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A data-driven stochastic approach to model and analyze test data on fatigue response

机译:一种基于数据驱动的随机方法,用于对疲劳响应的测试数据进行建模和分析

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摘要

A stochastic approach to model and analyze test on the fatigue response of materials and laminated composites is developed. The developed approach is `data-driven' in nature. It has been customary to describe the fatigue response of metallic and laminated composite materials using a suitable parameter that can serve as the indicator and descriptor of damage accumulation. In the present methodology, the fatigue response of the material is quantified by interpreting the corresponding material parameter to be an embedded Markov process. The true probability distributions of the fatigue response parameter are extracted from sample test data based on an analytical approach, and they are used in the formulation. To this end, the Maximum Entropy Method is incorporated into the formulation. A recursive stochastic matrix equation is developed based on the test data using the theory of reliability and Fokker-Plank-Kolmogorov equation. Application of the methodology to a composite laminate is demonstrated.
机译:提出了一种对材料和层状复合材料的疲劳响应进行建模和分析测试的随机方法。开发的方法本质上是“数据驱动”的。通常习惯使用合适的参数描述金属和层压复合材料的疲劳响应,该参数可以用作损伤累积的指标和指标。在本方法中,通过将相应的材料参数解释为嵌入式马尔可夫过程来量化材料的疲劳响应。基于分析方法,从样品测试数据中提取疲劳响应参数的真实概率分布,并将其用于配方中。为此,在配方中加入了最大熵方法。使用可靠性理论和Fokker-Plank-Kolmogorov方程,基于测试数据,开发了一个递归随机矩阵方程。演示了该方法在复合层压板上的应用。

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