On development of an accessible and non-intrusive level-set topology optimization framework via the discrete adjoint method

Hyun, Jaeyub, Jauregui, Carolina, Kim, H. Alicia and Neofytou, Andreas 2022. On development of an accessible and non-intrusive level-set topology optimization framework via the discrete adjoint method. Presented at: AIAA SCITECH 2022 Forum, Virtual, 03-07 January 2022. AIAA SCITECH 2022 Forum. Aerospace Reseach Central, 10.2514/6.2022-2548

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Abstract

This study is aimed at developing an accessible and non-intrusive level-set topology optimization framework based on the discrete adjoint method and modularized architecture. The physics solver and level-set interface are completely separated and functions independently, and thus its interoperability and reusability can be maximized. The developed modularized framework employs discrete adjoint sensitivity via the local perturbation scheme. This scheme combines element sensitivities typically used in density-based topology optimization with the local perturbations of boundary movements, thereby computing the consistent shape sensitivities in a straightforward manner. This is demonstrated by numerical examples, 2D structural stress minimization, 2D thermal eigenvalue maximization, and 3D MBB beam compliance minimization problems. Our developed modularized level-set topology optimization framework will make it possible to maximize its applicability to a wide range of complex multiphysics problems.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Engineering
Publisher:	Aerospace Reseach Central
ISBN:	9781624106316
Last Modified:	10 Jun 2023 01:59
URI:	https://orca.cardiff.ac.uk/id/eprint/147436

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