An efficient HTS electromagnetic model combining thin-strip, homogeneous and multi-scale methods by T-A formulation

TL;DR

This paper introduces a fast and accurate electromagnetic modeling approach for high-temperature superconductor (HTS) coils that combines thin-strip, homogeneous, and multi-scale methods using T-A formulation, validated by 2D and 3D simulations.

Contribution

The novel model integrates multiple methods with T-A formulation to improve efficiency and accuracy in simulating complex HTS coil geometries.

Findings

Total loss error less than 1% compared to reference model

Model significantly reduces computation time

Accurate in 3D simulations of HTS coils

Abstract

This study presents an HTS electromagnetic model combining the thin-strip, homogeneous and multi-scale methods using T-A formulation. In particular, we build the thin strips as both the analyzed HTS tapes and the boundaries of the homogeneous bulks where the non-analyzed tapes are merged. Thus, the coil geometry is re-constructed with several bulks, but the bulks boundaries and domains are tackled with different electromagnetic properties, and solved by T and A formulations, respectively. Firstly, we introduce the modeling process and highlight the differences and advantages over the previous models. Then, the accuracy of the proposed model is validated by comparing the results with those from the reference model based on a 2000-turn coil. The distributions of normalized current density, magnetic flux density and hysteresis losses from the two models are highly consistent, and the error of the total loss is less than 1%. Besides, the proposed model is the most time-saving among all the advanced models. Furthermore, the model can be applied in 3D simulations, and the high accuracy and efficiency are validated by simulating a 50-turn racetrack coil. The proposed method provides a feasible approach to simulating coils with many stacked tapes, and we will continue exploring more applications in solving HTS systems with complex geometries.