The impact of relative wheel-rail hardness on RCF, plastic flow, and rail grinding
Bibliographic record
Abstract
With the ongoing development of rail and wheel metallurgies, steels of greater hardness are now available for consideration at transit and freight railroads alike. Concerns are nearly always raised about the expected impact on the opposing component. That is, if the hardness of the wheels or rail is increased, might that cause problems with the opposing rail or wheels? In a companion paper [1], the authors explore the effect of relative hardness on wear of rails and wheels. An international survey developed for that paper to collect perspectives on how relative hardness affects wear also revealed perspectives related to rolling contact fatigue and plastic flow. Topics such as the Magic Wear Rate and role of rail grinding also arose. This paper explores those topics using fundamental principles of contact mechanics, interfacial properties, stress and strain analysis, and material performance to explain the consequences of harder wheel and/or rail steels on system performance, particularly with respect to RCF and plastic flow.
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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".