Passenger Track Curve Design Criteria: Comfort Criteria, Equivalent Comfort Criteria, and Application
Bibliographic record
Abstract
It is generally recognized by FRA, AREMA, Amtrak, OSHA, and many other applicable authorities that the maximum acceptable rate of radial acceleration for passengers comfort is 0.1g, where ‘g’ is 9.81 m/s/s [1]. Jerk is limited to 0.03g/s [1]. Roll is limited to 1 deg/sec. In this paper all values computed with the aforesaid standard values are referred to as the maximum desirable values as these may be exceeded if needed. Currently there is no procedure in the literature to compute the maximum desirable values. From these comfort criteria the formulae for superelevation run off, rate of change of curvature, radius, and spiral angle etc. are derived. Applications of these formulae and further potential applications thereof are presented. This study is intended for conventional non-tilting train. The equilibrium (Eq), actual (Ea), and unbalance superelevation (Eu) run-off are calculated to be 45 mm/sec, 26 mm/sec and 19 mm/sec respectively. From the run-off rates, the maximum desirable actual and unbalance superlevation comes out to be 87 mm and 63 mm respectively. The desirable ratio between unbalance and actual super-elevation comes to be 0.72. This helps in proportioning equilibrium superelevation to ensure comfort. Equations of spiral length are derived by proportioning 3.33 sec’s ride with the maximum desirable values of superelevation and these equations are found to be exactly the same as those derived another way in the paper no. JRC 2010-36050.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".