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A comparison of stochastic and data-driven FEM approaches to problems with insufficient material data

机译:随机有限元方法与数据驱动的有限元方法的比较

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In many applications the experimental results are not sufficient for material characterization. Nonetheless, predictive numerical simulations require to harness the available stress-strain data and to use them, e.g., as input parameters for finite element computations.In this contribution two strategies, a stochastic and a data-driven finite element method are compared and their advantages and disadvantages with respect to material uncertainties are studied. Examples in one and three dimensions are computed to illustrate the methods' properties. In particular, the data-driven method has shown to be a new and promising approach to the problem of imprecise material data. (C) 2019 Elsevier B.V. All rights reserved.
机译:在许多应用中,实验结果不足以进行材料表征。尽管如此,预测性数值模拟仍需要利用可用的应力-应变数据并将其用作有限元计算的输入参数。在此贡献中,比较了两种策略,随机方法和数据驱动的有限元方法,并比较了它们的优点。研究了材料不确定性方面的弊端。计算一维和三维示例以说明方法的属性。特别是,数据驱动方法已被证明是解决材料数据不精确问题的一种新的有前途的方法。 (C)2019 Elsevier B.V.保留所有权利。

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