Service Life Prediction for Weathering Steel Highway Structures
Why this work is in the frame
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Bibliographic record
Abstract
Composite concrete and steel slab-on-girder systems are used for the superstructures of highway structures, including underpasses and overpasses, throughout North America. In certain jurisdictions, it has been reported that large numbers of these structures show evidence of serious corrosion in the webs and the bottom flanges of the girders. The cause of the corrosion is believed to be a combination of moisture from melting snow, road salt, and sulphur dioxide. In a number of observed cases, the most heavily corroded regions of these bridges appear to coincide with the splash zones that are present due to the passage of large trucks. In order to facilitate the probabilistic structural analysis of these deteriorating structures, an analysis program has been developed, which enables the calculation of their diminishing structural reliability with the passage of time. Specifically, the effects of corrosion on the shear, moment, and bearing resistance of the girders are evaluated in accordance with the limit states outlined in the Canadian Highway Bridge Design Code [1]. Statistical distributions are then applied to the load- and resistance-related input parameters, including those associated with various corrosion models. A Monte Carlo simulation is then performed to generate curves of bridge reliability versus time for various assumed corrosion rates. The focus of this study is lifespan prediction of weathering steel highway structures. Weathering steel is a type of high-strength, low-alloy steel which has been found to behave favourably with respect to atmospheric corrosion resistance. The steel contains small amounts of nickel, chromium, and copper; it is available as Type A or Type AT, as designated in CAN/CSA G40.21-M92 [2]. Under repeated cycles of wetting and drying, weathering steel forms a thin, adherent oxide patina, which afterwards protects it from further penetration of oxygen and moisture that leads to corrosion. This patina is supposed to form in 18 to 36 months [2].
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it