We estimated the critical current of the second generation (2G) high-temperature superconducting (HTS) conductor using neural network fitting methods. The critical current of 2G HTS conductors depends on magnetic field strength and angle as well as on temperature, I_c(T, B, θ). Moreover, the critical current values vary for 2G HTS conductors from different manufacturers. In this study, we addressed three challenging issues in critical current assessment by neural network fitting methods, namely 90° asymmetry, a wide range of temperature-field-angle dependence, and different manufacturer conductor differences. Prediction models for three commercial HTS conductors were trained and evaluated by convergence, accuracy, and robustness. The linear regression correlation coefficient R was approximately equal to 1 for the three models. The critical current estimation obtained from the proposed method was compared with the critical current estimation from the interpolation method at different fixed temperatures using a multi-width no-insulation magnet. The model computation speed was also discussed. The proposed model needed only 2.7 s to compute 10 million data sets. Therefore, the convergence, accuracy, reliability, and speed of the proposed method prove that it can be used in a wide range of industrial applications and academic fields.

Research on Hyper Tube, a Korean high-speed HTS Maglev train, has reached the verification stage for actual operation, and electromagnetic dynamic characteristics analysis of the train is required accordingly. Depending on the winding type of the propulsion armature, the HTS magnet experiences the harmonic that causes AC loss. Beside the static thermal losses by thermal conduction, current leads et al., the AC loss should be take account for the thermal battery design depending on operation conditions. This study describes the AC loss analysis of the HTS magnet induced by the harmonic using the homogeneous T-A formulation widely used in recent. In consideration of acceleration and cruise conditions, the effect of the AC loss by harmonics on the capacity of the solid nitrogen thermal battery was discussed.

In promoting novel products with superconducting magnets to transportation and science industries, the most important factor is reliability. Recently, it was reported that a no-insulation (NI) superconducting magnet could be damaged with quenches caused by a thermal runaway, significant temperature deviation, extremely high characteristic resistance, etc. To resolve this issue, numerical analysis of high-temperature superconducting (HTS) racetrack coils with NI winding technology should be conducted. The authors proposed a homogenization method to analyze operating characteristics of the NI HTS coils by simplifying the finite element analysis (FEA) model and decreasing the solution time. In order to estimate their thermal stabilities, the proposed FEA simulation is one of the efficient methods for solving the electrical and thermal factors simultaneously. In this paper, the thermal analysis of the leakage currents of NI HTS racetrack coils is presented using a three-dimensional (3D) turn-distributed equivalent circuit FEA model. The charging and discharging delay phenomena were modeled by considering the contact resistances by turns. With the equivalent circuit model of the NI HTS magnets, the 3D racetrack coils were designed by considering a single turn and stacked turns, including metal insulation layers. Their material properties according to temperature variation were applied in the transient analysis. The critical currents by turns were estimated by considering the magnetic field, its angle, and temperature with a given current simultaneously. The simulation results were compared with a fabricated NI HTS magnet and are presented in this paper.

This study analyzes the quench behavior of No-insulation (NI) REBCO pancake. An quench analysis simulation model considering the complex critical current density distribution was developed and validated experimentally. The developed model includes an equivalent circuit model, a thermal model, a magnetic model, and a magnet critical current estimation model. The simulation model is based on a co-simulation using MATLAB and COMSOL, considering the balance of accuracy and computation time. The lumped parameter of the NI magnet was used to solve the governing equations of the equivalent circuit module and thermal module in MATLAB. To accurately calculate the non-uniform electromagnetic field distribution over the coil, a magnetic finite element method was used in COMSOL. A neural network was used to predict the temperature-field-angle dependent magnet critical current. Considering the numerical convergence at different over-current phases, adaptive simulation was used to reduce the total simulation time. The quench behavior was analyzed using the proposed model, and the results were verified experimentally. The simulation results showed that when the azimuthal current is greater than the magnet critical current, it will gradually saturate and approach the magnet critical current, and then decrease at a similar speed. The rate of decrease is equal to the rate of decrease of the magnet critical current. Through the analyses, the corresponding sudden-discharging behavior was simulated and analyzed. The proposed model can be used to perform the post-quench and sudden discharging analyses of pancake coil and has promising applications in multi-pancake post-quench studies.

The transient loss during the ramping process is an important evaluation metric for commercial large-scale magnet systems to meet refrigeration requirements; this loss is considerably influenced by contact resistivity. Due to the intrinsic bypass current of the no-insulation pancake, two parts of the transient loss were considered in this study: turn-to-turn loss generated by the radial direction current and the magnetization loss produced by the azimuthal direction current. A turn-distributed model was used to calculate the non-uniform current distribution, where the pancake coil is radially subdivided into each turn. The radial current was used to calculate the turn-to-turn loss. The turn azimuthal current was applied to the boundary condition of the T-A formula to calculate the magnetization loss in a cylindrical coordinate system. The superconductor index value model was used for the simulations, where the critical current density is the conductor engineering current density estimated by a neural network fitting model. The contact resistance dependent turn-to-turn loss and magnetization loss were presented. This approach is expected to be used in magnet-level NMR/ MRI systems.

Due to the higher thermal stability and the ability to be operated at liquid-helium-free temperature, the HTS cable show great promise for conduction-cooled tokamak magnet applications. However, the YBCO tapes embedded within the slot produce an axial strain, leading to a degradation in critical current. Meantime, the critical current is also strongly influenced by the field and its incidence angle on the tape. Understanding the impact of the coupled electromagnetic-mechanical effect on critical current degradation and magnetization loss is paramount. In this study, the coupling mechanical-electromagnetic critical current estimation model was first built based on the longitudinal strain model and tape its own in-field property. Subsequently, we analyze the DC critical current and the dynamic magnetization loss based on the 2D T-A model. Through the integration of the non-uniform magnetic field and longitudinal strain, the distribution of the critical current density could be evaluated. This enabled the complex current distribution and magnetization loss to be monitored effectively. The results of this study will be employed in the further optimization of CICC conductor in the future.