Highway Network Bridge Fatigue Damage Potential of Special Truck Configurations
Bibliographic record
Abstract
A study of the fatigue damage potential of special truck configurations was conducted to facilitate informed decisions by state transportation agencies in considering various truck size and weight and permit policies as well as to provide relative damage information that will be useful in ongoing network damage evaluations. The primary objective was to evaluate 78 existing common and FHWA-proposed truck configurations for relative fatigue damage potential. To accomplish this objective, an analytical fatigue evaluation tool was developed to determine the relative fatigue damage induced in highway network bridges by simulation of a highway fleet mix database crossing actual bridges modeled analytically. Additional objectives were to evaluate the influence of impact values and endurance limits used for a fatigue analysis. The semicontinuum analysis method, the Palmgren-Miner hypothesis, and the rain-flow cycle counting algorithm are incorporated. A 39-bridge database statistically selected as representative of bridges in the United States allowed a network level fatigue analysis of several hundred fatigue-prone details. Seventy-eight special truck configurations were studied, 25 of which were developed by FHWA as part of the comprehensive truck size and weight study. The remaining 53 vehicles were taken from the Turner proposal, Michigan, Pennsylvania, Canada, military, AASHTO, and other sources. It was found that fatigue damage potential is primarily a function of axle weight, spacing, and vehicle length instead of gross vehicle weight.
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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 | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".