A Neural Network Model for the Tomographic Analysis of Irradiated Nuclear Fuel Rods

A tomographic method based on a multilayer feed-forward artificial neural network is proposed for the reconstruction of gamma-radioactive fission product distribution in irradiated nuclear fuel rods. The quality of the method is investigated as compared to a conventional technique on experimental results concerning a Canada deuterium uranium reactor (CANDU)-type fuel rod irradiated in a TRIGA reactor.