Abstract
Numerical methods for the solution of crack and flaw identification problems in two-dimensional elastomechanics are presented in this chapter. The mechanical modelling is based on boundary element techniques, with special care of appropriate crack modeling. The possibility of partially or totally closed cracks (unilateral contact effects) is taken into account by means of suitable contact mechanics’ techniques which are based on linear complementarity algorithms. The identification problem is formulated within a general framework of output error minimization (least-squares data fitting) for an appropriately parametrized mechanical model. Backpropagation neural networks and filter-driven optimization, realized by extended Kalman filter algorithms, are used for the solution of the inverse problems. For the two-dimensional examples presented here the proposed method has similar performance for classical crack and flaw identification problems. The identification using the nonlinear model of unilateral cracks is a considerably more difficult task. The methods can be extended in order to cover more general parameter identification problems.
Partial support from the German Research Foundation (DFG) and the Greek-German scientific cooperation project IKYDA 2001, is greatfully acknowledged. These notes are partially based on common research work with Prof. Rafael Gallego, Granada, Spain and Assistant Prof. Aristidis Likas, Ioannina, Greece. More details can be found in the cited original publications. The authors takes the opportunity to express their cordial thanks.
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Stavroulakis, G.E., Engelhardt, M., Antes, H. (2005). Crack and Flaw Identification in Statics and Dynamics, using Filter Algorithms and Soft Computing. In: MrĂłz, Z., Stavroulakis, G.E. (eds) Parameter Identification of Materials and Structures. CISM International Centre for Mechanical Sciences, vol 469. Springer, Vienna. https://doi.org/10.1007/3-211-38134-1_5
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