Monte Carlo simulation of prompt gamma-ray spectra from depleted uranium under D-T neutron irradiation and electron recoil spectra in a liquid scintillator detector
Jianguo Qin, Caifeng Lai, Rong Liu, Tonghua Zhu, Xinwei Zhang,, Bangjiao Ye

TL;DR
This paper presents a two-step Monte Carlo simulation method to efficiently and reliably calculate prompt gamma-ray and electron recoil spectra from depleted uranium under D-T neutron irradiation, validated against experimental data.
Contribution
The study introduces a two-step Monte Carlo approach combining MCNP5 and EGSnrc codes to improve computational efficiency and accuracy in gamma-ray and electron recoil spectrum simulations.
Findings
Simulations agree well with experimental data in the 0.4-3 MeV gamma-ray energy range.
The method accurately predicts electron recoil spectra below 4 MeVee.
The two-step approach enhances reliability and reduces computation time.
Abstract
To overcome the problem of inefficient computing time and unreliable results in MCNP5 calculation, a two-step method is adopted to calculate the energy deposition of prompt gamma-rays in detectors for depleted uranium spherical shells under D-T neutrons irradiation. In the first step, the gamma-ray spectrum for energy below 7 MeV is calculated by MCNP5 code; secondly, the electron recoil spectrum in a BC501A liquid scintillator detector is simulated based on EGSnrc Monte Carlo Code with the gamma-ray spectrum from the first step as input. The comparison of calculated results with experimental ones shows that the simulations agree well with experiment in the energy region 0.4-3 MeV for the prompt gamma-ray spectrum and below 4 MeVee for the electron recoil spectrum. The reliability of the two-step method in this work is validated.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
