Efficient calculation of reactor noise via Ito-Langevin Process for correlated fluctuations

TL;DR

This paper introduces an Ito-Langevin process to efficiently model and simulate the correlated neutron noise in heterogeneous sub-critical systems, reducing computational costs and aiding reactor diagnostics.

Contribution

It derives a novel stochastic process framework that captures super-Poisson deviations in neutron noise, enabling faster simulations for reactor noise analysis.

Findings

Derivation of an Ito-Langevin process for neutron noise

Reduction in computational resources for noise simulation

Potential applications in reactor design and safety assessments

Abstract

We derive an Ito-Langevin stochastic process that captures the time-dependent deviation from Poisson behavior of the noise detected from a general heterogeneous sub-critical neutron system. Using the probability generating function for the actual physical process, we deduce the super-Poisson deviation of the covariance matrix of counts at the detector due to neutron multiplication upon fission. This leads to a general form that coincides with the second moment of an Ito process. This comparison facilitates the formulation of a corresponding effective Langevin equation, which potentially enables simulations that significantly reduce the computational resources required compared to direct simulation of the system's actual noise. This method could assist in designing sub-critical noise experiments for licensing new research reactors, for improving cross-section libraries and for non-destructive assays of spent fuel.