Projection of the Carbonation Depths and its Probability of Corrosion Initiation for the Uncracked and Cracked Concrete
Bibliographic record
Abstract
This research aims to investigate the impact of different relative humidity on the carbonation depth by using various mathematical models for the carbonation-induced corrosion at different Representative Concentration Pathways (RCPs) of CO2 concentrations. Additionally, the carbonation depth values were conducted for the uncracked and cracked concrete at various RCPs in the future, considering the impact of the relative humidity. Moreover, the probability of corrosion initiation was investigated using the Monte Carlo Simulation method at different percentages of either high or low calcium fly ash ranging from (5% FA to 30% FA) used as Supplementary Cementing Material (SCM) in the concrete mix for RC bridge decks at different concrete covers. Results show that the carbonation depths for the cracked concrete with a crack width of 0.20 mm are higher than that of the uncracked concrete by 126% at various percentages of either high or low calcium fly ash used as SCM in concrete mixes in year 100. The carbonation depths for concrete mix, including 30% of low calcium fly ash, increased by 78.6% compared to a concrete mix with zero percent of the low calcium fly ash, for the unc and cracked concrete with a crack width of 0.2 mm, in year 100. Finally, the probabilities of corrosion initiation values for uncracked concrete are almost constant (approximately equal to zero values) versus various percentages of either high or low calcium fly ash utilized as SCM in the concrete mix for RC bridge decks having a concrete cover of 50 mm in year 100.
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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 | 0.001 | 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) | 0.000 | 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".