A new strain gauge configuration on the rail web to decouple the wheel–rail lateral contact force from wayside measurement
Bibliographic record
Abstract
The simultaneous presence of bending moments and torques produced by the lateral and vertical contact forces between the wheel and the rail generates a complex strain state on the rail surface, which makes it difficult to identify the strain signals produced purely from the lateral contact force. In this study, a new strain gauge configuration is proposed to decouple strain signals of the wheel–rail lateral contact force from wayside measurements by analyzing the bending strains on the rail web using a full Wheatstone bridge. For this purpose, a finite element modeling of the wheel–rail contact is performed to analyze the bending strains on the rail web and to optimize two instrumented sections for eight electric resistance strain gauges. Laboratory testing is also used to examine the installation scheme of the strain gauges at the two optimal instrumented sections. A good agreement is observed between the experimental data and the simulation results. Strain signals are evenly distributed for about 10 cm in the middle region between the two optimal instrumented sections and only account for the lateral contact force.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".