Analyzing dynamic resistance in high-temperature superconducting tapes by combining finite element method with machine learning

Shu-liang Xiao, Zhi-gang Zeng, Di-fan Zhou, Zhuo-yue Jia, Zhi-chao Yan, Qi-zhan Li, Shi-heng Song, Chuan-bing Cai

Journal of Central South University ›› 2024, Vol. 31 ›› Issue (3) : 737-746. DOI: 10.1007/s11771-024-5614-7

Analyzing dynamic resistance in high-temperature superconducting tapes by combining finite element method with machine learning

Author information +
History +

Abstract

When an external alternating field reaches a threshold value, high-temperature superconductors (HTS) that are carrying direct current can exhibit dynamic resistance phenomenon. This phenomenon, often observed in tape applications, can be effectively studied using finite element methods (FEM). However, due to differences in production processes, HTS tapes have varying parameters, including magnetic-dependent critical current. This can pose a significant challenge when comparing dynamic resistance differences among HTS tapes. Due to the capability of machine learning to conveniently handle the nonlinear characteristics of superconductors and adapt to multivariate function fitting, this paper employs machine learning for fitting the critical current characteristics of tapes and applies it to calculate dynamic resistance in the FEM model. By employing machine learning to handle the critical current characteristics of various tapes, the FEM model showcases both feasibility and accuracy in the results.

Keywords

dynamic resistance / finite element method / critical current / machine learning

Cite this article

Download citation ▾
Shu-liang Xiao, Zhi-gang Zeng, Di-fan Zhou, Zhuo-yue Jia, Zhi-chao Yan, Qi-zhan Li, Shi-heng Song, Chuan-bing Cai. Analyzing dynamic resistance in high-temperature superconducting tapes by combining finite element method with machine learning. Journal of Central South University, 2024, 31(3): 737‒746 https://doi.org/10.1007/s11771-024-5614-7

References

[[1]]
Brandt E H, Mikitik G P. Why an AC magnetic field shifts the irreversibility line in type-II superconductors. Physical Review Letters, 2002, 89(2): 027002, J]
CrossRef Google scholar
[[2]]
Geng J-z, Painter T, Long P, et al.. A kilo-ampere level HTS flux pump. Superconductor Science and Technology, 2019, 32(7): 074004, J]
CrossRef Google scholar
[[3]]
Geng J, Matsuda K, Shen B, et al.. HTS persistent current switch controlled by AC magnetic field. IEEE Transactions on Applied Superconductivity, 2016, 26(3): 6603304, J]
CrossRef Google scholar
[[4]]
Jiang Z-n, Toyomoto R, Amemiya N, et al.. Dynamic resistance of a high-T c coated conductor wire in a perpendicular magnetic field at 77 K. Superconductor Science and Technology, 2017, 30(3): 03LT01, J]
CrossRef Google scholar
[[5]]
Jiang Z-n, Toyomoto R, Amemiya N, et al.. Dynamic resistance measurements in a GdBCO-coated conductor. IEEE Transactions on Applied Superconductivity, 2017, 27(4): 5900205, J]
CrossRef Google scholar
[[6]]
Jiang Z-n, Zhou W, Li Q, et al.. The dynamic resistance of YBCO coated conductor wire: Effect of DC current magnitude and applied field orientation. Superconductor Science and Technology, 2018, 31(3): 035002, J]
CrossRef Google scholar
[[7]]
Liu Y-c, Jiang Z-n, Sidorov G, et al.. Dynamic resistance measurement in a YBCO wire under perpendicular magnetic field at various operating temperatures. Journal of Applied Physics, 2019, 126(24): 243904, J]
CrossRef Google scholar
[[8]]
Jiang Z-n, Amemiya N, Kakimoto K, et al.. The dependence of AC loss characteristics on the space in stacked YBCO conductors. Superconductor Science and Technology, 2008, 21(1): 015020, J]
CrossRef Google scholar
[[9]]
Brooks J M, Ainslie M D, Jiang Z-n, et al.. The transient voltage response of ReBCO coated conductors exhibiting dynamic resistance. Superconductor Science and Technology, 2020, 33(3): 035007, J]
CrossRef Google scholar
[[10]]
Oomen M P, Rieger J, Leghissa M, et al.. Dynamic resistance in a slab-like superconductor with J c(B) dependence. Superconductor Science and Technology, 1999, 12(6): 382-387, J]
CrossRef Google scholar
[[11]]
Zhang H-y, Hao C-t, Xin Y, et al.. Demarcation currents and corner field for dynamic resistance of HTS-coated conductors. IEEE Transactions on Applied Superconductivity, 2020, 30(8): 6601305, J]
CrossRef Google scholar
[[12]]
Liu R-j, Yang W-j, Song D-b, et al.. Effect of dynamic resistance on AC loss in stacked superconducting tapes. IEEE Transactions on Applied Superconductivity, 2020, 30(4): 5900305 [J]
[[13]]
Zhang H-y, Machura P, Kails K, et al.. Dynamic loss and magnetization loss of HTS coated conductors, stacks, and coils for high-speed synchronous machines. Superconductor Science and Technology, 2020, 33(8): 084008, J]
CrossRef Google scholar
[[14]]
Ainslie M D, Bumby C W, Jiang Z-n, et al.. Numerical modelling of dynamic resistance in high-temperature superconducting coated-conductor wires. Superconductor Science and Technology, 2018, 31(7): 074003, J]
CrossRef Google scholar
[[15]]
Li Q, Yao M, Jiang Z-n, et al.. Numerical modeling of dynamic loss in HTS-coated conductors under perpendicular magnetic fields. IEEE Transactions on Applied Superconductivity, 2018, 28(2): 6600106, J]
CrossRef Google scholar
[[16]]
Ma J, Geng J-z, Chan W-k, et al.. A temperature-dependent multilayer model for direct current carrying HTS coated-conductors under perpendicular AC magnetic fields. Superconductor Science and Technology, 2020, 33(4): 045007, J]
CrossRef Google scholar
[[17]]
Li C, Xing Y-y, Zhao B-t, et al.. Dynamic resistance of series-connected HTS stacks considering electromagnetic and thermal coupling. IEEE Transactions on Applied Superconductivity, 2022, 32(4): 8200305, J]
CrossRef Google scholar
[[18]]
Shen B-y, Chen X-y, Fu L, et al.. Numerical modelling of the dynamic voltage in HTS materials under the action of DC transport currents and different oscillating magnetic fields. Materials, 2022, 15(3): 795, J]
CrossRef Google scholar
[[19]]
Shen B-y, Zhang M-s, Bian X-m, et al.. Optimisation of energy efficiency: Dynamic voltages in superconducting tapes to energise superconducting power/energy applications. Electronics, 2022, 11(7): 1098, J]
CrossRef Google scholar
[[20]]
Zhang H-y, Shen B-y, Chen X-y, et al.. Dynamic resistance and dynamic loss in a ReBCO superconductor. Superconductor Science and Technology, 2022, 35(11): 113001, J]
CrossRef Google scholar
[[21]]
Grilli F, Sirois F, Zermeño V M R, et al.. Self-consistent modeling of the I c of HTS devices: How accurate do models really need to be?. IEEE Transactions on Applied Superconductivity, 2014, 24(6): 8000508, J]
CrossRef Google scholar
[[22]]
Hilton D K, Gavrilin A V, Trociewitz U P. Practical fit functions for transport critical current versus field magnitude and angle data from (RE)BCO coated conductors at fixed low temperatures and in high magnetic fields. Superconductor Science and Technology, 2015, 28(7): 074002, J]
CrossRef Google scholar
[[23]]
Liu Q-y, Kim S. Temperature-field-angle dependent critical current estimation of commercial second generation high temperature superconducting conductor using double hidden layer Bayesian regularized neural network. Superconductor Science and Technology, 2022, 35(3): 035001, J]
CrossRef Google scholar
[[24]]
Zhu L-f, Wang Y-s, Meng Z-q, et al.. Critical current and n-value prediction of second-generation high temperature superconducting conductors considering the temperature-field dependence based on the back propagation neural network with encoder. Superconductor Science and Technology, 2022, 35(10): 104002, J]
CrossRef Google scholar
[[25]]
Savoldi R L, Bonifetto R, Carli S, et al.. Modeling of pulsed heat load in a cryogenic SHe loop using artificial neural networks. Cryogenics, 2013, 57: 173-180, J]
CrossRef Google scholar
[[26]]
Leclerc J, Makong H L, Lorin C, et al.. Artificial neural networks for AC losses prediction in superconducting round filaments. Superconductor Science and Technology, 2016, 29(6): 065008, J]
CrossRef Google scholar
[[27]]
Yazdani-asrami M, Taghipour-gorjikolaie M, Song W-j, et al.. Prediction of nonsinusoidal AC loss of superconducting tapes using artificial intelligence-based models. IEEE Access, 2020, 8: 207287-207297, J]
CrossRef Google scholar
[[28]]
Wen Z-z, Zhang H-y, Mueller M. Sensitivity analysis and machine learning modelling for the output characteristics of rotary HTS flux pumps. Superconductor Science and Technology, 2021, 34(12): 125019, J]
CrossRef Google scholar
[[29]]
Hong Z, Campbell A M, Coombs T A. Numerical solution of critical state in superconductivity by finite element software. Superconductor Science and Technology, 2006, 19(12): 1246-1252, J]
CrossRef Google scholar
[[30]]
Vanderbemden P, Hong Z, Coombs T A, et al.. Behavior of bulk high-temperature superconductors of finite thickness subjected to crossed magnetic fields: Experiment and model. Physical Review B, 2007, 75(17): 174515, J]
CrossRef Google scholar
[[31]]
Li S, Chen D-x, Fang Jin. Transport ac losses of a second-generation HTS tape with a ferromagnetic substrate and conducting stabilizer. Superconductor Science and Technology, 2015, 28(12): 125011, J]
CrossRef Google scholar
[[32]]
Li S, Chen D-xing. Scaling law for voltage - current curve of a superconductor tape with a power-law dependence of electric field on a magnetic-field-dependent sheet current density. Physica C: Superconductivity and Its Applications, 2017, 538: 32-39, J]
CrossRef Google scholar
[[33]]
STUART W, NICK S, ANDRES P. Critical current characterisation of HTS superconducting wire [EB/OL]. [2021-02-24]. https://figshare.com/search?q=:keyword:%20%222G%20HTS%22.

Accesses

Citations

Detail

Sections
Recommended

/