Identification of contamination flux in a domain of porous media as an inverse problem solved with Artificial Neural Networks

After a short introduction and main issues associated with inverse problem, three examples are chosen to illustrate the application of Artificial Neural Networks in the inverse problems solution. For a steady state convection problem, assuming given concentration field values in a few measurement points and values of hydraulic head in the same piezometers, the source of the concentration and its intensity are deduced using Artificial Neural Networks (ANNs). The same method is used for identification of diffusivity vector. To illustrate the reliability of the procedure, the case of randomly perturbed data is presented. The main conclusion states that the soft method seems to be very automatic and convenient in solving a large family of inverse problems.