Optimal design of measurement network for neutronic activity field reconstruction by data assimilation

An optimal reconstruction of the neutronic activity field can be determined for a nuclear reactor core using a data assimilation framework to merge information from models and measurements. In this paper, we focus on solving the inverse problem of determining an optimal repartition of the measuring instruments within the core, to get the best possible results from the data assimilation reconstruction procedure. The position optimisation is realised using a Simulated Annealing algorithm, based on the Metropolis–Hastings proposition. Moreover, algebraic improvements of data assimilation have been developed, optimising their computational performance, and are presented here.