Neutron spectroscopy with TENIS using an artificial neural network
| Parent link: | Applied Radiation and Isotopes.— .— Amsterdam: Elsevier Science Publishing Company Inc. Vol. 201.— 2023.— Article number 111035, 8 p. |
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| Autres auteurs: | , , , , |
| Résumé: | Title screen 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 1H(nth, γ)2D 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 109 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 252Cf is about 0.01. The agreement of the unfolding results for mono-energetic and 252Cf neutron sources confirms the performance of the TENIS system as a neutron spectrometer Текстовый файл AM_Agreement |
| Langue: | anglais |
| Publié: |
2023
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| Sujets: | |
| Accès en ligne: | https://doi.org/10.1016/j.apradiso.2023.111035 |
| Format: | Électronique Chapitre de livre |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=680248 |