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Level set topology optimization with nodally integrated reproducing kernel particle method

Neofytou, Andreas, Huang, Tsung-Hui, Kambampati, Sandilya, Picelli, Renato, Chen, Jiun-Shyan and Kim, H. Alicia 2021. Level set topology optimization with nodally integrated reproducing kernel particle method. Computer Methods in Applied Mechanics and Engineering 385 , 114016. 10.1016/j.cma.2021.114016

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Abstract

A level set topology optimization (LSTO) using the stabilized nodally integrated reproducing kernel particle method (RKPM) to solve the governing equations is introduced in this paper. This methodology allows for an exact geometry description of a structure at each iteration without remeshing and without any interpolation scheme. Moreover, useful characteristics of the RKPM such as the easily controlled order of continuity and the ability to freely place particles in a design domain wherever needed are illustrated through stress based and design-dependent surface loading examples. The numerical results illustrate the effectiveness and robustness of the methodology with good optimization convergence behavior and ability to handle large topological changes. Furthermore, it is shown that different particle distributions can be used to increase efficiency without additional complexity.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: Elsevier
ISSN: 0045-7825
Funders: EPSRC
Date of First Compliant Deposit: 24 August 2021
Date of Acceptance: 22 June 2021
Last Modified: 10 Sep 2021 09:23
URI: https://orca.cardiff.ac.uk/id/eprint/143489

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