Shape optimization using a level set based mesh evolution method: an overview and tutorial

Pub Date : 2023-10-31 DOI:10.5802/crmath.498
Charles Dapogny, Florian Feppon
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引用次数: 1

Abstract

This article revolves around a recent numerical framework for shape and topology optimization, which features an exact mesh of the shape at each iteration of the process, while still leaving the room for an arbitrary evolution of the latter (including changes in its topology). In a nutshell, two complementary representations of the shape are combined: on the one hand, it is meshed exactly, which allows for precise mechanical calculations based on the finite element method; on the other hand, it is described implicitly, using the level set method, which makes it possible to track its evolution in a robust way. In the first part of this work, we overview the main aspects of this numerical strategy. After a brief presentation of some necessary background material – related to shape optimization and meshing, among others – we describe the numerical schemes involved, notably when it comes to the practice of the level set method, the remeshing algorithms, and the considered optimization solver. This strategy is illustrated with 2d and 3d numerical examples in various physical contexts. In the second part of this article, we propose a simple albeit efficient python-based implementation of this framework. The code is described with a fair amount of details, and it is expected that the reader can easily elaborate upon the presented examples to tackle his own problems.
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形状优化使用基于水平集的网格进化方法:概述和教程
本文围绕最近的形状和拓扑优化的数值框架展开,该框架在过程的每次迭代中都具有精确的形状网格,同时仍然为后者的任意演变(包括其拓扑的变化)留下空间。简而言之,形状的两种互补表示相结合:一方面,它被精确地网格化,这允许基于有限元方法的精确力学计算;另一方面,它是隐式描述的,使用水平集方法,这使得以鲁棒的方式跟踪其演变成为可能。在这项工作的第一部分,我们概述了这个数字策略的主要方面。在简要介绍了一些必要的背景材料(与形状优化和网格划分相关)之后,我们描述了所涉及的数值方案,特别是当涉及到水平集方法、网格划分算法和考虑的优化求解器的实践时。在各种物理环境下,用2d和3d数值例子说明了这种策略。在本文的第二部分中,我们提出了这个框架的一个简单但高效的基于python的实现。代码描述了相当多的细节,希望读者能够轻松地详细说明所提供的示例来解决自己的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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