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PolyPlas: a Python implementation of a topology optimization framework for plasticity with unstructured polygonal finite elements

delete2025-08-19
delete0
PRE
AI
E
Emily Alcazar
J
Jonathan B. Russ
G
Gláucio H. Paulino *
DOI：10.1007/s00158-025-04055-2delete
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摘要

摘要

En 中文
我们提出PolyPlas，一种用于考虑von Mises塑性及非结构化多边形有限元网格的结构拓扑优化框架的Python实现。该代码的模块化结构借鉴了PolyTop——一个用于线性弹性材料 Compliance 最小化的早期教育代码。为了实现开源访问和可扩展性，PolyPlas完全采用Python实现。非线性前向问题通过带回溯线搜索的Newton-Raphson方法求解，以提高收敛稳定性。路径依赖的灵敏度分析采用伴随法进行，并在此对路径依赖算法和灵敏度分析的实现进行了详细讨论。最后，给出了若干数值算例，以说明PolyPlas在求解考虑von Mises塑性拓扑优化问题方面的能力，其结果形成了具有高能量吸收的结构。PolyPlas完全旨在用于教育目的，并激励拓扑优化领域中考虑能量耗散现象的进一步发展。
Keyword:
Topology optimization
Elastoplasticity
Educational code
Open-source

期刊

Structural and Multidisciplinary Optimization 封面图
Structural and Multidisciplinary Optimization
IF:
4
论文数:
4.9K
被引数:
1.7W

机构

D
Department of Civil and Environmental Engineering
学者数:
896
论文数: 520
被引数: 1
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