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基于反冲质子法建立了一种测量D-T中子与平板型宏观样品作用的次级中子角度谱的实验方法.为保证探测器的能量线性并在较低的中子有效测量下阈(0.5 MeV)情况下获得好的中子-伽马射线甄别性能,采用高、低能段分别测量的方法.采用事件记录法,同时记录了次级中子和伴随伽马射线的脉冲形状甄别和脉冲幅度二维信息,利用基于ROOT数据分析平台编写的离线数据分析程序,完成了伴随伽马射线的挑选和扣除,以及高、低两能段反冲质子谱的拼接,并成功的将神经网络技术应用于中子能谱的解谱,获得了D-T中子与9和18 cm厚平板型聚乙烯材料作用的0.515 MeV的次级中子角度谱实验结果.实验模型的MC模拟由MCNP5完成,数据库采用ENDF-VI,实验结果和MC计算结果在实验不确定度范围内一致.An experimental method of measuring the secondary neutron angular spectrum from polyethylene slab assembly with D-T neutron source based on the proton-recoil method is developed. In order to ensure the energy linearity of the detector and obtain a good neutron-gamma discrimination capability in the case of a low effective neutron threshold (0.5MeV), neutron energy spectrum is measured in two parts: one is in a high energy region and the other in a lower energy region. The pulse shape discrimination (PSD) and the pulse height distribution (PH) two-dimensional information of the secondary neutron and the associated gamma rays are recorded event-by-event simultaneously. The selection and the deduction of the gamma ray events and the joining of the two-segment energy spectra are carried out by using the off-line data analysis programs written in the ROOT data analysis framework. Furthermore, an artificial neural network technique is used to accomplish the unfolding of the neutron spectra successfully. The experimental results of the second neutron angular spectra from 9cm and 18cm thick polythene slab assemblies with D-T neutron source in an energy region of 0.5 MeV to 15 MeV are obtained. The Monte Carlo calculations of the experimental models are accomplished by using the MCNP5 code with ENDF-VI data library. The experimental results are in agree ment with the calculation results within the experimental uncertainties.
[1] Oyama Y, Maekawa H 1986 Nucl. Instr. and Meth. A 245 173
[2] [3] Chen Y, Liu R, Shen J 1998 Fusion Technology 34 1023
[4] [5] [6] Yan J, Li C, Liu R, Jiang L, Lu X X, Wang M 2011 Acta Phys. Sin. 60 0160 (in Chinese) [言 杰、李 澄、刘 荣、蒋 励、鹿心鑫、王 玫 2011 60 0160]
[7] Mark H B, Martin T H, Howard B D 2010 Neural Network ToolboxTM 7 Users Guide. The Mathworks, Inc. www.mathworks.com/help/pdf_doc/nnet/nnet.pdf
[8] [9] Textor R E, Verbinski V V 1968 ORNL-4160
[10] [11] [12] Yan J, Liu R, Li C 2011 Sci. China G 54 465
[13] MCNP-A General Monte Carlo N-Particle Transport Code, Version 5, 2003 X-5 Monte Carlo Team, Los Alamos National Laboritory
[14] -
[1] Oyama Y, Maekawa H 1986 Nucl. Instr. and Meth. A 245 173
[2] [3] Chen Y, Liu R, Shen J 1998 Fusion Technology 34 1023
[4] [5] [6] Yan J, Li C, Liu R, Jiang L, Lu X X, Wang M 2011 Acta Phys. Sin. 60 0160 (in Chinese) [言 杰、李 澄、刘 荣、蒋 励、鹿心鑫、王 玫 2011 60 0160]
[7] Mark H B, Martin T H, Howard B D 2010 Neural Network ToolboxTM 7 Users Guide. The Mathworks, Inc. www.mathworks.com/help/pdf_doc/nnet/nnet.pdf
[8] [9] Textor R E, Verbinski V V 1968 ORNL-4160
[10] [11] [12] Yan J, Liu R, Li C 2011 Sci. China G 54 465
[13] MCNP-A General Monte Carlo N-Particle Transport Code, Version 5, 2003 X-5 Monte Carlo Team, Los Alamos National Laboritory
[14]
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