Numerical investigation on thermal performance of rotating target for CANS
Bibliographic record
Abstract
Compact accelerator-driven neutron sources (CANSs) demonstrate significant potential for applications in both scientific and industrial fields. A critical challenge for further expanding CANS’s applications is to improve the neutron yield, which requires a highly efficient thermal dissipation ability for neutron targets to bear the high power of incident beam. By employing the rotating target, the bearable thermal load of neutron target can be significantly enhanced. Therefore, a quantitative evaluation of the thermal dissipation capacity of rotating target is in need. With the finite volume method, we conduct a systematic numerical investigation on the thermal performance of the rotating target. Particularly, we study the effects of the number of target piece, the rotation speed, the flow rate of coolant, and the incident beam power with different beam spot distributions on the temperature of the neutron-producing layer of the target. These results allow us to quantify the thermal performance of rotating target while meeting stringent engineering criteria. Our results provide a robust foundation for the application of rotating targets in CANS.
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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 | 0.000 |
| 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".