Stochastic Method for Delayed Neutron Precursors Transport in Liquid Fuel

TL;DR

This paper introduces a stochastic Monte Carlo method for modeling delayed neutron precursor transport in liquid fuel, incorporating advection and diffusion effects through Green's functions, validated on a 1D system.

Contribution

The paper presents a novel stochastic approach using Green's functions to model DNP transport, extending Monte Carlo techniques with a probabilistic interpretation of ADR equations.

Findings

Method accurately captures fuel velocity effects on neutron flux

Reactivity decreases with increased fuel speed

Diffusion can mitigate the impact of fuel velocity

Abstract

This paper presents a novel stochastic method for modeling the transport of Delayed Neutron Precursors (DNPs) in liquid nuclear fuel. The method incorporates advection and diffusion effects into the Monte Carlo solution of the neutron balance equation by leveraging the Green's function of the advection-diffusion-reaction (ADR) equation. For a 1D system, we demonstrate that the Green's function can be interpreted as the Probability Density Function (PDF) of the position increment of a Brownian motion with drift. Using this interpretation, the position of DNPs is sampled via a time-of-flight process combined with a drift and diffusion model. The method is validated on a modified 1D rod problem, where results from the Monte Carlo implementation are compared against those obtained using a deterministic approach. The comparison confirms that the method accurately captures the impact of fuel velocity and diffusion on neutron flux. As expected, the fuel velocity shifts the neutron flux. Reactivity decreases as a function of speed while diffusion can counteract this decrease under certain conditions. While the current study is limited to 1D systems, the approach could be extended to higher dimensions and more complex geometries by replacing the Green's function with the Stochastic Differential Equation (SDE) associated with the ADR equation.