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The back-streaming neutron beam line (Back-n) was built in the beginning of 2018, which is part of the China Spallation Neutron Source (CSNS). The Back-n is the first white neutron beam line in China, and its main application is for nuclear data measurement. For most of neutron-induced nuclear reaction measurements based on white neutron facilities, the beam of gamma rays accompanied with neutron beam is one of the most important experimental backgrounds. The back streaming neutron beam is transported directly from the spallation target to the experimental station without any moderator or shielding, the flux of the in-beam gamma rays in the experimental station is much larger than those of these facilities with neutron moderator and shielding. Therefore, it is necessary to consider the influence of in-beam gamma rays on the experimental results. Studies of the in-beam gamma rays are carried out at the back-n. Monte-Carlo simulation is employed to obtain the energy distribution and the time structure of the in-beam gamma rays. According to the simulation results, when the neutron flight time is longer than 1.0 μs the energy distribution of the in-beam gamma rays does not vary with flight time. Therefore, the time structure of these gamma rays can be measured without the correction of the detection efficiency. In this work, the time structure of the in-beam gamma rays in the low neutron energy region is measured by both direct and indirect methods. In the direct measurement, a 6Li loaded ZnS(Ag) scintillator is located on the neutron beam line and the time of flight method is used to determine the time structure of neutrons and gamma rays. The gamma rays are separated from neutrons with pulse-shape discrimination. The black filter method is used to verify the particle discrimination results. In the indirect measurement, the C6D6 scintillation detectors are used to measure the gamma rays scattered off a Pb sample on the way of the neutron beam. The time structure of the in-beam gamma rays is derived from that of the scattered gamma rays. The experimental results are in good agreement with the simulations with the time-of-flight between 12 μs and 2.0 ms. Besides, according to the simulation results, the intensity of the in-beam gamma rays is 1.21 × 106 s–1·cm–2 in the center of the experimental station 2 of Back-n, which is 76.5 m away from the spallation target of CSNS.
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Keywords:
- back-streaming white neutron source /
- in-beam γ-rays measurement /
- time of flight method /
- Monte-Carlo simulation
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图 1 CSNS Back-n布局图
Figure 1. Layout of the CSNS Back-n.
图 2 Geant 4构建的散裂靶几何模型
Figure 2. Geometric model of the spallation target in Geant 4 code.
图 3 束内伽马射线的模拟结果 (a) 能谱; (b) 时间结构
Figure 3. The simulation results of the in-beam gamma rays: (a) The energy spectrum; (b) the time structure.
图 4 束内伽马射线的能谱 (a) γ-flash和连续伽马能谱; (b)连续伽马在不同时间区间的能谱
Figure 4. The energy spectra of the in-beam gamma rays: (a) The energy spectra of γ-flash and the consecutive gamma rays; (b) the energy spectra of the consecutive gamma rays at different time.
图 5 (a)直接测量实验布局; (b) EJ-420闪烁体结构
Figure 5. (a) The experimental setup of the direct measurement; (b) the structure of the EJ-420 scintillator.
图 6 EJ-420的伽马波形和中子波形
Figure 6. The waveforms of EJ-420: Gamma ray’s waveform and neutron’s waveform.
图 7 (a) 中子伽马波形甄别结果; (b) EJ-420的飞行时间谱
Figure 7. (a) The pulse shape discrimination result of neutron and gamma rays; (b) time-of-flight spectrum of the EJ-420.
图 8 (a) 间接测量实验布局; (b) Geant 4中的几何模型
Figure 8. (a) The experimental setup of the indirect measurement; (b) the geometric model in Geant 4 code.
图 9 实验测量与Geant 4模拟得到的TOF谱和束内伽马TOF谱
Figure 9. The TOF spectrum of indirect measurement (black solid line) and the Geant 4 simulated TOF spectrum (red solid line) and the in-beam γ-rays (blue dashed line).
图 10 束内伽马射线的TOF谱对比
Figure 10. The comparison of the TOF spectra of the in-beam gamma rays.
表 1 Geant 4中的物理模型
Table 1. Physical models in the Geant 4 code.
粒子类型 能量区间/MeV 物理模型 质子 < 1600 G4HadronModel G4CascadeInterface 中子 < 20.0 G4NeutronHPModel (ENDF/B-VII.1) > 20.0 G4HadronModel 伽马 > 0 G4RayleighScattering G4PhotoElectricEffect G4ComptonScattering G4GammaConversion 电子 > 0 G4eMultipleScattering G4eIonisation G4eBremsstrahlung 
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[1] Chen H, Wang X L 2016 Nat. Mater. 15 689
Google Scholar
[2] Tang J Y, Fu S N, Jing H T, Tang H Q, Wei J, Xia H H 2010 Chin. Phys. C 34 121
Google Scholar
[3] Jing H T, Tang J Y, Tang H Q, Zhang C, Zhou Z Y, Zhong Q P, Ruan X C 2010 Nucl. Instrum. Methods A 621 91
Google Scholar
[4] An Q, Bai H Y, Bao J, et al. 2017 J. Instrum 12 P07022
[5] Chen Y H, Luan G Y, Bao J, et al. 2019 Eur. Phys. J. A 55 115
Google Scholar
[6] 鲍杰, 陈永浩, 张显鹏竺 2019 物理学报 68 080101
Google Scholar
Bao J, Chen Y H, Zhang X P, et al. 2019 Acta Phys. Sin 68 080101
Google Scholar
[7] Li Q, Luan G Y, Bao J, et al. 2019 Nucl. Instrum. Methods A 946 162497
Google Scholar
[8] Liu X Y, Yang Y W, Liu R, et al. 2019 Nucl. Sci. Tech 30 139
Google Scholar
[9] Yang Y, Wen Z, Han Z, et al. 2019 Nucl. Instrum. Methods A 940 486
Google Scholar
[10] Bai H, Fan R, Jiang H, et al. 2020 Chin. Phys. C 44 014003
Google Scholar
[11] Jiang H, Jiang W, Bai H, et al. 2019 Chin. Phys. C 43 124002
Google Scholar
[12] Briesmeister J F E 2000 MCNP-A General Monte Carlo N-Particle Transport Code (Version 4C) LA-13709-M
[13] Allison J, Amako K, Apostolakis J, et al. 2016 Nucl. Instrum. Methods A 836 186
Google Scholar
[14] Bohlen T T, Cerutti F, Chin M P W, Fasso A, Ferrari A, Ortega P G, Mairani A, Sala P R, Smirnov G, Vlachoudis V 2014 Nucl. Data Sheets 120 211
Google Scholar
[15] Zhang L Y, Jing H T, Tang J Y, et al. 2018 Appl. Radiat. Isot 132 212
Google Scholar
[16] Chadwick M B, Herman M, Oblozinsky P, et al. 2011 Nucl. Data Sheets 112 2887
Google Scholar
[17] EJ-420 Data Sheet, https://eljentechnology.com/images/products/data_sheets/EJ-420.pdf/[2020-04-15]
[18] Wang Q, Cao P, Qi X, et al. 2018 Rev. Sci. Instrum 89 013511
Google Scholar
[19] Syme D B 1982 Nucl. Instrum. Methods 198 357
Google Scholar
[20] Ren J, Ruan X C, Bao J, et al. 2019 Radiation Detection Technology and Methods 3 52
Google Scholar
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