2021
DOI: 10.1016/j.anucene.2020.107978
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NECP-MCX: A hybrid Monte-Carlo-Deterministic particle-transport code for the simulation of deep-penetration problems

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Cited by 56 publications
(7 citation statements)
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“…NECP-MCX is developed based on a hybrid Monte Carlo deterministic method, where the deterministic method is utilized to generate consistent mesh-based weightwindow and source-biasing parameters for the Monte Carlo method to reduce variance. The code has been verified against with various benchmarks (He et al, 2021;Li et al, 2021).…”
Section: Results Of Critical Benchmarksmentioning
confidence: 99%
See 1 more Smart Citation
“…NECP-MCX is developed based on a hybrid Monte Carlo deterministic method, where the deterministic method is utilized to generate consistent mesh-based weightwindow and source-biasing parameters for the Monte Carlo method to reduce variance. The code has been verified against with various benchmarks (He et al, 2021;Li et al, 2021).…”
Section: Results Of Critical Benchmarksmentioning
confidence: 99%
“…In the present work, we will investigate the effects of the aforementioned treatments for thermal neutron scattering data on the neutronics calculations. The analysis is carried out with the Monte Caro code NECP-MCX (He et al, 2021).…”
Section: Introductionmentioning
confidence: 99%
“…III lists the building and running environment of OpenMC, in order to redo or evaluate the results. For industrial operations, it suggests to use programs such as JMCT [13], RMC [14], MCX [15], cosRMC [16] and etc. C. On-the-fly Doppler Broadening…”
Section: B Reference Codementioning
confidence: 99%
“…Neutronic analysis are simulated by the NECP‐MCX, 22 which is a hybrid Monte‐Carlo‐Deterministic particle‐transport code developed by Nuclear Engineering Computational Physics (NECP) laboratory of Xi'an Jiaotong University. The neutronic analysis is based on the geometry shown in Figure 1 and the reactor core design parameters listed in Table 2.…”
Section: Nuster‐100 Core Performance Analysesmentioning
confidence: 99%