In this paper scientific research on using the hybrid algorithm in optimization of the dynamic structures was carried out. The boundary-initial problem for elastodynamics was solved by using boundary element method (BEM) [2]. The hybrid algorithm being the coupling of the evolutionary algorithm, gradient algorithm and the artificial neural network was carried out. Topology and shape optimization problems were considered for different criteria, which concern: mass, displacements, stresses, compliance and natural frequencies. As a tool for the modeling of boundary shape the NURBS curves were applied. Several numerical examples testifying to the effectiveness and efficiency of the proposed methods of optimization were carried out, a few interesting tests are included in the paper.
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The paper presents the connected evolutionary and gradient identification of the internal defects in an elastic body under dynamical load. The identification proceeds on the basis of the knowledge about boundary displacements in some sensor points. In the first step the evolutionary algorithm (EA) identifies the number, kind, position and size of internal defects. The fitness function is computed with the help of the pseudo-gaussian fuzzy inference systems (PGFISs). In the second step the gradient method of identification is used to obtain more precise results. The structure of the chromosome and the connection between the EA and the PGFIS is presented. The results of identification in an elastic rectangular under sinusoidal load with internal defects in the form of crack or circular voids are shown.
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