The Bayesian neural network(BNN)method is proposed to predict the isotopic cross-sections in proton induced spallation reactions.Learning from more than 4000 data sets of isotopic cross-sections from 19 experimental m...The Bayesian neural network(BNN)method is proposed to predict the isotopic cross-sections in proton induced spallation reactions.Learning from more than 4000 data sets of isotopic cross-sections from 19 experimental measurements and 5 theoretical predictions with the SPACS parametrization,in which the mass of the spallation system ranges from 36 to 238,and the incident energy from 200 MeV/u to 1500 MeV/u,it is demonstrated that the BNN method can provide good predictions of the residue fragment cross-sections in spallation reactions.展开更多
From the empirical phenomena of fragment distributions in nuclear spallation reactions,semiempirical formulas named SPAGINS were constructed to predict fragment cross-sections in high-energyγ-induced nuclear spallati...From the empirical phenomena of fragment distributions in nuclear spallation reactions,semiempirical formulas named SPAGINS were constructed to predict fragment cross-sections in high-energyγ-induced nuclear spallation reactions(PNSR).In constructing the SPAGINS formulas,theoretical models,including the TALYS toolkit,SPACS,and Rudstam formulas,were employed to study the general phenomenon of fragment distributions in PNSR with incident energies ranging from 100 to 1000 MeV.Considering the primary characteristics of PNSR,the SPAGINS formulas modify the EPAX and SPACS formulas and efficiently reproduce the measured data.The SPAGINS formulas provide a new and effective tool for predicting fragment production in PNSR.展开更多
基金Supported by the National Natural Science Foundation of China(11975091,U1732135,11875070)Natural Science Foundation of Henan Province(162300410179)supported by the US Department of Energy(DE-FG02-93ER40773)
文摘The Bayesian neural network(BNN)method is proposed to predict the isotopic cross-sections in proton induced spallation reactions.Learning from more than 4000 data sets of isotopic cross-sections from 19 experimental measurements and 5 theoretical predictions with the SPACS parametrization,in which the mass of the spallation system ranges from 36 to 238,and the incident energy from 200 MeV/u to 1500 MeV/u,it is demonstrated that the BNN method can provide good predictions of the residue fragment cross-sections in spallation reactions.
基金supported by the Program for Innovative Research Team(in Science and Technology)in University of Henan Province(No.21IRTSTHN011),China。
文摘From the empirical phenomena of fragment distributions in nuclear spallation reactions,semiempirical formulas named SPAGINS were constructed to predict fragment cross-sections in high-energyγ-induced nuclear spallation reactions(PNSR).In constructing the SPAGINS formulas,theoretical models,including the TALYS toolkit,SPACS,and Rudstam formulas,were employed to study the general phenomenon of fragment distributions in PNSR with incident energies ranging from 100 to 1000 MeV.Considering the primary characteristics of PNSR,the SPAGINS formulas modify the EPAX and SPACS formulas and efficiently reproduce the measured data.The SPAGINS formulas provide a new and effective tool for predicting fragment production in PNSR.
