Simulation Research on Explosives Detection System Based on D-D Sealed Neutron Generator

Yadong Gao, De-Dong He, Ke Gong, Guang Shi, Si-Yuan Chen, Chen Zhu, Shiwei Jing
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Abstract

A prompt gamma neutron activation analysis (PGNAA) system based on a deuterium-deuterium (D-D) sealed neutron generator was designed using the MOCA code for explosive detection. The system is mainly composed of four parts: D-D sealed neutron generator, moderator, shielding, and Lutetium Yttrium OxyorthoSilicate (LYSO) scintillation detectors. Polyethylene (PE) was selected as the moderator and the optimal thickness was 7cm. Lead, PE, and boron-containing polyethylene were used as shielding materials. In the optimized model, the LYSO detector is used to measure eighteen materials, such as wood, melamine, glucose, and nylon, and so on. Firstly, the nitrogen characteristic peak of 10.8 MeV was analyzed to determine whether the material contained nitrogen. Then, the ratio of characteristic peak counts of C/O and O/N were calculated to distinguish explosives from nitrogen containing materials. Finally, dinitrobenzene, nitroglycerin, TNT, and ammonium nitrate can be separated from nitrogenous substances by a discriminant algorithm. The final device can be used to detect the chemical composition of the threat substances, and the maximum dose rate of the system meets the limits of international protection standards.
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基于D-D密封中子发生器的爆炸物探测系统仿真研究
采用MOCA代码,设计了基于氘-氘(D-D)密封中子发生器的快速伽马中子活化分析(PGNAA)系统。该系统主要由四部分组成:D-D密封中子发生器、慢化剂、屏蔽和LYSO闪烁探测器。选择聚乙烯(PE)作为慢化剂,最佳厚度为7cm。采用铅、聚乙烯和含硼聚乙烯作为屏蔽材料。在优化的模型中,LYSO检测仪用于测量木材、三聚氰胺、葡萄糖、尼龙等18种材料。首先通过分析10.8 MeV的氮特征峰来判断材料是否含氮。然后,计算出C/O和O/N特征峰数的比值,以区分炸药和含氮物质。最后通过判别算法将二硝基苯、硝化甘油、TNT和硝酸铵从含氮物质中分离出来。最终装置可用于检测威胁物质的化学成分,系统的最大剂量率符合国际防护标准的限值。
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