An inverse problem in nonlinear elastostatics is considered which concerns the identification of unilateral contact cracks by means of boundary measurements for given static loadings. Highly nonlinear structural behav- iour like closed cracks can hardly be identified. In this case. The analysis of more than one loading cases is pro- posed and tested in this paper. the direct problem is modelled by using a direct multiregion boundary element fromulation. The arising liner complementarity problem is solved explicitly by a pivoting (Lemke) technique. In view of the complexity of the inverse problem, neural network based identification approach is adopted which uses feed-forward multilayer neural networks trained by back-propagation, error-driven supervised training.
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