A parallel parameterized level set method for large-scale structural topology optimization under design-dependent load

This paper proposes a topology optimization framework for three-dimensional continuum structures subjected to design-dependent loads, including gravity, centrifugal, and hydrostatic pressure loads. First, this study utilizes the parameterized level set method (PLSM) with unstructured meshes to effec...

Full description

Saved in:
Bibliographic Details
Published in:Computer methods in applied mechanics and engineering Vol. 443; p. 118032
Main Authors: Wei, Peng, Cheng, Ben, Lin, Haoju, Liu, Hui
Format: Journal Article
Language:English
Published: Elsevier B.V 01.08.2025
Subjects:
ISSN:0045-7825
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper proposes a topology optimization framework for three-dimensional continuum structures subjected to design-dependent loads, including gravity, centrifugal, and hydrostatic pressure loads. First, this study utilizes the parameterized level set method (PLSM) with unstructured meshes to effectively handle complex structural shapes and boundary conditions. Second, this work employs parallel computing techniques and uses the shape function as the basis function in PLSM to significantly enhance computational efficiency. Additionally, this study comprehensively analyzes design-dependent loads and addresses topology optimization of large-scale structures under complex load conditions. This study overcomes the lack of research on complicated 3D design-dependent load problems. It aims to broaden the application of topology optimization techniques, making them more applicable to engineering practices, such as large-scale underwater structures. Finally, several 3D examples demonstrate the proposed framework’s efficiency, stability, and ability to generate innovative structural designs. •A parameterized level set method based on shape functions and unstructured meshes.•Distributed-memory parallel computing is used on large-scale topology optimization.•Study analyzes design-dependent loads: gravity, centrifugal, and hydrostatic loads.•The algorithm has good stability, efficiency, and scalability.
ISSN:0045-7825
DOI:10.1016/j.cma.2025.118032