Simulation of Physical Parameters for a Photoneutron Source

TL;DR

This paper presents a simulation method for a photoneutron source that accurately predicts neutron flux and energy spectrum with high efficiency, aiding the design and verification of nuclear experiments.

Contribution

The study introduces a subsection Monte Carlo simulation approach with covariance reduction techniques for complex geometries, improving efficiency over traditional methods.

Findings

Simulated neutron flux and energy spectrum agree with experimental data within 1.6% error.

The method achieves 23 times higher efficiency than normal Monte Carlo simulations.

Provides a fast, reliable way to predict physical parameters for photoneutron sources.

Abstract

A compact photoneutron source (PNS), based on an electron linac was designed and constructed to provide required nuclear data for the design of Thorium Molten Salt Reactor (TMSR). Many local shielding are built to reduce the background of neutron and {\gamma} rays, making the location of the time of flight (TOF) detector be fixed at 6.2 m place. Under the existing layout, some physical parameters are very difficult to get by the experiments, while can be obtained by the Monte Carlo simulation method. However, for the deep penetration problem of the neutron and {\gamma} rays transport in the channel of PNS with complex geometry, the normal Monte Carlo method is inefficient since electron transport calculation need a large amount of computing time and neutrons have little contribution to the detector in far-source region. In this work, the subsection method is applied in the simulation for PNS, which divide the simulation process in two steps, recording the neutron and {\gamma} rays information passing through the source window in the first step and adopting the covariance reduction techniques in the second step. The simulated neutron flux and energy spectrum at the TOF detector place with the relative error 1.6% are well agreement with the experimental results, achieving an efficiency 23 times better than the normal method. This method is fast and efficient in predicting the physical parameters, providing a required verification and initiating the foreseen physics experiment.