Neutron-Alpha Reaction Cross Section Determination by Machine Learning Approaches

Amrani N., Yeşilkanat C. M., AKKOYUN S.

Journal of Fusion Energy, cilt.43, sa.2, 2024 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 43 Sayı: 2
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1007/s10894-024-00461-4
  • Dergi Adı: Journal of Fusion Energy
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Chemical Abstracts Core, Communication Abstracts, Compendex, INSPEC, Metadex, Civil Engineering Abstracts
  • Anahtar Kelimeler: (n, α) reaction, Machine-learning, Reaction cross-section
  • Sivas Cumhuriyet Üniversitesi Adresli: Evet

Özet

This study focuses on leveraging powerful machine learning approaches to determine neutron- alpha reaction cross-sections within the 14–15 MeV energy range. The investigation utilizes an experimental dataset comprising measurements of 133 nuclei concerning (n, α) reaction cross- sections. These data are divided into training and validation subsets, following established protocols, with 80% allocated for model training and 20% for testing. Key nucleus characteristics, including neutron number (N), mass number (A), and symmetry representation [(N-Z)²/A], were used as input variables for the machine learning models. SVR and XGBoost methods showed superior performance among the other machine learning methods used in the present study. In addition, a machine learning based online calculation tool was developed to estimate the reaction cross section.