Sensor position optimization for flux mapping in a nuclear reactor using compressed sensing

Abstract

The paper presents a novel approach to sensor position optimisation based on compressed sensing (CS) and its application to neutron flux estimation in a nuclear reactor. An online flux mapping system (FMS) with a suitable algorithm is needed to continuously monitor neutron flux distribution from the measurements of in-core detectors in large nuclear reactors. In the present work, sensor positions are optimized by designing a sensing matrix Φ for the CS system in which the dictionary is known in advance. The sensing matrix is optimized by maximising the incoherence of the dictionary matrix and incorporating the estimation error in the optimization process. The proposed method uses the CS recovery technique, Basis Pursuit De-Noising (BPDN), for flux mapping along the vertical direction at the detector housing locations (1-D). In the end, the method suggests the optimized positions and number of sensors for efficient estimation of neutron flux inside the reactor core.