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张婧瑶, 王南萍. MCNP模拟月表关键性元素γ射线与实测结果比较分析[J]. 原子核物理评论, 2014, 31(1): 112-117. DOI: 10.11804/NuclPhysRev.31.01.112
引用本文: 张婧瑶, 王南萍. MCNP模拟月表关键性元素γ射线与实测结果比较分析[J]. 原子核物理评论, 2014, 31(1): 112-117. DOI: 10.11804/NuclPhysRev.31.01.112
ZHANG Jingyao, WANG Nanping. Monte Carlo Simulation and Analysis of γ Rays for the Important Elements of Lunar Surface[J]. Nuclear Physics Review, 2014, 31(1): 112-117. DOI: 10.11804/NuclPhysRev.31.01.112
Citation: ZHANG Jingyao, WANG Nanping. Monte Carlo Simulation and Analysis of γ Rays for the Important Elements of Lunar Surface[J]. Nuclear Physics Review, 2014, 31(1): 112-117. DOI: 10.11804/NuclPhysRev.31.01.112

MCNP模拟月表关键性元素γ射线与实测结果比较分析

Monte Carlo Simulation and Analysis of γ Rays for the Important Elements of Lunar Surface

  • 摘要: 嫦娥一号携带的 射线谱仪传回大量能谱数据,对其分析与解谱是一个比较复杂的过程。针对此问题,提出按照月表 射线来源的物理过程,分为月球表面天然放射元素、中子非弹性散射和中子俘获三部分。用MCNP 程序模拟其在GRS 中的能谱数据,将模拟结果叠加并与实测谱线对比,结果表明,模拟 谱线能帮助辨识出实测谱线中的部分关键元素,例如40K、214Bi 等。It is a more complex data processing problem of the data of -ray spectrum, which were collected by Chang'E-1 from lunar surface. It is presented that MCNP simulation for the spectra, according to three kinds of physical events, such as natural radioactive elements emission, the rays induced by inelastic neutron scattering and neutron capture on the lunar surface in this paper. The simulated results were superimposed and compared with the measured spectrum by Chang'E-1. The results show that 40K and 214Bi can be identi ed
    from the measured data with our MCNP models.

     

    Abstract: It is a more complex data processing problem of the data of -ray spectrum, which were collected by Chang'E-1 from lunar surface. It is presented that MCNP simulation for the spectra, according to three kinds of physical events, such as natural radioactive elements emission, the rays induced by inelastic neutron scattering and neutron capture on the lunar surface in this paper. The simulated results were superimposed and compared with the measured spectrum by Chang'E-1. The results show that 40K and 214Bi can be identi ed
    from the measured data with our MCNP models.

     

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