Validating Spring Weight Restriction Limits with Mechanistic–Empirical Failure Prediction Models
Bibliographic record
Abstract
This study developed local mechanistic–empirical failure models to predict fatigue and rutting damage on spring-weight-restricted (SWR) roads in Manitoba, Canada. The local models were used to assess the SWR load limits and to validate the current SWR deflection levels that regulate commercial vehicle weights during the spring period. The local model predictions were compared with the damage models of the Asphalt Institute (AI) and the Mechanistic–Empirical Design Guide (MEPDG). The results indicated that the predicted equivalent single-axle load repetitions to fatigue failure from the local model were higher than those of the MEPDG and the AI models by an average of 37% and 20%, respectively. On the basis of the local model equivalent single-axle load predictions, the current SWR deflection limits used in Manitoba appear to be a reasonable method for regulating B-Train operations during the spring period.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".