A parallel parameterized level set topology optimization framework for large-scale structures with unstructured meshes
In addition to the requirements of full-scale optimization, the adaptability to structures with arbitrary geometries and complex boundary conditions is also important to topology optimization in practical engineering applications. A parallel parameterized level set topology optimization framework fo...
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| Published in: | Computer methods in applied mechanics and engineering Vol. 397; p. 115112 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
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Amsterdam
Elsevier B.V
01.07.2022
Elsevier BV |
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| ISSN: | 0045-7825, 1879-2138 |
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| Abstract | In addition to the requirements of full-scale optimization, the adaptability to structures with arbitrary geometries and complex boundary conditions is also important to topology optimization in practical engineering applications. A parallel parameterized level set topology optimization framework for large-scale structures with unstructured meshes is proposed in this work, in which the full-scale optimization is realized with distributed memory parallel computing technology while the arbitrary geometries and complex boundary conditions are conveniently handled with the usage of unstructured meshes. To realize the combination of distributed memory parallel computing technology and parameterized level set topology optimization using unstructured meshes, several means are taken: (1) the shape functions in finite element analysis are employed to parameterize the level set function; (2) the data structure called directed acyclic graph is adopted to represent the unstructured mesh; (3) the passive domain and boundary conditions are imposed directly on the geometry entities of the structures; (4) a multiple averaging filter is introduced to reduce the tiny structural members in the optimized results for the requirement of manufacturability. Several computing tests are presented in this paper, which verify the stability, efficiency, scalability, and the potential to discover new structure styles of the framework.
•A PLSM framework is proposed for large-scale practical engineering problems.•The shape function based PLSM handles irregular unstructured meshes well.•The multiple averaging filter proposed suits the domain decomposition strategy well.•The algorithm has good stability, efficiency, and scalability. |
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| AbstractList | In addition to the requirements of full-scale optimization, the adaptability to structures with arbitrary geometries and complex boundary conditions is also important to topology optimization in practical engineering applications. A parallel parameterized level set topology optimization framework for large-scale structures with unstructured meshes is proposed in this work, in which the full-scale optimization is realized with distributed memory parallel computing technology while the arbitrary geometries and complex boundary conditions are conveniently handled with the usage of unstructured meshes. To realize the combination of distributed memory parallel computing technology and parameterized level set topology optimization using unstructured meshes, several means are taken: (1) the shape functions in finite element analysis are employed to parameterize the level set function; (2) the data structure called directed acyclic graph is adopted to represent the unstructured mesh; (3) the passive domain and boundary conditions are imposed directly on the geometry entities of the structures; (4) a multiple averaging filter is introduced to reduce the tiny structural members in the optimized results for the requirement of manufacturability. Several computing tests are presented in this paper, which verify the stability, efficiency, scalability, and the potential to discover new structure styles of the framework. In addition to the requirements of full-scale optimization, the adaptability to structures with arbitrary geometries and complex boundary conditions is also important to topology optimization in practical engineering applications. A parallel parameterized level set topology optimization framework for large-scale structures with unstructured meshes is proposed in this work, in which the full-scale optimization is realized with distributed memory parallel computing technology while the arbitrary geometries and complex boundary conditions are conveniently handled with the usage of unstructured meshes. To realize the combination of distributed memory parallel computing technology and parameterized level set topology optimization using unstructured meshes, several means are taken: (1) the shape functions in finite element analysis are employed to parameterize the level set function; (2) the data structure called directed acyclic graph is adopted to represent the unstructured mesh; (3) the passive domain and boundary conditions are imposed directly on the geometry entities of the structures; (4) a multiple averaging filter is introduced to reduce the tiny structural members in the optimized results for the requirement of manufacturability. Several computing tests are presented in this paper, which verify the stability, efficiency, scalability, and the potential to discover new structure styles of the framework. •A PLSM framework is proposed for large-scale practical engineering problems.•The shape function based PLSM handles irregular unstructured meshes well.•The multiple averaging filter proposed suits the domain decomposition strategy well.•The algorithm has good stability, efficiency, and scalability. |
| ArticleNumber | 115112 |
| Author | Wei, Peng Liu, Hui Lin, Haoju |
| Author_xml | – sequence: 1 givenname: Haoju surname: Lin fullname: Lin, Haoju organization: State Key Laboratory of Subtropical Building Science, School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510641, China – sequence: 2 givenname: Hui surname: Liu fullname: Liu, Hui email: h.liu@whu.edu.cn organization: Department of Engineering Mechanics, School of Civil Engineering, Wuhan University, Wuhan 430072, China – sequence: 3 givenname: Peng orcidid: 0000-0001-5826-1527 surname: Wei fullname: Wei, Peng email: ctpwei@scut.edu.cn organization: State Key Laboratory of Subtropical Building Science, School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510641, China |
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| Keywords | Topology optimization Unstructured mesh Parallel computing Parameterized level set method Sensitivity filter |
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| SubjectTerms | Boundary conditions Data structures Distributed memory Finite element method Manufacturability Optimization Parallel computing Parameterization Parameterized level set method Sensitivity filter Shape functions Structural members Topology optimization Unstructured mesh |
| Title | A parallel parameterized level set topology optimization framework for large-scale structures with unstructured meshes |
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