Related papers: Cross-disciplinary Reactor-to-Repository Framework…
This paper introduces a deep reinforcement learning (RL) framework for optimizing the operations of power plants pairing renewable energy with storage. The objective is to maximize revenue from energy markets while minimizing storage…
The recent observation of Coherent Elastic Neutrino Nucleus Scattering (CE{\nu}NS) with neutrinos from pion decay at rest ({\pi}-DAR) sources by the COHERENT Collaboration has raised interest in this process in the search for new physics.…
We present a stochastic framework for low-population dynamics in circulating-fuel reactors (CFRs) that captures delayed-neutron precursor (DNP) transport without delay terms. Starting from a modified point-kinetics model with two…
Artificial neural networks with internal dynamics exhibit remarkable capability in processing information. Reservoir computing (RC) is a canonical example that features rich computing expressivity and compatibility with physical…
CONSORT is the UK's last remaining civilian research reactor, and its present core is soon to be removed. This study examines the feasibility of re-using the reactor facility for accelerator-driven systems research by replacing the fuel and…
Advanced nuclear fission, which encompasses various innovative nuclear reactor designs, could contribute to the decarbonization of the United States electricity sector. However, little is known about how cost-competitive these reactors…
Realistic nuclear level densities (NLDs) obtained within the spectral distribution method (SDM) are employed to study nuclear processes of astrophysical interest. The merit of SDM lies in the fact that the NLDs corresponding to many body…
Reservoir Computing (RC) models, a subclass of recurrent neural networks, are distinguished by their fixed, non-trainable input layer and dynamically coupled reservoir, with only the static readout layer being trained. This design…
Reservoir computing (RC) is a state-of-the-art machine learning method that makes use of the power of dynamical systems (the reservoir) for real-time inference. When using biological complex systems as reservoir substrates, it serves as a…
Reservoir Computing (RC) has become popular in recent years thanks to its fast and efficient computational capabilities. Standard RC has been shown to be equivalent in the asymptotic limit to Recurrent Kernels, which helps in analyzing its…
10 years from now medium baseline reactor experiments will attempt to determine the neutrino mass hierarchy from the differences (RL+PV) between the extrema of the Fourier transformed neutrino spectra. Recently Qian et al. have claimed that…
Over the past decade, the investigation of machine learning (ML) within the field of nuclear engineering has grown significantly. With many approaches reaching maturity, the next phase of investigation will determine the feasibility and…
Neutrinos and their weak interactions play a vital role in the physics of core-collapse supernovae and binary neutron star mergers. Their description within astrophysical simulations, including the weak rates, is of pivotal importance not…
The RENO experiment reports measured flux and energy spectrum of reactor electron antineutrinos\,($\overline{\nu}_e$) from the six reactors at Hanbit Nuclear Power Plant. The measurements use 966\,094\,(116\,111)\,$\overline{\nu}_e$…
Deeper insight into the features of a reactor as a source of antineutrinos is required for making further advances in studying the fundamental properties of the neutrino. The relationship between the thermal power of a reactor and the rate…
Reservoir computing is a machine learning paradigm that uses a high-dimensional dynamical system, or \emph{reservoir}, to approximate and predict time series data. The scale, speed and power usage of reservoir computers could be enhanced by…
The age of exascale computing has arrived and the risks associated with neutron and other atmospheric radiation are becoming more critical as the computing power increases, hence, the expected Mean Time Between Failures will be reduced…
The nature of the supernova remnants (SNRs) 3C 397 and W49B has long been a subject of debate, with prior studies offering conflicting interpretations between thermonuclear and core-collapse scenarios. To help settle this debate, we present…
The cross sections for neutrino scattering off the 12C and 16O nuclei are calculated within the framework of the continuum Random Phase Approximation. A model to consider also the final state interactions is developed. Total…
The petroleum industry faces unprecedented challenges in reservoir management, requiring rapid integration of complex multimodal datasets for real-time decision support. This study presents a novel integrated framework combining…