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An AI-Assisted Design Method for Topology Optimization without Pre-Optimized Training Data

Published online by Cambridge University Press:  26 May 2022

A. Halle ,
L. F. Campanile  and
A. Hasse
A. Halle*
Affiliation:
Chemnitz University of Technology, Germany
L. F. Campanile
Affiliation:
Chemnitz University of Technology, Germany
A. Hasse
Affiliation:
Chemnitz University of Technology, Germany
*
alex.halle@mb.tu-chemnitz.de

Abstract

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Engineers widely use topology optimization during the initial process of product development to obtain a first possible geometry design. The state-of-the-art method is iterative calculation, which requires both time and computational power. This paper proposes an AI-assisted design method for topology optimization, which does not require any optimized data. The presented AI-assisted design procedure generates geometries that are similar to those of conventional topology optimizers, but require only a fraction of the computational effort.

Keywords

topology optimisationAI-assisted designcomputational design methodsdesign evaluationdesign to x (DtX)

Information

Type
Article
Information
Proceedings of the Design Society , Volume 2: DESIGN2022 , May 2022 , pp. 1589 - 1598
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2022.

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