A comparison study of GEANT4 and MCNP6 on neutron-induced gamma simulation. (December 2022)

• Record Type: Journal Article
• Authors: Ge, Yi; Liang, Jingang; Zhang, Qiong; Tang, Wei; Munoz-Garcia, Agustin
• Is Part Of: Applied radiation and isotopes. Volume 190(2022)
• Publication Date: 2022-12
• Subjects: Neutron-induced gamma -- GEANT4 -- MCNP6 -- Nuclear well logging; Radiology -- Periodicals; Radiation -- Industrial applications -- Periodicals; Nuclear chemistry -- Periodicals; Internet resource; Periodical; 660.298
• DOI: 10.1016/j.apradiso.2022.110514
• Languages: English
• ISSNs: 0969-8043

Abstract

Abstract: Neutron-induced gamma simulation has multiple applications in various fields, such as radiation therapy, imaging, and nuclear well logging. Among them, Monte Carlo Codes, MCNP6, and GEANT4 are suitable solutions for nuclear detection. Since there are few published comparisons of GEANT4 with MCNP6, especially for the simulation of neutron-induced gamma spectra, therefore, the aim of this paper is to compare the GEANT4 and MCNP6 in the simulation of low-energy (less than 20 MeV) neutron-induced inelastic and capture gamma spectra, the feasibility of which could help to provide an alternative approach for researchers where MCNP6 is not available. Two representative models pertaining to nuclear well logging applications are designed and employed for the purpose of comparison, based on which neutron-induced inelastic and capture gamma spectra are analyzed using different methods associated with each code specifically, such as Time Window, Energy Cutoff, and Physics Tracking. Based on the cross-section library ENDF/B-VII.1, the results obtained from MCNP 6.1 and GEANT4 10.6 match well, which demonstrates the feasibility of using either code in such applications. Highlights: The performance of two Monte Carlo codes are compared regarding neutron-induced gamma simulation. The neutron-induced gamma spectra are obtained by different methods for comparison. Comparison between GEANT4 and MCNP6 simulation shows good agreement.