Robustness of nuclear core activity reconstruction by data assimilation

TL;DR

This paper explores the use of data assimilation, inspired by meteorology, to accurately reconstruct nuclear core activity fields using measurements and models, analyzing robustness and instrument influence.

Contribution

It introduces a novel application of meteorological data assimilation techniques to nuclear core activity reconstruction, assessing robustness and instrument effects.

Findings

Reconstruction remains robust with decreasing measurement data.

Instrument type and spatial distribution significantly impact reconstruction accuracy.

The method effectively combines measurements and models for nuclear activity mapping.

Abstract

We apply a data assimilation techniques, inspired from meteorological applications, to perform an optimal reconstruction of the neutronic activity field in a nuclear core. Both measurements, and information coming from a numerical model, are used. We first study the robustness of the method when the amount of measured information decreases. We then study the influence of the nature of the instruments and their spatial repartition on the efficiency of the field reconstruction.