Itô-calculus based mathematical models for stochastic nuclear reactor kinetics and dynamics simulations of low neutron source nuclear power plant (NPP) start-up
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Author(s)
Gordon, TL
Williams, MMR
Eaton, MD
Haigh, P
Type
Journal Article
Abstract
This paper investigates the effect thermal feedback has on the stochastic nuclear reactor dynamics of low
neutron source nuclear power plant (NPP) start-ups. Stochastic mathematical and computational models are
required to determine the probability of a stochastic power surge occurring during nuclear reactor start-up that
would damage the nuclear fuel. The aim is to design the nuclear reactor, the nuclear fuel, and the operational
start-up procedures in a manner that minimises the probability of a stochastic power surge occurring, which
damages the nuclear fuel, to a prescribed level of probabilistic risk (10−8–10−5). Recently, the Pál-Bell equations
have been used for such low neutron source nuclear reactor start-up simulations. However, the stochastic
nuclear reactor start-up models, based upon the Pál-Bell equations, cannot accommodate changes in the
macroscopic neutron cross-sections arising from feedback processes. An alternative approach that could, in
principle, include thermal feedback processes is the forward master equations. However, these are complex to
implement for multidimensional and multi-group stochastic nuclear reactor dynamics problems. In addition,
time-dependent analog Monte Carlo models could be used but these are computationally prohibitive for most
nuclear reactor start-up simulations. This is due to the stringent requirements on the statistical accuracy of the
safety probability associated with stochastic power surges. Therefore, this paper uses an alternative Itô-calculus
approach to compute the stochastic properties required for low neutron source NPP start-up. The Itô-calculus
approach is an approximate mathematical method, compared to the more general Pál-Bell and Monte Carlo
methods, for low neutron source nuclear reactor start-up and fast burst systems. Therefore, the implementation
of the Itô calculus method is first validated against the Caliban fast burst nuclear reactor experimental waittime results to understand the accuracy of the method. The implementation of a simple feedback model is also
verified against the point neutron kinetics equations. The neutron population CDF calculated using the PálBell equations without thermal feedback, and the safety probabilities computed with, and without, including
thermal feedback mechanisms are then analysed and assessed. These results demonstrate that the Itô-calculus
approach can be used to gain useful insight into the behaviour of stochastic nuclear kinetics and dynamics
during low neutron source NPP start-up. Furthermore, the results suggest that the safety probabilities computed
using the Pál-Bell method are not affected by neglecting thermal feedback mechanisms which is an important
result from a nuclear reactor safety perspective.
neutron source nuclear power plant (NPP) start-ups. Stochastic mathematical and computational models are
required to determine the probability of a stochastic power surge occurring during nuclear reactor start-up that
would damage the nuclear fuel. The aim is to design the nuclear reactor, the nuclear fuel, and the operational
start-up procedures in a manner that minimises the probability of a stochastic power surge occurring, which
damages the nuclear fuel, to a prescribed level of probabilistic risk (10−8–10−5). Recently, the Pál-Bell equations
have been used for such low neutron source nuclear reactor start-up simulations. However, the stochastic
nuclear reactor start-up models, based upon the Pál-Bell equations, cannot accommodate changes in the
macroscopic neutron cross-sections arising from feedback processes. An alternative approach that could, in
principle, include thermal feedback processes is the forward master equations. However, these are complex to
implement for multidimensional and multi-group stochastic nuclear reactor dynamics problems. In addition,
time-dependent analog Monte Carlo models could be used but these are computationally prohibitive for most
nuclear reactor start-up simulations. This is due to the stringent requirements on the statistical accuracy of the
safety probability associated with stochastic power surges. Therefore, this paper uses an alternative Itô-calculus
approach to compute the stochastic properties required for low neutron source NPP start-up. The Itô-calculus
approach is an approximate mathematical method, compared to the more general Pál-Bell and Monte Carlo
methods, for low neutron source nuclear reactor start-up and fast burst systems. Therefore, the implementation
of the Itô calculus method is first validated against the Caliban fast burst nuclear reactor experimental waittime results to understand the accuracy of the method. The implementation of a simple feedback model is also
verified against the point neutron kinetics equations. The neutron population CDF calculated using the PálBell equations without thermal feedback, and the safety probabilities computed with, and without, including
thermal feedback mechanisms are then analysed and assessed. These results demonstrate that the Itô-calculus
approach can be used to gain useful insight into the behaviour of stochastic nuclear kinetics and dynamics
during low neutron source NPP start-up. Furthermore, the results suggest that the safety probabilities computed
using the Pál-Bell method are not affected by neglecting thermal feedback mechanisms which is an important
result from a nuclear reactor safety perspective.
Date Issued
2024-07
Date Acceptance
2024-02-22
Citation
Annals of Nuclear Energy, 2024, 202
ISSN
0306-4549
Publisher
Elsevier BV
Journal / Book Title
Annals of Nuclear Energy
Volume
202
Copyright Statement
© 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
License URL
Identifier
http://dx.doi.org/10.1016/j.anucene.2024.110451
Publication Status
Published
Article Number
110451
Date Publish Online
2024-03-12