使用人工神经网络的TENIS中子光谱学。
Neutron spectroscopy with TENIS using an artificial neural network.
作者信息
Bagherzadeh-Atashchi S, Ghal-Eh N, Rahmani F, Izadi-Najafabadi R, Bedenko S V
机构信息
Department of Physics, Faculty of Science, Ferdowsi University of Mashhad, P.O. Box 91775-1436, Mashhad, Iran.
Department of Physics, Faculty of Science, Ferdowsi University of Mashhad, P.O. Box 91775-1436, Mashhad, Iran.
出版信息
Appl Radiat Isot. 2023 Nov;201:111035. doi: 10.1016/j.apradiso.2023.111035. Epub 2023 Sep 15.
In this research, a ThErmal Neutron Imaging System (TENIS) consisting of two perpendicular sets of plastic scintillator arrays for boron neutron capture therapy (BNCT) application has been investigated in a completely different approach for neutron energy spectrum unfolding. TENIS provides a thermal neutron map based on the detection of 2.22 MeV gamma-rays resulting from H(n, γ)D reactions, but in the present study, the 70-pixel thermal neutron images have been used as input data for unfolding the energy spectrum of incident neutrons. Having generated the thermal neutron images for 10 incident mono-energetic neutrons, a 70 × 109 response matrix has been generated using the MCNPX2.6 code for feeding into the artificial neural network tools of MATLAB. The errors of the final results for mono-energetic neutron sources are less than 10% and the root mean square error (RMSE) for the unfolded neutron spectrum of Cf is about 0.01. The agreement of the unfolding results for mono-energetic and Cf neutron sources confirms the performance of the TENIS system as a neutron spectrometer.
在本研究中，一种用于硼中子俘获疗法（BNCT）的热中子成像系统（TENIS）已被采用一种完全不同的方法进行研究，该系统由两组相互垂直的塑料闪烁体阵列组成，用于中子能谱展开。TENIS基于对H(n, γ)D反应产生的2.22 MeV伽马射线的探测提供热中子图，但在本研究中，70像素的热中子图像已被用作展开入射中子能谱的输入数据。在生成了10个单能入射中子的热中子图像后，使用MCNPX2.6代码生成了一个70×109的响应矩阵，用于输入到MATLAB的人工神经网络工具中。单能中子源最终结果的误差小于10%，Cf展开中子谱的均方根误差（RMSE）约为0.01。单能和Cf中子源展开结果的一致性证实了TENIS系统作为中子光谱仪的性能。
Zotero 插件