The Effect of Girder Profiles on the Probability of Fatigue Damage in Continuous I-Multigirder Steel Bridges
Bibliographic record
Abstract
Fatigue is one of the main sources of mechanical failure in steel bridges. However, a few studies have investigated the relationship between the longitudinal shape of bridge girders and long-term fatigue effects. This paper shows how different girder profiles affect the probability of fatigue damage occurring in continuous I-multigirder steel bridges. The analysis was conducted using realistic traffic scenarios defined through truck data collected in USA and Canada. Monte Carlo simulations with 5000 realizations were performed on several continuous bridge configurations with different span lengths and different girder profiles. The results of the analysis showed that the probability of fatigue damage is affected by profile shape and the smoothness of the transition between the maximum and minimum height of the cross section. In particular, the probability of fatigue damage on continuous I-multigirder steel bridges can be reduced by up to 26% for typical fatigue construction details over a bridge service life of 75 years by modifying the geometry of the girders during the design phase of the bridge.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".