Topology optimization of structures subject to self-weight loading under stress constraints
ISSN: 0264-4401
Article publication date: 25 October 2021
Issue publication date: 1 February 2022
Abstract
Purpose
The purpose of this paper is to present an approach for structural weight minimization under von Mises stress constraints and self-weight loading based on the topological derivative method. Although self-weight loading topology has been the subject of intense research, mainly compliance minimization has been addressed.
Design/methodology/approach
The resulting minimization problem is solved with the help of the topological derivative method, which allows the development of efficient and robust topology optimization algorithms. Then, the derived result is used together with a level-set domain representation method to devise a topology design algorithm.
Findings
Numerical examples are presented, showing the effectiveness of the proposed approach in solving a structural topology optimization problem under self-weight loading and stress constraint. When the self-weight loading is dominant, the presence of the regularizing term in the formulation is crucial for the design process.
Originality/value
The novelty of this research work lies in the use of a regularized formulation to deal with the presence of the self-weight loading combined with a penalization function to treat the von Mises stress constraint.
Keywords
Acknowledgements
This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.
Replication of results: The authors are agreeable to share the codes and details of results with those who contact them.
Conflict of interest: The authors declare that they have no conflict of interest.
Citation
Batista dos Santos, R. and Gomes Lopes, C. (2022), "Topology optimization of structures subject to self-weight loading under stress constraints", Engineering Computations, Vol. 39 No. 1, pp. 380-394. https://doi.org/10.1108/EC-06-2021-0368
Publisher
:Emerald Publishing Limited
Copyright © 2021, Emerald Publishing Limited