Young's Modulus and Poisson's Ratio Estimation Based on PSO Constriction Factor Method Parameters Evaluation

G. Dias, R. Magalhães, D. Ferreira, B. Barbosa
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引用次数: 2

Abstract

The knowledge of materials' mechanical properties in design during product development phases is necessary to identify components and assembly problems. These are problems such as mechanical stresses and deformations which normally cause plastic deformation, early fatigue or even fracture. This article is aimed to use particle swarm optimization (PSO) and finite element inverse analysis to determine Young's Modulus and Poisson's ratio from a cantilever beam, manufactured in ASTM A36 steel, subjected to a load of 19.6 N applied to its free end. The cantilever beam was modeled and simulated using a commercial FEA software. Constriction Factor Method (PSO variation) was used and its parameters were analyzed in order to improve errors. PSO results indicated Young's Modulus and Poisson's ratio errors of around 1.9% and 0.4%, respectively, when compared to the original material properties. Improvement in the data convergence and a reduction in the number of PSO iterations was observed. This shows the potentiality of using PSO along with Finite Element Inverse Analysis for mechanical properties evaluation.
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基于PSO收缩因子法的杨氏模量和泊松比估计
在产品开发阶段的设计中,了解材料的机械性能对于识别零部件和装配问题是必要的。这些是诸如通常引起塑性变形、早期疲劳甚至断裂的机械应力和变形的问题。本文旨在使用粒子群优化(PSO)和有限元逆分析来确定由ASTM A36钢制造的悬臂梁的杨氏模量和泊松比,悬臂梁的自由端承受19.6N的载荷。使用商业有限元分析软件对悬臂梁进行建模和模拟。采用收缩因子法(PSO-variation)对其参数进行分析,以改善误差。PSO结果表明,与原始材料性能相比,杨氏模量和泊松比误差分别约为1.9%和0.4%。观察到数据收敛性的改善和PSO迭代次数的减少。这表明了将粒子群算法与有限元逆分析一起用于力学性能评估的潜力。
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CiteScore
2.70
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0.00%
发文量
21
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