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本工作探索了基于Triple GEM探测器对快中子能谱的测量, 利用MCNPX和Geant4软件分别模拟了两种在Triple GEM阴极耦合由多层聚乙烯组成的堆栈式中子转化质子的转化模型, 研究对象包含了5种单能中子源和Am-Be连续谱中子源. 模拟得到了探测系统对160条单能中子的响应函数和上述源的反冲质子谱分布, 使用GRAVEL和MLEM算法对模拟得到的6种快中子源的反冲质子谱进行了解谱研究, 并把解谱结果与标准输入谱进行了对比, 结果显示与标准输入谱均符合较好, 解谱的相对不确定度为10%—15%; 并研究了气体探测器能量分辨率对解谱精度影响的关系, 结果表明微结构气体探测器的能量分辨率好于30%时, 快中子的解谱精度就可以满足实际应用需求. 本研究在以前的实验基础上提出了一种新的转化结构, 并通过模拟结果得出微结构气体探测器可以应用于快中子探测, 并能够利用得到的反冲质子谱结合合适的反演算法实现入射中子源的能谱重建. 本文积累的建模和解谱算法为将来微结构气体探测器组成的快中子探测系统应用于未知快中子源探测, 能谱重建, 实现源项识别提供了新的办法.This paper focuses on the feasibility of fast neutron energy spectrum measurement. The MCNPX and Geant4 are used to simulate two conversion models of stacking neutrons to protons in the triple GEM cathode coupled with multilayer polyethylene, with five kinds of single-energy neutron sources and Am-Be continuous neutron sources taken as research objects. The response function to 160 single energy neutrons and the recoil proton spectrum distribution of the above sources of the detection system are obtained by simulation. Using GRAVEL algorithm and MLEM algorithm and through simulation, the recoil proton spectra of six kinds of fast neutron sources are obtained, and they are further analyzed. The spectrum outcome is compared with the standard input spectrum, showing that they are in good agreement with each other. The relative uncertainty of the unfolding spectrum is around 10%–15%. In this part the relation of gas detector with the precision of unfolding spectrum is also discussed. The result shows that when the energy resolution of micro-pattern gas detection is better than 30%, the accuracy of fast neutron spectrum can meet the needs of practical applications. Furthermore, a new transformation model is proposed based on previous experiments and proves the feasibility of applying micro-pattern gas detector to fast neutron detection of simulation. Moreover, spectrum reconstruction can be achieved by using the obtained recoil proton spectrum combined with a suitable inversion algorithm. The modeling and spectrum analysis of this study can provide a different method of applying the fast neutron detection system composed of micro-pattern gas detectors to the detection of unknown fast neutron sources and also to the source recognition through spectrum reconstruction.








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