Thermal feedback in coaxial superconducting radio frequency cavities
Bibliographic record
Abstract
The surface resistance of superconducting radio frequency (SRF) cavities depends on the strength of the applied rf field. This field dependence is caused by a combination of intrinsic losses and the extrinsic thermal feedback (TFB) effect. To test theories of intrinsic field dependence, the extrinsic part must be compensated for when analyzing experimental data from SRF cavity tests. Performing this compensation requires knowing thermal parameters that describe heat flow in the cavity walls. The relevant thermal parameters have been measured in the case of superfluid helium, below 2.177 K, but no detailed measurements have yet been reported for cooling of niobium surfaces in normal fluid helium baths. Because of this, the impact of TFB on the field dependence at temperatures near 4.2 K is unknown. In the present study, we report measurements of normal fluid helium boiling from niobium surfaces and its dependence on the orientation of the boiling surface and bath temperature. These measurements are used to create a finite-element model of heat transfer in cavities from TRIUMF’s coaxial test program. This tool is then used to compensate for TFB when analyzing a range of datasets from this program. Results are presented showing that TFB has a weak impact for the temperatures of 2.0 and 4.2 K, where SRF cavities are usually operated, but it is an important effect at intermediate temperatures. Published by the American Physical Society 2024
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".