Nuclear Science and Techniques

《核技术》(英文版) ISSN 1001-8042 CN 31-1559/TL     2019 Impact factor 1.556

Nuclear Science and Techniques ›› 2017, Vol. 28 ›› Issue (6): 80 doi: 10.1007/s41365-017-0236-5

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Feasibility study on determining the conventional true value of gamma-ray air kerma in a minitype reference radiation

Yi-Xin Liu1,2, Biao Wei1, Yang Xu1,2, Meng He2, Ren-Hong Zhuo2, De-Zhi Wen2, Da-Jie Ding2,Ben-Jiang Mao2   

  1. 1 Key Laboratory of Optoelectronics Technology and System, Ministry of Education, Chongqing University, Chongqing 400044, China
    2 Institute of Nuclear Physics and Chemistry, China Academy of Engineering Physics, Mianyang 621999, China
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Yi-Xin Liu, Biao Wei, Yang Xu, Meng He, Ren-Hong Zhuo, De-Zhi Wen, Da-Jie Ding, Ben-Jiang Mao. Feasibility study on determining the conventional true value of gamma-ray air kerma in a minitype reference radiation.Nuclear Science and Techniques, 2017, 28(6): 80     doi: 10.1007/s41365-017-0236-5
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Abstract:

A minitype reference radiation (MRR) with dimensions of only 1 m 9 1 m 9 1 m has been developed for the in situ calibration of photon dosimeters. The present
work conducts a feasibility study on determining the conventional true value of gamma-ray air kerma at the point of test in the MRR. Owing to its smaller imensions, the scattered gamma-rays in the MRR are expected to induce a non-negligible interference with the radiation field compared with conditions in the standard reference radiation stipulated by ISO4037-1 or GB/T12162.1. A gamma-ray spectrometer was employed to obtain the spectra of scattered gamma-rays within the MRR, and the feature components of the spectra were extracted by principal component analysis to characterize the interference of a dosimeter probe in the radiation field. A prediction model of the CAK at the point of test was built by least squares support vector machine based on the feature component data obtained from nine sample dosimeters under five different dose rates. The mean prediction error of the CAK prediction model was within ±4.5%, and the maximum prediction error was about ±10%.

Key words: Air kerma, Reference radiation, Calibration, Principal component analysis, Support vector machine