One aspect of the safety and security of nuclear reactors is to identify the distribution of neutron flux within the reactor with the highest possible accuracy. For this purpose, fission chamber detectors are widely used to measure the neutron field and thus allow control of the neutron flux within the reactors. However, with neutrons, gamma-rays are also emitted by nuclei and detected by fission chambers. As a result, physical processes are used to bring out the desired neutron spectrum.
In this work, we propose a new approach to solve the problem of neutron/gamma discrimination at the output of the preamplifier of a fission chamber. It is the application of blind source separation methods based on the decomposition of tensor element signals to extract the independent components constituting the signals delivered by a fission chamber.
For nuclear safety reasons, we simulated the neutron flux inside CNESTEN’s TRIGA Mark II reactor using Garfield++ bound Geant4 Monte Carlo methods. Indeed, Geant4 allowed us to model the fission chamber whereas Garfield++ allowed us to simulate the drift parameters from the ionization of the filling gas. We compared these models with those obtained using pyFC (python-based simulation of Fission Chambers).
Mounia Laassiri (ASP2016 Alumna)