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In recent years, commercial HTS superconductors have gained an increasinginterest for their use in applications involving large-scale superconductorsystems. These systems are typically made from hundreds to thousands of turnsof conductors. Due to the large number of turns, the simulations of a wholesystem can become prohibitive in terms of computing time and load. Therefore,an efficient strategy which does not compromise the accuracy of calculations isneeded. Recently, a method, based on a multi-scale approach, showed that thecomputational load can be lowered by simulating, in detail, only severalsignificant tapes from the system. The main limitation of this approach is theinaccuracy of the estimation of the background magnetic field. To address thisissue, we consider the following two complementary strategies. The firststrategy consists in the iterative implementation of the multi-scale method.The multi-scale method solves itself a dynamic problem, the iterativeimplementation proposed here is the iterative application of the multi-scalemethod, and a dynamic solution is obtained at each iteration. The secondstrategy is a new interpolation method for current distributions, based on theinverse cumulative density function interpolation technique. With respect toconventional interpolation methods, a more realistic current densitydistribution is then obtained, which allows for a better estimation of thebackground magnetic field, and consequently, a better estimation of thehysteresis losses. In contrast with previous works, here we do not focus onlyon the estimation of the hysteresis losses, but also the estimation ofbackground field and the current density distribution is addressed.

Iterative multi-scale method for accurate estimation of current density and hysteresis losses in large scale HTS systems