Evaluating the potential of a rolling deflection measurement system to estimate track modulus
Bibliographic record
Abstract
Over the past two decades, a rolling deflection measurement system aiming to continuously measure the track modulus has been under development at the University of Nebraska – Lincoln under the sponsorship of the Federal Railroad Administration. This system measures the relative vertical distance (referred to as Y rel ) between the rail surface and the rail/wheel contact plane at a distance of 1.22 m from the nearest wheel to the sensor system. The aim of this study was to investigate the potential of using the Y rel measurement as an indicator of the track modulus for various rail foundation conditions. To meet this objective, a detailed finite element model capable of simulating moving loads and track modulus variation was developed. One of the unique contributions of this study is that it presents a comprehensive study of the Y rel –track modulus relationship by defining more realistic support conditions using discrete spring supports and by simulating the stochastic nature of the track modulus along a 160-m track length. The numerical model was employed to examine the accuracy of estimating the track modulus using the Y rel measurements when foundation stiffness is variable. Furthermore, the correlation between the statistical properties of the track modulus and Y rel was studied over different track segment lengths.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".