Current redistribution during inhomogeneous quench of 2G HTS tapes
Bibliographic record
Abstract
Abstract Inhomogeneous temperature elevations, also called hot spots, occurring in second generation high-temperature superconductor (2G HTS) tapes may lead to their destruction. A better understanding of inhomogeneous quenches would contribute to develop strategies to better protect superconducting devices based on 2G HTS tapes against hot spots. To do so, we investigated the current redistribution around a dissipative zone in a 2G HTS tape with a combination of experiments and numerical simulations based on the finite element method (FEM). Firstly, the inhomogeneous heat generation in a commercial 2G HTS bare tape (without copper cladding) was observed through the visualization of bubble generation. Secondly, the current redistribution around a dissipative zone in commercial 2G HTS bare tapes from two different manufacturers was investigated using voltage taps on both sides of the tape. The measured voltages showed that the current redistribution around the dissipative area in the top stabilizer layer of the tape is different from that in the bottom stabilizer layer. Using a 3D electro-thermal FEM model, we reproduced these behaviors, assuming a HTS tape architecture with an inhomogeneous local critical current density. Finally, using the same FEM model, we explored the impact of a lack of silver on one lateral side of a 2G HTS tape. Our results indicate that such a lack of silver does not critically affect the quench dynamics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".