Influence of Climate Change on the Probability of Chloride-Induced Corrosion Initiation for RC Bridge Decks Made of Geopolymer Concrete
Bibliographic record
Abstract
Climate change poses a significant threat to the durability of reinforced concrete (RC) bridges, which are particularly vulnerable to chloride-induced corrosion of steel reinforcements. The main problem for the current research is the increase in the projected maximum temperature values, especially for the high emission scenario in the future because of climate change, applied to the upper part of the RC bridge deck made of geopolymer concrete (GPC) composed of 50% fly ash and 50% slag. This will reduce the corrosion initiation time and the safety and durability of the RC bridge deck structure. Despite extensive research on chloride-induced corrosion, there is a scientific gap in understanding how future climate variations will influence the rate of corrosion in RC bridges. Specifically, comprehensive studies assessing the effect of maximum temperature on the probability of the corrosion initiation process in RC bridge decks made of GPC exposed to chloride environments are lacking. This study used the Monte Carlo simulation method to assess the probability of corrosion initiation (PCI) under various future climate scenarios for Toronto City, Canada. This research examines the impact of the maximum temperature and relative humidity on the diffusion coefficient of chloride ions in concrete. It assesses the PCI for different concrete cover thicknesses in RC decks made of geopolymer concrete composed of 50% fly ash and 50% slag over specified periods, dealing with the sensitivity analysis for this parameter among different parameters defined in the performance function. The results indicate a substantial increase in the PCI for a 40 mm concrete cover compared with a 50 mm cover in various years. Furthermore, maximum temperatures ranging from 40 °C to 45 °C significantly increase the PCI compared with temperatures between 25 °C and 35 °C for a 50 mm concrete cover. Finally, polynomial functions have been deduced to investigate the reliability index and PCI as a function of various coefficients of variations for mean concrete covers made of GPC at various maximum temperature values in different years. These findings provide important information for the design and maintenance of RC structures, ensuring their longevity in the face of climate change.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".