圧電セラミックス多層複合平板の設計における近似最適化法

概要

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The present paper discusses an approximate optimization method using the neural network in order to design a multi-layered composite plate constructed of an isotropic structural layer and multiple piezoceramic layers of class 6mm. The puropse of this design is to determine the ticknesses of the piezoceramic layers, such that the maximum value of the electric potential distribution which controls the thermal displacement on the surface of the structural layer is minimized subject to stress constraints. Instead of the back propagation method, the quasi-Newton method is employed for an updating formula of the connection weights. By restricting the normalization range of the training data, total execution time necessary to the training process are remarkably reduced. Thus, performance of the learning algorithm is greatly improved. Applying the improved learning algorithm to the design of the multi-layered composite plate, fairly good results for the approximate optimization are obtained.
2004-05-25