Design concept generation with variational deep embedding over comprehensive optimization

Kikuo Fujita*, Kazuki Minowa, Yutaka Nomaguchi, Shintaro Yamasaki, Kentaro Yaji

*この研究の対応する著者

研究成果: Conference contribution

抄録

This paper proposes a framework for generating design concepts through the loop of comprehensive exploitation and consequent exploration. The former is by any sophisticated optimization such as topology optimization with diversely different. The latter realization is due to the variational deep embedding (VaDE), a deep learning technique with classification capability. In the process of design concept generation first, exploitation through computational optimization generates various possibilities of design entities. Second, VaDE learns them. This learning encodes the clusters of similar entities over the latent space with smaller dimensions. The clustering result reveals some design concepts and identifies voids where as-yet-unrecognized design concepts are prospective. Third, the decoder of the learned VaDE generates some possibilities for new design entities. Forth such new entities are examined, and relevant new conditions will trigger further exploitation by the optimization. In this paper, this framework is implemented for and applied to the conceptual design problem of bridge structures. This application demonstrates that the framework can identify voids over the latent space and explore the possibility of new concepts. This paper brings up some discussion on the promises and possibilities of the proposed framework.

本文言語English
ホスト出版物のタイトル47th Design Automation Conference (DAC)
出版社American Society of Mechanical Engineers (ASME)
ISBN(電子版)9780791885390
DOI
出版ステータスPublished - 2021
外部発表はい
イベント47th Design Automation Conference, DAC 2021, Held as Part of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2021 - Virtual, Online
継続期間: 2021 8月 172021 8月 19

出版物シリーズ

名前Proceedings of the ASME Design Engineering Technical Conference
3B-2021

Conference

Conference47th Design Automation Conference, DAC 2021, Held as Part of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2021
CityVirtual, Online
Period21/8/1721/8/19

ASJC Scopus subject areas

  • 機械工学
  • コンピュータ グラフィックスおよびコンピュータ支援設計
  • コンピュータ サイエンスの応用
  • モデリングとシミュレーション

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