Machine learning (ML) and deep learning (DL), in particular, are common tools for anomaly
detection (AD). With the rapid increase in the number of Internet-connected devices, the …

In this work, a novel deep learning approach to unfold nuclear power reactor signals is
proposed. It includes a combination of convolutional neural networks (CNN), denoising …

This paper deals with the development, validation, and demonstration of an innovative
neutronic tool. The novelty of the tool resides in its versatility, since many different systems …

KWU pressurized water reactors, the neutron flux is measured with in-core and the ex-core
detectors. Investigating the signal fluctuations of these detectors at fixed burnup, periods of …

In a nuclear reactor, even operating at full power and steady-state conditions, fluctuations
are detected in the recording of any process parameter. These fluctuations (also called …

The paper presents CORE SIM+, a tool developed for diffusion-based neutron noise
simulations. The simulator is based on the 3-dimensional, two-energy group neutron …

Mechanical vibrations of core internals are among the main perturbations that induce
oscillations in the neutron flux field, also known as neutron noise. In this work, different …

Neutron noise equations, which are obtained by assuming small perturbations of
macroscopic cross sections around a steady-state neutron field and by subsequently taking …

This work is a contribution towards the development of computational methods that allow
investigation and prediction of reactor noise response due to in-core perturbations such as …

Enhancing the safety of nuclear power plants relies on the prompt and accurate
identification of potential anomalies within the reactor. This paper explores the application of …