Calibration of a Fluid-Structure Problem with Keras

Abstract

In this short paper we report on an inverse problem issued from a physical system, namely a fluid structure problem where the parameters are the rigidity constant, the solid-fluid density ratio and the fluid viscosity. We have chosen a simple geometry so that the numerical solution of the system is easy. We compare the solution of this inverse problem by a Neural Network with a more classical solution obtained with a genetic algorithm. The Neural Network does much better.