期刊
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
卷 64, 期 6, 页码 4343-4353出版社
SPRINGER
DOI: 10.1007/s00158-021-03018-7
关键词
Topology optimization; Parallel computing; Large scale; PETSc; Python C-Extension module; Python wrapper; 3D printing; Porous structures; Robust design; Infill
资金
- ETH Zurich
- European Union [812765]
- Villum Investigator Project InnoTop - Villum Foundation
- Marie Curie Actions (MSCA) [812765] Funding Source: Marie Curie Actions (MSCA)
This paper introduces a Python wrapper and extended functionality of a parallel topology optimization framework, making it easier for users to define problems, expand the potential user base, and use it for educational purposes. By adding features such as passive domains and local volume constraints, the framework can be better applied to real-world design applications.
This paper presents a Python wrapper and extended functionality of the parallel topology optimization framework introduced by Aage et al. (Topology optimization using PETSc: an easy-to-use, fully parallel, open source topology optimization framework. Struct Multidiscip Optim 51(3):565-572, 2015). The Python interface, which simplifies the problem definition, is intended to expand the potential user base and to ease the use of large-scale topology optimization for educational purposes. The functionality of the topology optimization framework is extended to include passive domains and local volume constraints among others, which contributes to its usability to real-world design applications. The functionality is demonstrated via the cantilever beam, bracket and torsion ball examples. Several tests are provided which can be used to verify the proper installation and for evaluating the performance of the user's system setup. The open-source code is available at https:// github. com/thsmit/, repository TopOpt_in_PETSc_wrapped_in_Python.
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