Artificial Neural Network for Unfolding Accelerator-based Neutron Spectrum by Means of Multiple-foil Activation Method

Tadahiro Kin, Y. Sanzen, M. Kamida, K. Aoki, N. Araki, Yukinobu Watanabe

研究成果: 著書/レポートタイプへの貢献会議での発言

抄録

In medical radioisotope (RI) production by accelerator neutron, double-differential thick-target neutron yield (DDTTNY) is necessary to be measured to estimate production amount and its radioactive and isotopic purity. We adopted the multiple-foil activation method for the measurement. The DDTTNY should be derived by an unfolding technique from measured numbers of produced atoms via the activation reactions. We have developed an unfolding code using artificial neural network (ANN) which requires no initial guess spectrum and no human-inducible convergence condition which are required for conventional unfolding methods. To demonstrate the ability to derive DDTTNY by the ANN unfolding code, we input numbers of produced atoms obtained by a multiple-foil activation experiment conducted at Kyushu University Tandem Laboratory. The resultant DDTTNY is compared with that by GRAVEL code, which is one of the conventional codes. Since there is no large discrepancy, we found that the ANN unfolding code has same ability to GRAVEL code even no initial guess spectrum was used.

元の言語英語
ホスト出版物のタイトル2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings
出版者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781538622827
DOI
出版物ステータス出版済み - 11 12 2018
イベント2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Atlanta, 米国
継続期間: 10 21 201710 28 2017

出版物シリーズ

名前2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings

その他

その他2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017
米国
Atlanta
期間10/21/1710/28/17

Fingerprint

neutron spectra
Neutrons
Metal foil
Particle accelerators
foils
accelerators
Chemical activation
activation
Neural networks
neutrons
Atoms
Radioisotopes
atoms
purity
estimates
Experiments

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Radiology Nuclear Medicine and imaging
  • Nuclear and High Energy Physics

これを引用

Kin, T., Sanzen, Y., Kamida, M., Aoki, K., Araki, N., & Watanabe, Y. (2018). Artificial Neural Network for Unfolding Accelerator-based Neutron Spectrum by Means of Multiple-foil Activation Method. : 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings [8532892] (2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NSSMIC.2017.8532892

Artificial Neural Network for Unfolding Accelerator-based Neutron Spectrum by Means of Multiple-foil Activation Method. / Kin, Tadahiro; Sanzen, Y.; Kamida, M.; Aoki, K.; Araki, N.; Watanabe, Yukinobu.

2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. 8532892 (2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings).

研究成果: 著書/レポートタイプへの貢献会議での発言

Kin, T, Sanzen, Y, Kamida, M, Aoki, K, Araki, N & Watanabe, Y 2018, Artificial Neural Network for Unfolding Accelerator-based Neutron Spectrum by Means of Multiple-foil Activation Method. : 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings., 8532892, 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings, Institute of Electrical and Electronics Engineers Inc., 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017, Atlanta, 米国, 10/21/17. https://doi.org/10.1109/NSSMIC.2017.8532892
Kin T, Sanzen Y, Kamida M, Aoki K, Araki N, Watanabe Y. Artificial Neural Network for Unfolding Accelerator-based Neutron Spectrum by Means of Multiple-foil Activation Method. : 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. 8532892. (2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings). https://doi.org/10.1109/NSSMIC.2017.8532892
Kin, Tadahiro ; Sanzen, Y. ; Kamida, M. ; Aoki, K. ; Araki, N. ; Watanabe, Yukinobu. / Artificial Neural Network for Unfolding Accelerator-based Neutron Spectrum by Means of Multiple-foil Activation Method. 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. (2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings).
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