Neural network predictions of (n, 2n) reaction cross-sections at 14.6 MeV incident neutron energy
Yazarlar (3)
Prof. Dr. Meryem SEFERİNOĞLU Sinop Üniversitesi, Türkiye
Naima Amrani
Prof. Dr. Tuncay Bayram Sinop Üniversitesi
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Applied Radiation and Isotopes (Q2) | ||
| Makale Dili | – | Basım Tarihi | 01-2023 |
| Cilt / Sayı / Sayfa | 191 / 0 / 110554–0 | DOI | – |
| Makale Linki | https://www.sciencedirect.com/science/article/pii/S0969804322004390 | ||
| UAK Araştırma Alanları |
Dedektör Teknolojisi
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| Özet |
| In this study, we have estimated the (n,2n) reaction cross-section for 14.6 MeV incident neutron energy by using the artificial neural network (ANN) method. We have also predicted the reaction cross-sections whose experimental data are not available in the literature. For the construction of the present ANN, available experimental data in the literature has been borrowed. The ANN estimations have been compared with the available experimental data and the results from a theoretical calculation and the two commonly used computer codes. According to the results that the ANN results are in good agreement with the experimental data than the codes and this shows that the method can be a powerful tool for the estimation of cross-section data for the neutron-induced reactions. Considering the predictions of the ANN of the cross-sections whose experimental data are not available in the literature, it is seen that they … |
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