer to evaluate the quality. The user can identify potential areas of concern based on the initial material distribution. In these areas, the minimum feature size requirement can be altered as deemed necessary by the user. The algorithm rigorously resolves the compliance problem using the updated filtering map, resulting in solutions that eliminate, merge, or thicken topological members of concern. The new framework is demonstrated on 2D benchmark examples and the extension to 3D is shown. Its ability to achieve performance improvement with few computational resources are demonstrated on buckling and stress concentration examples. |
| first_indexed | 2024-09-23T13:19:22Z |
| format | Article |
| id | mit-1721.1/148295 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T13:19:22Z |
| publishDate | 2023 |
| publisher | Springer Berlin Heidelberg |
| record_format | dspace |
| spelling | mit-1721.1/1482952024-01-08T20:25:51Z Human-Informed Topology Optimization: interactive application of feature size controls Ha, Dat Q. Carstensen, Josephine V. Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Abstract This paper presents a new topology optimization framework in which the design decisions are made by humans and machines in collaboration. The new Human-Informed Topology Optimization approach eases the accessibility of topology optimization tools and enables improved design identification for the so-called ‘everyday’ and ‘in-the-field’ design situations. The new framework is based on standard density-based compliance minimization. However, the design engineer is enabled to actively use their experience and expertise to locally alter the minimum feature size requirements. This is done by conducting a short initial solution and prompting the design engineer to evaluate the quality. The user can identify potential areas of concern based on the initial material distribution. In these areas, the minimum feature size requirement can be altered as deemed necessary by the user. The algorithm rigorously resolves the compliance problem using the updated filtering map, resulting in solutions that eliminate, merge, or thicken topological members of concern. The new framework is demonstrated on 2D benchmark examples and the extension to 3D is shown. Its ability to achieve performance improvement with few computational resources are demonstrated on buckling and stress concentration examples. 2023-03-06T13:08:56Z 2023-03-06T13:08:56Z 2023-02-28 2023-03-05T04:08:11Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/148295 Structural and Multidisciplinary Optimization. 2023 Feb 28;66(3):59 PUBLISHER_CC en https://doi.org/10.1007/s00158-023-03512-0 Creative Commons Attribution https://creativecommons.org/licenses/by/4.0/ The Author(s) application/pdf Springer Berlin Heidelberg Springer Berlin Heidelberg |
| spellingShingle | Ha, Dat Q. Carstensen, Josephine V. Human-Informed Topology Optimization: interactive application of feature size controls |
| title | Human-Informed Topology Optimization: interactive application of feature size controls |
| title_full | Human-Informed Topology Optimization: interactive application of feature size controls |
| title_fullStr | Human-Informed Topology Optimization: interactive application of feature size controls |
| title_full_unstemmed | Human-Informed Topology Optimization: interactive application of feature size controls |
| title_short | Human-Informed Topology Optimization: interactive application of feature size controls |
| title_sort | human informed topology optimization interactive application of feature size controls |
| url | https://hdl.handle.net/1721.1/148295 |
| work_keys_str_mv | AT hadatq humaninformedtopologyoptimizationinteractiveapplicationoffeaturesizecontrols AT carstensenjosephinev humaninformedtopologyoptimizationinteractiveapplicationoffeaturesizecontrols |