变边界条件下柔性机构的非线性弹性拓扑优化综合

IF 2.9 3区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY International Journal for Numerical Methods in Engineering Pub Date : 2024-10-29 DOI:10.1002/nme.7613
Lee R. Alacoque, Anurag Bhattacharyya, Kai A. James
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引用次数: 0

摘要

在柔性机构的拓扑优化中,边界条件的具体位置对最终的材料分布和设计性能有很大影响。与此同时,载荷和支撑的最有效位置往往难以人工找到。这极大地限制了拓扑优化在许多机构设计问题中的有效性。我们通过开发一种方法来消除这一限制,该方法可以自动确定规定的输入位移和一组支撑同时具有最佳材料布局的最佳定位。利用非线性弹性物理,我们合成了各种具有大输出位移、卡通响应和规定输出路径的柔性机构,从而在每种测试情况下都能显著提高性能。与以前的研究中使用人工设计的边界条件生成的最佳设计相比,本文提出的机制的性能提高了47%至380%。结果表明,非线性机构响应可能对边界条件位置特别敏感,如果没有自动化方法,很难找到有效的位置。
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Compliant Mechanism Synthesis Using Nonlinear Elastic Topology Optimization With Variable Boundary Conditions

In topology optimization of compliant mechanisms, the specific placement of boundary conditions strongly affects the resulting material distribution and performance of the design. At the same time, the most effective locations of the loads and supports are often difficult to find manually. This substantially limits topology optimization's effectiveness for many mechanism design problems. We remove this limitation by developing a method which automatically determines optimal positioning of a prescribed input displacement and a set of supports simultaneously with an optimal material layout. Using nonlinear elastic physics, we synthesize a variety of compliant mechanisms with large output displacements, snap-through responses, and prescribed output paths, producing designs with significantly improved performance in every case tested. Compared to optimal designs generated using manually designed boundary conditions used in previous studies, the mechanisms presented in this paper see performance increases ranging from 47% to 380%. The results show that nonlinear mechanism responses may be particularly sensitive to boundary condition locations and that effective placements can be difficult to find without an automated method.

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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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