Comparison of Different INC Physical Models of MCNPX to Compute Spallation Neutronics of LBE Target

NUBA Conference Series -1: Nuclear Physics and Astrophysics

物理学;天文学

Feghhi, Seyed Amir Hossein^1 ; Gholamzadeh, Zohreh^2 ; Tenreiro, Claudio^3 ; Alipoor, Zahra^4

Department of Radiation Application, Shahid Beheshti University, G.C, Tehran, Iran^1

Reactor Research School, Nuclear Science and Technology Research Institute, Tehran, Iran^2

Department of Physics, Talca University, Talca, Chile^3

Department of Physics, Zanjan University, Iran^4

关键词: Computational data;    Energy depositions;    External sources;    Particle transport codes;    Simulation data;    Spallation process;    Spallation targets;    Sub-critical reactors;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/590/1/012043/pdf
DOI  :  10.1088/1742-6596/590/1/012043

学科分类：天文学(综合)

来源: IOP

【 摘 要 】

Spallation particles can utilize in different fields such as neutron scattering studies, external source for burning spent fuel as well as running subcritical reactors. Different computational particle transport codes are widely used to model spallation process into the heavy targets. Among these codes, MCNPX 2.6.0 comprises various intra nuclear cascade models for spallation calculations. Impact of different intra nuclear cascade models on calculation of neutronic parameters of LBE target has been evaluated in this work. Escaped neutron yield, energy deposition and residual nuclei production in the spallation target has been calculated using the physical models. A comparison between the computational and experimental has been carried out to validate the computational data. The simulation data showed there is a good conformity between the obtained data from Bertini/Drenser and Isabel/Drenser. The data achieved by Bertini/Abla and Isabel/Abla models are close to each other for the studied parameters as well. Among the studied models, CEM showed more discrepancies with experimental and other computational data. According to the obtained data, INCL4/Drenser, INCL4/Abla and Isabel/Drenser models can meet more agreements with experimental data.