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Numerical Approximation of Stochastic Systems for Composite Materials Based on Markov Chains

机译:基于马尔可夫链的复合材料随机系统的数值近似

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The crack density and crack growth rate are important parameters which are used to describe the fatigue damage and predict fatigue life of a composite material. Even the same good manufacturing practice, the fatigue damage of materials may be different. Also material properties often accompany random fluctuation. Thus stochastic systems are used to present the crack density and crack growth rate. It is surprising that there are not any numerical schemes established for hybrid stochastic systems in composite materials. In this paper, based on Markov chains, the Euler-aruyama method is developed, and the main aim is to show the convergence of the numerical solutions under the non-Lipschitz condition for hybrid stochastic material systems.
机译:裂纹密度和裂纹生长速率是重要的参数,用于描述复合材料的疲劳损伤和预测疲劳寿命。即使是相同的良好制造实践,材料的疲劳损坏可能是不同的。材料特性通常伴随着随机波动。因此,随机系统用于呈现裂纹密度和裂纹生长速率。令人惊讶的是,在复合材料中没有为混合随机系统建立的任何数值方案。本文基于马尔可夫链,开发了Euler-Aruyama方法,主要目的是展示了混合随机材料系统的非嘴唇尖端条件下数值解的收敛性。

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