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A numerical approach to determine the sufficiency of given boundary data sets for uniquely estimating interior elastic properties

机译:一种确定给定边界数据集充分性的数值方法,用于唯一估计内部弹性特性

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摘要

We consider an inverse elasticity problem in which forces and displacements are known on the boundary and the material property distribution inside the body is to be found. In other words, we need to estimate the distribution of constitutive properties using the finite boundary data sets. Uniqueness of the solution to this problem is proved in the literature only under certain assumptions for a given complete Dirichlet-to-Neumann map. Another complication in the numerical solution of this problem is that the number of boundary data sets needed to establish uniqueness is not known even under the restricted cases where uniqueness is proved theoretically. In this paper, we present a numerical technique that can assess the sufficiency of given boundary data sets by computing the rank of a sensitivity matrix that arises in the Gauss-Newton method used to solve the problem. Numerical experiments are presented to illustrate the method.
机译:我们考虑一个反弹性问题,其中边界上的力和位移是已知的,并且将发现体内的材料属性分布。换句话说,我们需要使用有限边界数据集来估计本构特性的分布。仅在给定完整Dirichlet-to-Neumann映射的某些假设下,才能在文献中证明该问题的解决方案的唯一性。这个问题的数值解决方案的另一个复杂之处在于,即使在理论上证明唯一性的有限情况下,建立唯一性所需的边界数据集的数量也不知道。在本文中,我们提出了一种数值技术,可以通过计算用于解决问题的高斯-牛顿法中出现的灵敏度矩阵的秩来评估给定边界数据集的充分性。数值实验表明了该方法。

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