Effects of climate change and environmental aggressiveness on onset of corrosion in concrete highway bridge decks
Bibliographic record
Abstract
Reinforced concrete bridge decks in the Canadian Highway Bridge Design Code (CSA S6-19) are classified as non-replaceable components with a required 75-year design service life. In cold regions, their durability is primarily governed by chloride-induced corrosion from the frequent use of deicing salts, making this the principal durability concern. This study presents a probabilistic assessment of chloride-induced corrosion initiation in reinforced concrete highway bridge decks, accounting for corrosive environments and temperature increases due to climate change, which can accelerate corrosion by increasing chloride diffusion and lowering the chloride threshold. The time to corrosion onset is estimated using Monte Carlo simulations to model key parameters across various concrete and steel combinations. The results confirm that elevated temperatures accelerate chloride diffusion and reduce chloride thresholds, collectively shortening the time to corrosion initiation across all environmental corrosivity levels. Notably, the relative impact of climate change is greater in milder corrosive environments, as baseline diffusion rates in highly aggressive conditions are already elevated. Moreover, the use of high-performance concrete and corrosion-resistant steel is shown to be an effective adaptation strategy in severe corrosive environments, delaying corrosion initiation and extending deck service life.
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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) | 0.000 | 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) | 0.001 | 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".