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Spent nuclear fuel (SNF) antineutrino flux is an important source of uncertainties for a reactor neutrino flux prediction. However, if one want to determine the contribution of spent fuel, many data are needed, such as the amount of spent…

Instrumentation and Detectors · Physics 2017-05-22 X. B. Ma , Y. F. Zhao , Y. X. Chen , W. L. Zhong , F. P. An

Nuclear fission reactors are abundant sources of antineutrinos. The flux and spectrum of antineutrinos emitted by a reactor can indicate its activity and composition, suggesting potential applications of neutrino measurements beyond…

OpenMC is an open-source Monte Carlo code with increasing relevance in criticality safety and reactor physics applications. While its validation has covered a broad range of systems, its performance in spent nuclear fuel storage scenarios…

Nuclear archaeology research provides scientific methods to reconstruct the operating histories of fissile material production facilities to account for past fissile material production. While it has typically focused on analyzing material…

Physics and Society · Physics 2024-02-27 Benjamin Jung , Antonio Figueroa , Malte Göttsche

The accurate calculation and uncertainty quantification of the characteristics of spent nuclear fuel (SNF) play a crucial role in ensuring the safety, efficiency, and sustainability of nuclear energy production, waste management, and…

Machine Learning · Computer Science 2023-08-17 Arnau Albà , Andreas Adelmann , Lucas Münster , Dimitri Rochman , Romana Boiger

Neutronic calculations for reactors are a daunting task when using Monte Carlo (MC) methods. As high-performance computing has advanced, the simulation of a reactor is nowadays more readily done, but design and optimization with multiple…

Neural and Evolutionary Computing · Computer Science 2024-03-22 Deborah Schwarcz , Nadav Schneider , Gal Oren , Uri Steinitz

Nuclear reactors are often modeled as inflexible baseload generators with fixed downtimes and restrictive ramping constraints. In practice, however, a reactor's operational flexibility is closely tied to its fuel cycle and associated…

Systems and Control · Electrical Eng. & Systems 2025-09-03 Shiny Choudhury , Michael Davidson , George Tynan

In a conventional light water reactor loaded with a range of uranium and plutonium-based fuel mixtures, the variation in antineutrino production over the cycle reflects both the initial core fissile inventory and its evolution. Under the…

Nuclear Experiment · Physics 2018-01-17 Adam Bernstein , Nathaniel Bowden , Anna Erickson

Nuclear power is a significant source of electricity in the United States, but the average U.S. nuclear power plant is around 40 years old. Safe management of spent nuclear fuel (SNF) is a crucial aspect of the back end of the nuclear fuel…

The ability to infer the reactor flux from spent fuel or seized fissile material would enhance the tools of nuclear forensics and nuclear nonproliferation significantly. We show that reactor flux can be inferred from the ratios of xenon-136…

Nuclear Theory · Physics 2015-06-05 A. C. Hayes , Gerard Jungman

Physical Reservoir Computing (PRC) leverages the intrinsic nonlinear dynamics of physical substrates, mechanical, optical, spintronic, and beyond, as fixed computational reservoirs, offering a compelling paradigm for energy-efficient and…

Robotics · Computer Science 2026-04-10 Yogesh Phalak , Wen Sin Lor , Apoorva Khairnar , Benjamin Jantzen , Noel Naughton , Suyi Li

Circulating-fuel reactors (CFRs) lose reactivity when delayed-neutron precursors (DNPs) drift out of the core and may regain part of it when the fuel re-enters the core. This paper formulates a physics-based description of both effects by…

Computational Physics · Physics 2026-05-05 Lubomír Bureš

The Reservoir Computing (RC) framework states that any non-linear, input-driven dynamical system (the reservoir) exhibiting properties such as a fading memory and input separability can be trained to perform computational tasks. This broad…

Emerging Technologies · Computer Science 2019-06-20 Matthew Dale , Julian F. Miller , Susan Stepney , Martin A. Trefzer

A physical neural network (PNN) has both the strong potential to solve machine learning tasks and intrinsic physical properties, such as high-speed computation and energy efficiency. Reservoir computing (RC) is an excellent framework for…

Chaotic Dynamics · Physics 2024-12-18 Tomoyuki Kubota , Yusuke Imai , Sumito Tsunegi , Kohei Nakajima

The large quantities of antineutrinos produced through the decay of fission fragments in nuclear reactors provide an opportunity to study the properties of these particles and investigate their use in reactor monitoring. The reactor…

Developing accurate models for chemical reactors is often challenging due to the complexity of reaction kinetics and process dynamics. Traditional approaches require retraining models for each new system, limiting generalizability and…

Computational Engineering, Finance, and Science · Computer Science 2025-05-29 Zihao Wang , Zhe Wu

Dry casks for spent nuclear fuel (SNF) ensure the safe storage of SNF and provide radiation shielding. However, the presence of the thick casks encompassing several layers of steel and concrete makes inspection of the SNF a challenging…

Instrumentation and Detectors · Physics 2021-10-19 Zhihua Liua , Ming Fang , Jon George , Ling-Jian Meng , Angela Di Fulvio

Antineutrinos produced at nuclear reactors constitute a severe source of background for the detection of geoneutrinos, which bring to the Earth's surface information about natural radioactivity in the whole planet. In this framework we…

Instrumentation and Detectors · Physics 2015-06-23 Marica Baldoncini , Ivan Callegari , Giovanni Fiorentini , Fabio Mantovani , Barbara Ricci , Virginia Strati , Gerti Xhixha

In this paper, we take the first steps towards a novel unified framework for the analysis of perturbations in both the Time and Frequency domains. The identification of type and source of such perturbations is fundamental for monitoring…

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