This paper proposes an approach that combines reduced-order models with machine
learning in order to create physics-informed digital twins to predict high-dimensional output …

The generalized empirical interpolation method (GEIM) can be used to estimate the physical
field by combining observation data acquired from the physical system itself and a reduced …

Sensor positioning and real-time estimation of non-observable fields is an open question in
the nuclear sector, especially for advanced nuclear reactors. In Circulating Fuel Reactors …

In this paper, we apply the so-called generalized empirical interpolation method (GEIM) to
address the problem of sensor placement in nuclear reactors. This task is challenging due to …

The fast reconstruction of neutronic field in a nuclear core using reduced modeling and
limited observations has attracted considerable attention. In particular, four design …

Due to the multiple physics involved and their mutual and complex interactions, nuclear
engineers and researchers are constantly working on develo** highly accurate Multi …

The problem of estimating in real-time the state of a system by combining experimental data
and models has been extensively addressed in literature. In particular, there have been a lot …

The proper orthogonal decomposition (POD) method has been applied in nuclear reactor
physics to extract features of dominant flux or power. In particular, the gappy POD method is …

Abstract The Empirical Interpolation Method (EIM) and its generalized version (GEIM) can be
used to approximate a physical system by combining data measured from the system itself …

This paper deals with the use of Reduced Order Methods for neutronics modelling. This
approach is used whether both accuracy and computational efficiency are required. A very …