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Auteur principal: Ryazanov, V. V.
Format: Preprint
Publié: 2026
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Accès en ligne:https://arxiv.org/abs/2603.14058
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author Ryazanov, V. V.
author_facet Ryazanov, V. V.
contents The potential for using boundary functionals of random risk processes to solve nuclear safety problems at nuclear power plants is assessed. In certain situations (MSRs (Molten Salt Reactors), High-Temperature Gas-Cooled Reactors (HTGRs), pulverized fuel reactors, reactor startups, and accident analysis (core collapse)), neutron behavior changes significantly. Neutron clustering begins to play an important role, and the distributions characterizing neutron behavior change. The normal distribution is replaced by stable, but also limiting, distributions. Boundary functionals allow for precise calculation of the power quantile and provide a mathematical bridge between abstract directed percolation and engineering calculations of protection settings.
format Preprint
id arxiv_https___arxiv_org_abs_2603_14058
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Possibilities of applying boundary functionals of random processes to nuclear safety problems
Ryazanov, V. V.
Statistical Mechanics
The potential for using boundary functionals of random risk processes to solve nuclear safety problems at nuclear power plants is assessed. In certain situations (MSRs (Molten Salt Reactors), High-Temperature Gas-Cooled Reactors (HTGRs), pulverized fuel reactors, reactor startups, and accident analysis (core collapse)), neutron behavior changes significantly. Neutron clustering begins to play an important role, and the distributions characterizing neutron behavior change. The normal distribution is replaced by stable, but also limiting, distributions. Boundary functionals allow for precise calculation of the power quantile and provide a mathematical bridge between abstract directed percolation and engineering calculations of protection settings.
title Possibilities of applying boundary functionals of random processes to nuclear safety problems
topic Statistical Mechanics
url https://arxiv.org/abs/2603.14058