Aerodynamic load spectrum and fatigue behaviour of high‐speed train's equipment cabin
Bibliographic record
Abstract
Abstract In present study, the aerodynamic fatigue behaviour of train equipment cabin was investigated. Pressure sensors were arranged at train passing side. Eight‐grade load spectrum was constructed by means of rain‐flow counting, and fatigue damage was calculated with Miner's rule and Carten‐Dolan rule, both for the matrix metals and welds. For welds, defect detection was considered via visual inspection with nondestructive test (VI‐NDT), pure nondestructive test (P‐NDT), and without nondestructive test (W‐NDT). The result confirms that welds play an unfavourable role rather than matrix metals. Weld damage in W‐NDT exceeds its limit (1.0) to designed mileage. Then, damage influence was studied under tunnel passing, train passing, and running direction. Running direction as the head car contributes 82% to approximately 86% and 70% to approximately 77% of the total damage for matrix metal and welds, respectively. Train passing gives more damage to matrix metals than welds. Tunnel passing contributes 25% to approximately 26% for both matrix metals and welds.
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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 | 0.000 |
| 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".