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

机译:基于PSO收缩因子方法参数评估的杨氏模量和泊松比估计

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摘要

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.
机译:产品开发阶段设计中的材料机械性能的知识是识别组件和装配问题的必要条件。这些是通常导致塑性变形,早期疲劳甚至骨折的机械应力和变形等问题。本文旨在使用粒子群优化(PSO)和有限元逆分析,以确定在ASTM A36钢中制造的悬臂梁的杨氏模量和泊松比,经受19.6n的负荷,其自由端应用于其自由端。使用商业FEA软件建模和模拟悬臂梁。使用收缩因子方法(PSO变异),分析其参数以改善误差。 PSO结果表明,与原材料特性相比,幼年模量分别约为1.9%和0.4%。观察到数据收敛性和减少PSO迭代的减少。这表明使用PSO以及机械性能评估的有限元逆分析的潜力。

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