Designing and assessing wheel/rail profiles for improved rolling contact fatigue and wear performance
Bibliographic record
Abstract
A quick survey of wheel and rail profiles used around the world reveals a huge range of options. Wheels come in cylindrical, conical, and concave variations, while rails range in shape from a very flat 14 in. (350 mm) head radius to a tightly crowned 6 in. (150 mm) head radius. The rationale for implementing one or the other is often institutional inertia—a strong tendency to continue doing what has been done in the past. But the impacts of wheel and rail profiles on the performance of the vehicle/track interaction are large and the decision should not be made lightly. Unfortunately, there are few well-matched “off-the-shelf” solutions from the existing commercially available profiles, such that new rails and wheels often suffer early failures or infant mortality. Through examples and case studies, this paper discusses the significant role that wheel and rail profiles play with respect to performance and safety and makes the case for wheel and rail profiles specifically suited to the needs of each railway. Various techniques for assessing the performance of systems of wheels and rails are reviewed and discussed.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".