机械隐身结构和各向异性材料的并行优化

IF 2.7 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
Yifu Lu, Liyong Tong
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引用次数: 0

摘要

本文研究了机械隐身问题的结构拓扑和材料性能并行优化问题,同时考虑了隐身器件的宏观结构、微观结构和新型空间变化的微观结构取向,形成了一个多尺度拓扑优化问题。在这项工作中,我们(1)提出了一种新的基于元素的机械隐身目标函数;(2)建立多尺度优化问题的通用数学公式,包括原始目标函数与材料微观结构之间的新数学关系,并通过扩展的移动等面阈值(MIST)方法实现公式优化问题;(3)研究宏观结构与材料微观结构和取向的并行优化;(4)提出了一种新的全各向异性材料的解析方法来计算最优材料取向。通过基准数值算例验证了该方法的有效性。目前的数值结果表明,与文献相比,该方法可将隐身性能提高26.25%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Concurrent Optimization of Structures and Anisotropic Materials for Mechanical Cloaking

Concurrent Optimization of Structures and Anisotropic Materials for Mechanical Cloaking

This paper studies the concurrent optimization of structural topologies and material properties for mechanical cloaking problems, in which the macrostructures, microstructures, and novel spatially-varying microstructure orientations of the cloaking devices are simultaneously considered and form a multiscale topology optimization problem. In this work, we (1) propose a new element-based objective function for mechanical cloaking; (2) establish generic mathematical formulations to model the multiscale optimization problem, including a novel mathematical relation between the original objective function and material microstructures, and implement the formulated optimization problem via an extended moving iso-surface threshold (MIST) method; (3) investigate the concurrent optimization of the macrostructure and material microstructures and orientations; (4) propose a novel analytical method derived for fully anisotropic materials to compute the optimal material orientations. Benchmark numerical examples are investigated to validate the proposed method. The present numerical results show that the proposed method can improve the cloaking performance by up to 26.25% compared with the literature.

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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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