Crack and Flaw Identification in Statics and Dynamics, using Filter Algorithms and Soft Computing

  • Georgios E. Stavroulakis
  • Marek Engelhardt
  • Heinz Antes
Part of the CISM International Centre for Mechanical Sciences book series (CISM, volume 469)


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.


Neural Network Inverse Problem Kalman Filter Boundary Element Boundary Element Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© CISM, Udine 2005

Authors and Affiliations

  • Georgios E. Stavroulakis
    • 1
    • 2
  • Marek Engelhardt
    • 2
  • Heinz Antes
    • 2
  1. 1.Department of MathematicsUniversity of IoanninaGreece
  2. 2.Department of Civil EngineeringTechnical University of BraunschweigGermany

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