MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

HiTop 2.0: combining topology optimisation with multiple feature size controls and human preferences

Author(s)
Schiffer, Gillian; Ha, Dat Quoc; Carstensen, Josephine V
Thumbnail
DownloadPublished version (5.050Mb)
Publisher with Creative Commons License

Publisher with Creative Commons License

Creative Commons Attribution

Terms of use
Creative Commons Attribution https://creativecommons.org/licenses/by/4.0/
Metadata
Show full item record
Abstract
Topology optimisation is a computational design approach that generates high-performing, efficient structures uniquely suited to a design engineer’s goal. However, there exist two major obstacles to the accessibility, or ease of use, of topology optimisation: expensive computational costs and users’ binary decision between personal intuition and the algorithm’s result. Human-informed topology optimisation, or HiTop, presents an alternative approach to topology optimisation when a user lacks access to a high-performance computer or knowledge of code parameters. HiTop 2.0 prompts users to interactively identify a region of interest in the preliminary design and modify the size of the solid and/or void features. The novel contribution of this paper implements multi-phase minimum and maximum solid feature size controls in HiTop 2.0, and demonstrates 2D and 3D benchmark examples, including test cases that show how the user can interactively enhance issues related to eigenvalues, stress, and energy absorption, while solving the minimum compliance problem.
Date issued
2023-12-31
URI
https://hdl.handle.net/1721.1/164294
Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Journal
Virtual and Physical Prototyping
Publisher
Taylor & Francis
Citation
Schiffer, G., Ha, D. Q., & Carstensen, J. V. (2023). HiTop 2.0: combining topology optimisation with multiple feature size controls and human preferences. Virtual and Physical Prototyping, 18(1).
Version: Final published version

Collections
  • MIT Open Access Articles

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.