Estimation of critical current density of bulk superconductor with artificial neural network  

作　　者：Gangling Wu Huadong Yong 

机构地区：[1]Key Laboratory of Mechanics on Disaster and Environment in Western China,The Ministry of Education of China,Lanzhou University,Lanzhou,Gansu 730000,People’s Republic of China [2]Department of Mechanics and Engineering Sciences,College of Civil Engineering and Mechanics,Lanzhou University,Lanzhou,Gansu 730000,People’s Republic of China

出　　处：《Superconductivity》2023年第3期34-45,共12页超导（英文）

基　　金：support from the National Natural Science Foundation of China(Grant Nos.U2241267,12172155 and 11872195).

摘　　要：In the applications of superconducting materials,the critical current density J_(c)(B)is a crucial performance parameter.The conventional method of measuring J_(c)(B)of bulk superconductor is magnetization method.However,there are errors in the estimation of J_(c)(B)in the lower field,and the estimation is not applicable in the region where the magnetic field reverses.In this paper,J_(c)(B)of the bulk superconductor is determined by the hysteresis and magnetostriction loops with artificial neural network(ANN),respectively.Compared with double‐output ANN,the critical current density obtained by single‐output ANN is more accurate.Finally,the prediction results given by the hysteresis and magnetostriction loops are discussed.

关 键 词：Critical current density ANN Kim model Hysteresis loop Magnetostriction loop Bulk superconductor 

分 类 号：O44[理学—电磁学] TP18[理学—物理]