基于相场的多材料梯度界面拓扑优化的统一算法框架

IF 2.7 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
Qian Yu, Qing Xia, Yibao Li, Chao Yang
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引用次数: 0

摘要

本文提出了一种基于相场法的多材料梯度界面拓扑优化的统一算法框架。在该框架中,将拓扑优化问题转化为求解一组线性偏微分方程。然后,我们引入标量变量对材料性质进行分级,从而在有效弹性张量中产生复杂的非线性插值算子。然后,我们定义了一个辅助变量来代替线性椭圆方程系统的所有非线性变换。将二阶精确的Crank-Nicolson格式应用于重新表述的系统,其中所有高阶非线性项都以半显式方式处理。通过数值算例证明了该算法框架是无条件能量稳定的,并证明了其稳定性和准确性。研究了拓扑设计中具有不同界面行为的一系列基准问题,验证了该方法的有效性。分析了模型中不同参数的敏感性,评价了它们对所得结构的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Unified Algorithm Framework for Phase-Field Based Multimaterial Topology Optimization With Various Graded Interfaces

In this work, we present a unified algorithm framework for multimaterial topology optimization with various graded interfaces based on the phase field method. In the framework, the topology optimization problem is transformed into solving a set of linear partial differential equations (PDEs). We then introduce a scalar variable to grade the material property, resulting in a complex nonlinear interpolation operator in the effective elastic tensor. Following that, we define an auxiliary variable to substitute all the nonlinear transformations for a linear elliptic equation system. A second-order accurate Crank–Nicolson scheme is applied on the reformulated system, in which all high-order nonlinear terms are treated in a semi-explicit fashion. We prove that the proposed algorithm framework is unconditionally energy stable and demonstrate its stability as well as accuracy by numerical examples. A series of benchmark problems with different interfacial behaviors in topological design are investigated to verify the effectiveness of our method. The sensitivity of different parameters in the model is analyzed to evaluate their effects on the resulting structure.

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来源期刊
CiteScore
5.70
自引率
6.90%
发文量
276
审稿时长
5.3 months
期刊介绍: The International Journal for Numerical Methods in Engineering publishes original papers describing significant, novel developments in numerical methods that are applicable to engineering problems. The Journal is known for welcoming contributions in a wide range of areas in computational engineering, including computational issues in model reduction, uncertainty quantification, verification and validation, inverse analysis and stochastic methods, optimisation, element technology, solution techniques and parallel computing, damage and fracture, mechanics at micro and nano-scales, low-speed fluid dynamics, fluid-structure interaction, electromagnetics, coupled diffusion phenomena, and error estimation and mesh generation. It is emphasized that this is by no means an exhaustive list, and particularly papers on multi-scale, multi-physics or multi-disciplinary problems, and on new, emerging topics are welcome.
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