Finite element model for predicting corrosion-induced cracking, spalling and delamination of RC bridge decks
Bibliographic record
Abstract
The corrosion of reinforcing steel in reinforced concrete (RC) bridge decks due to the application of de-icing salts in winter has been recognized as one of the major causes of highway bridge deterioration in North America. Corrosion-induced damage is usually manifested by longitudinal cracking, spalling, and/or delamination of the concrete cover due to the expansion of corrosion products accumulating around the reinforcement. This damage leads to reduction or loss of serviceability, safety, and service life of RC bridge decks. This paper presents finite element analyses of the behaviour of the concrete bridge deck cover subjected to reinforcing steel corrosion. The prediction of the damage caused by corroding reinforcing bars is established by calculating the induced stresses in the surrounding concrete. The numerical model is used to conduct a parametric investigation of several design variables. It is found from the analyses that different failure mechanisms govern depending on the geometry and configuration of the reinforcing bars in the concrete cover of the bridge deck. Finally, the impact of concrete overlays on the governing failure modes of cracking, spalling and/or delamination of the concrete cover is investigated by using the model.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".