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Structural and Multidisciplinary Optimization

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23.05.2020 | Research Paper

Continuous density-based topology optimization of cracked structures using peridynamics

verfasst von: A. Sohouli, A. Kefal, A. Abdelhamid, M. Yildiz, A. Suleman

Erschienen in: Structural and Multidisciplinary Optimization | Ausgabe 5/2020

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Abstract

Peridynamics (PD) is a meshless approach that addresses some of the difficulties and limitations associated with mesh-based topology optimization (TO) methods. This study investigates topology optimization of structures with and without embedded cracks using peridynamics (PD-TO). To this end, PD is coupled with two different continuous density-based topology optimization methods, namely the optimality criteria and the proportional optimization. The optimization results are compared for a continuous definition of the design variables, which are the relative densities defined for PD particles. The checkerboard issue has been removed using filtering schemes. The accuracy of the proposed PD-TO approach is validated by solving benchmark problems and comparing the optimal topologies with those obtained using a FEM-based topology optimization. Various problems are solved with and without defects (cracks) under different loading and constraint boundary conditions. Topology optimization for an unstructured discretization problem has also been investigated applied to a complex geometry. The optimal topology of a cracked structure may change for different optimization methods. The numerical results demonstrate the accuracy, high efficiency, and robustness of the PD-TO approach.

Vorheriger Artikel On the co-rotational method for geometrically nonlinear topology optimization

Nächster Artikel Stress-based shape and topology optimization with cellular level set in B-splines

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Titel: Continuous density-based topology optimization of cracked structures using peridynamics
verfasst von: A. Sohouli
A. Kefal
A. Abdelhamid
M. Yildiz
A. Suleman
Publikationsdatum: 23.05.2020
Verlag: Springer Berlin Heidelberg
Erschienen in: Structural and Multidisciplinary Optimization / Ausgabe 5/2020
Print ISSN: 1615-147X
Elektronische ISSN: 1615-1488
DOI: https://doi.org/10.1007/s00158-020-02608-1

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