Fast Vibroacoustic Optimization of Mechanical Structures Using Artificial Neural Networks

Abstract

An artificial neural network (ANN) is adjusted to make analytical approximation of objective function for a specific structural acoustic application. It is used as the replacement of the main real objective function during the optimization process. The goal of optimization is to find the best geometry modification of the considered model which is supposed to produce lower values of the radiated sound power levels. The result of this study shows that the function approximation by neural networks can reduce the duration of optimization procedure. Furthermore, the tuning of ANN internal parameter settings is a real challenge to be considered.