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首页> 外文期刊>Journal of Computational Science and Technology >Stochastic Homogenization Analysis of a Particle Reinforced Composite Material using an Approximate Monte-Carlo Simulation with the Weighted Least Square Method
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Stochastic Homogenization Analysis of a Particle Reinforced Composite Material using an Approximate Monte-Carlo Simulation with the Weighted Least Square Method

机译:颗粒增强复合材料的随机均质分析,采用加权最小二乘法的近似蒙特卡洛模拟

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References(11) Cited-By(3) This paper describes a stochastic homogenization analysis of a particle reinforced composite material using an approximation technique. In order to analyze the influence of a microscopic random variation of an elastic property of a component material on the homogenized elastic property of a particle reinforced composite material, the Monte-Carlo simulation is employed. Since the conventional Monte-Carlo simulation sometimes involves a higher computational cost, an approximate stochastic homogenization method using the Monte-Carlo simulation combined with a polynomial-based approximation technique is employed, and accuracy of the approximate Monte-Carlo simulation is investigated. In order to apply a lower order approximation to the approximate Monte-Carlo simulation effectively, the weighted least square method is proposed, and its effectiveness is discussed with the numerical results.
机译:参考文献(11)Cyed-By(3)本文描述了一种使用近似技术的颗粒增强复合材料的随机均质分析。为了分析组成材料的弹性的微观随机变化对颗粒增强复合材料的均质弹性特性的影响,采用了蒙特卡洛模拟。由于常规的蒙特卡洛模拟有时会涉及较高的计算成本,因此,采用了蒙特卡洛模拟与基于多项式的近似技术相结合的近似随机均化方法,并研究了近似蒙特卡洛模拟的准确性。为了将低阶近似有效地应用于近似蒙特卡洛模拟,提出了加权最小二乘法,并结合数值结果讨论了其有效性。

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