Probability-based modeling of chloride-induced corrosion in concrete structures including parameters correlation
Bibliographic record
Abstract
This paper presents a practical approach for probabilistic modeling of chloride-induced corrosion of steel reinforcement in concrete structures based on the first-order reliability method (FORM). The method enables to take into account the uncertainties in the parameters that govern the physical models of chloride ingress into concrete and corrosion of carbon steel including concrete diffusivity, concrete cover depth, surface chloride concentration and threshold chloride level for onset of corrosion. The governing parameters are modelled as random variables with different levels of correlation and the probability of corrosion is determined and compared to the predictions obtained by more rigorous approaches, such as second-order reliability method (SORM) and Monte Carlo simulation (MCS). The approach is applied to predict the level of corrosion in the top layer of reinforcing carbon steel of a highway bridge deck that was exposed to chlorides from deicing salts. The results illustrate the accuracy and efficiency of FORM when compared to SORM and MCS. The paper also shows that the impact of correlation between the chloride diffusivity and chloride threshold level on the corrosion probability is negligible and can be ignored.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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 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".