Iterative multi-scale method for accurate estimation of current density and hysteresis losses in large scale HTS systems
Edgar Berrospe-Juarez, Victor M. R. Zermeno, Frederic Trillaud and, Francesco Grilli

TL;DR
This paper introduces an iterative multi-scale approach combined with a new interpolation method to accurately estimate current density and hysteresis losses in large-scale HTS systems, reducing computational load without sacrificing accuracy.
Contribution
It proposes a novel iterative multi-scale method with an inverse cumulative density function interpolation to improve background field and current density estimations in HTS system simulations.
Findings
Enhanced accuracy in background magnetic field estimation
Improved current density distribution modeling
Reduced computational time for large-scale HTS simulations
Abstract
In recent years, commercial HTS superconductors have gained an increasing interest for their use in applications involving large-scale superconductor systems. These systems are typically made from hundreds to thousands of turns of conductors. Due to the large number of turns, the simulations of a whole system can become prohibitive in terms of computing time and load. Therefore, an efficient strategy which does not compromise the accuracy of calculations is needed. Recently, a method, based on a multi-scale approach, showed that the computational load can be lowered by simulating, in detail, only several significant tapes from the system. The main limitation of this approach is the inaccuracy of the estimation of the background magnetic field. To address this issue, we consider the following two complementary strategies. The first strategy consists in the iterative implementation of the…
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Taxonomy
TopicsPhysics of Superconductivity and Magnetism · Superconducting Materials and Applications · Magnetic Properties and Applications
