Estimation of Distributions of Contact Stressess and Displacements Using Regularization Schemes

S. Kubo, K. Ohji
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Abstract

Estimation of tractions and displacements on inaccessible boundaries, such as contact areas of solids, can be regarded as an inverse boundary value problem. In this study finite-element based inverse analysis schemes with regularization were applied to the estimation of the distributions of tractions and displacements on contact areas. The finite element equation was rewritten in terms of unknown boundary values on the contact area using over-prescribed boundary values. This equation was solved for the boundary values on the contact area. Like many other inverse problems, this inverse problem was severely ill-conditioned and the estimated distributions were very sensitive to the over-prescribed boundary values used in the estimation. To overcome the ill-posedness of this boundary value inverse problem, the function expansion method and Tikhonov regularization were introduced in the finite element-based inverse analysis scheme. The number of terms in the function expansion and the smoothing parameter in Tikhonov regularization were regarded as regularization parameters in the inverse analysis. To determine the optimum value of these regularization parameters, the estimated error criterion and the AIC were introduced. The usefulness of the finite element-based inversion scheme was examined by numerical simulations. It was found that the distributions of tractions and displacements can be estimated reasonably even from noisy observations by using the finite-element based inverse analysis schemes with regularization. The optimum value of the regularization parameters can be estimated by the estimated error criterion or by the AIC.
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用正则化方法估计接触应力和位移的分布
在不可接近的边界(如固体的接触区域)上的牵引力和位移的估计可以看作是一个反边值问题。本文将基于正则化的有限元反分析方法应用于接触区域上的牵引力和位移分布的估计。将有限元方程改写为接触区域上未知边界值的形式,并使用过规定的边界值。求解了接触区域的边界值。像许多其他反问题一样,这个反问题是严重病态的,估计的分布对估计中使用的过度规定的边界值非常敏感。为了克服该边值反问题的病态性,在基于有限元的反分析方案中引入了函数展开法和Tikhonov正则化。将函数展开中的项数和Tikhonov正则化中的平滑参数作为逆分析中的正则化参数。为了确定这些正则化参数的最优值,引入了估计误差准则和AIC。数值模拟验证了基于有限元的反演方法的有效性。结果表明,采用正则化的有限元反分析格式,即使在有噪声的观测中,也能合理地估计出牵引力和位移的分布。正则化参数的最优值可以通过估计误差准则或AIC来估计。
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