Nuclear data generation & implementation for analog Monte Carlo simulation

被引:0
|
作者
Ramirez, Camilo Cordero [1 ]
Jouanne, Cedric [1 ]
机构
[1] Univ Paris Saclay, CEA, Serv Etudes Reacteurs & Mathemat Appl, F-91191 Gif Sur Yvette, France
关键词
D O I
10.1051/epjconf/202328403011
中图分类号
TL [原子能技术]; O571 [原子核物理学];
学科分类号
0827 ; 082701 ;
摘要
Nuclear data is in constant evolution as more experimental data is gathered, computational capabilities increase, and evaluators verify its validity by means of stochastic and deterministic simulations. The focus here is on the analog Monte Carlo simulation of nuclear reactions that produce more than two particles in the outgoing channel, which needs specific considerations to ensure the correlations between the particles and thus the conservation of energy and of translational and angular momenta. It is possible to adapt nuclear data and its exploitation to implement realistic reactions from the phenomenological point of view (as opposed to the historical need of variance reduction techniques), which increases computation time but allows the expansion of the transport codes capabilities. Simulation anomalies were found concerning the kinematical calculations of photon energies emitted from neutron-induced inelastic scattering (n,n'gamma), as well as concerning the photon multiplicity of Gd-155(n,gamma) due to the presence of a rotational band in Gd-156. Recommendations are given for potential solutions for both anomalies.
引用
收藏
页数:4
相关论文
共 50 条
  • [21] Generation of correlated pseudorandom variables in Monte Carlo simulation
    Wen De-Zhi
    Zhuo Ren-Hong
    Ding Da-Jie
    Zheng Hui
    Cheng Jing
    Li Zheng-Hong
    ACTA PHYSICA SINICA, 2012, 61 (22)
  • [22] MateSim: Monte Carlo simulation for the generation of mating tables
    Carvajal-Rodriguez, A.
    BIOSYSTEMS, 2018, 171 : 26 - 30
  • [23] Monte Carlo Simulation of Neutron Generation by Lightning Leaders
    Xu, Wei
    Celestin, Sebastien
    Pasko, Victor P.
    2013 US NATIONAL COMMITTEE OF URSI NATIONAL RADIO SCIENCE MEETING (USNC-URSI NRSM), 2013,
  • [24] Simulation of Rossi-α method with analog Monte-Carlo method
    Xie, Q.-L. (xieql@mail.ihep.ac.cn), 2012, Atomic Energy Press (46):
  • [25] Iterative Bayesian Monte Carlo for nuclear data evaluation
    Erwin Alhassan
    Dimitri Rochman
    Alexander Vasiliev
    Mathieu Hursin
    Arjan J.Koning
    Hakim Ferroukhi
    Nuclear Science and Techniques, 2022, 33 (04) : 103 - 133
  • [26] Bayesian Monte Carlo method for nuclear data evaluation
    A. J. Koning
    The European Physical Journal A, 2015, 51
  • [27] Iterative Bayesian Monte Carlo for nuclear data evaluation
    Erwin Alhassan
    Dimitri Rochman
    Alexander Vasiliev
    Mathieu Hursin
    Arjan J. Koning
    Hakim Ferroukhi
    Nuclear Science and Techniques, 2022, 33
  • [28] Bayesian Monte Carlo method for nuclear data evaluation
    Koning, A. J.
    EUROPEAN PHYSICAL JOURNAL A, 2015, 51 (12): : 1 - 16
  • [29] Iterative Bayesian Monte Carlo for nuclear data evaluation
    Alhassan, Erwin
    Rochman, Dimitri
    Vasiliev, Alexander
    Hursin, Mathieu
    Koning, Arjan J.
    Ferroukhi, Hakim
    NUCLEAR SCIENCE AND TECHNIQUES, 2022, 33 (04)
  • [30] Bayesian Monte Carlo Method for Nuclear Data Evaluation
    Honing, A. J.
    NUCLEAR DATA SHEETS, 2015, 123 : 207 - 213