Computation of self-field hysteresis losses in conductors with helicoidal structure using a 2D finite element method
Bibliographic record
Abstract
It is well known that twisting current-carrying conductors helps to reduce their coupling losses. However, the impact of twisting on self-field hysteresis losses has not been as extensively investigated as that on the reduction of coupling losses. This is mostly because the reduction of coupling losses has been an important issue to tackle in the past, and it is not possible to consider twisting within the classical two-dimensional (2D) approaches for the computation of self-field hysteresis losses. Recently, numerical codes considering the effect of twisting in continuous symmetries have appeared. For general three-dimensional (3D) simulations, one issue is that no robust, widely accepted and easy to obtain model for expressing the relationship between the current density and the electric field is available. On the other hand, we can consider that in these helicoidal structures currents flow only along the helicoidal trajectories. This approach allows one to use the scalar power-law for superconductor resistivity and makes the eddy current approach to a solution of a hysteresis loss problem feasible. In this paper we use the finite element method to solve the eddy current model in helicoidal structures in 2D domains utilizing the helicoidal symmetry. The developed tool uses the full 3D geometry but allows discretization which takes advantage of the helicoidal symmetry to reduce the computational domain to a 2D one. We utilize in this tool the non-linear power law for modelling the resistivity in the superconducting regions and study how the self-field losses are influenced by the twisting of a 10-filament wire. Additionally, in the case of high aspect ratio tapes, we compare the results computed with the new tool and a one-dimensional program based on the integral equation method and developed for simulating single layer power cables made of ReBCO coated conductors. Finally, we discuss modelling issues and present open questions related to helicoidal structures and AC-loss computations in three dimensions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".