Could laser-based profile measurements be used in wheel/rail contact and vehicle dynamics simulations?
Bibliographic record
Abstract
Contact-based profilometers have been the de facto standard in obtaining wheel and rail profiles for the purposes of vehicle-track and wheel-rail interaction studies. Still, they cannot collect profiles in large quantities. This paper explores the potential of laser-based profilometers for wheel and rail profile measurements in vehicle-track dynamic simulations. Comparisons between contact and laser-based profilometers were performed using sample rail profiles measured in the lab. Through contact simulations, contact preprocessing and multi-body dynamics simulations (MBD), differences in contact pressures, forces, and Y/Q were analyzed. The importance of data processing and profile smoothing is also discussed. Axle sum Y/Q showed the smallest differences between the two sets of profiles, with more than 80% of the MBD simulations having less than 10% difference. While far from perfect, the ability of wayside and vehicle-mounted laser profilometers can enable analyses to be performed at a much larger scale. The authors hope this work will lead to an open-minded approach to continue evaluating laser-based profiles in simulations.
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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".