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JMCT Monte Carlo analysis of BEAVRS benchmark: hot zero power results

Li Gang Deng Li Zhang Bao-Yin Li Rui Shi Dun-Fu Shangguan Dan-Hua Hu Ze-Hua Fu Yuan-Guang Ma Yan

JMCT Monte Carlo analysis of BEAVRS benchmark: hot zero power results

Li Gang, Deng Li, Zhang Bao-Yin, Li Rui, Shi Dun-Fu, Shangguan Dan-Hua, Hu Ze-Hua, Fu Yuan-Guang, Ma Yan
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  • Received Date:  15 August 2015
  • Accepted Date:  14 December 2015
  • Published Online:  05 March 2016

JMCT Monte Carlo analysis of BEAVRS benchmark: hot zero power results

    Corresponding author: Deng Li,
  • 1. Institute of Applied Physics and Computational Mathematics, Beijing 100094, China;
  • 2. CAEP Software Center for High Performance Numerical Simulation, Beijing 100088, China
Fund Project:  Project supported by the Sub-item of Special Projects of the National Energy Bureau, China (Grant No. 2015ZX06002008), the Nuclear Power Development Project of the Science, Technology and Industry for National Defense of China (Grant No. [2012]1523), the National High Technology Research and Development Program of China (Grant No. 2012AA01A303), and the Fund of China Academy of Engineering Physics (Grant No. 2014B0202029).

Abstract: J Monte Carlo transport code (JMCT), a new three-dimentional (3 D) Monte Carlo transport code, is introduced in this paper. The code is developed on the basis of 3 D geometry infrastructure JCOGIN and composed of multilayer modules. JMCT is capable of simulating the collision of particles with multi-group energy or providing energy data libraries. Two forms of parallelism supported in JMCT are domain decomposition and domain replication. The code has very good expansibility. JMCT Monte Carlo results have been compared with hot zero power (HZP) measurements of BEAVRS benchmark model from the MIT Computational Reactor Physics Group. Included in the comparisons are the eigenvalues, control rod bank worths, isothermal temperature coefficients, axially integrated full core detector measurements, axial detector profiles, etc. The eigenvalues for the HZP condition with different control rods positions and boron concentrations are calculated and the error is less than 0.2% compared with the theoretical error 1.000. The results of JMCT for isothermal temperature coefficients are also listed together with MC21 results and measured data. Each calculation for the eigenvalue is run by 1000 cycles in total, discarding 600 cycles, tracking 4 million neutrons each cycle. It takes 5.3-5.7 hours to run on 200 CPU cores. The JMCT results of axially integrated radial detector relative power distribution (RPD) and axial normalized detector signal are compared with the measured data. Power depressions from grid spacers are clearly seen in the JMCT results and accord with the measured data. The JMCT results of axially integrated assembly RPD power distribution are in good agreement with MC21 results, the maximum difference being 3.173% for 193 assemblies. So is the result of pin power RPD relative power at the axial elevation of peak power; the minimum relative power RPD 0.278 of JMCT is comparable to 0.283 of MC21, and the max relative power RPD 2.422 of JMCT is comparable to 2.452 of MC21. The calculation for RPD is run with 3000 inactive cycles and 5000 active cycles, tracking 4 million particles each cycle. It takes about 4.8 days to run on 200 CPU cores. Shannon entropy is used to demonstrate that the fission source distribution is converged after 3000 inactive cycles. With the development of computers and parallel computing, the Monte Carlo method can be used in reactor design instead of benchmarking other calculated results.

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