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

TL;DR

This paper presents an approach to optimize the placement of measurement instruments in a nuclear reactor core to improve neutronic activity field reconstruction using data assimilation, employing simulated annealing and algebraic enhancements.

Contribution

It introduces a novel method for instrument placement optimization in nuclear reactors using data assimilation and simulated annealing, with algebraic improvements for computational efficiency.

Findings

Optimized instrument placement improves reconstruction accuracy.

Algebraic enhancements reduce computational costs.

Method demonstrates effectiveness in nuclear reactor core modeling.

Abstract

Using data assimilation framework, to merge information from model and measurement, an optimal reconstruction of the neutronic activity field can be determined for a nuclear reactor core. 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 Simulated Annealing algorithm, based on the Metropolis-Hastings one. Moreover, in order to address the optimisation computing challenge, algebraic improvements of data assimilation have been developed and are presented here.