The influence of binder type, cracking and cover on corrosion rates of steel in chloride-contaminated concrete
Bibliographic record
Abstract
Cracking of reinforced concrete can result in substantial reduction in service life owing to rapid initiation of steel corrosion. Supplementary cementitious materials (SCMs) can alter not only the pore solution chemistry but also the environment surrounding the steel and lead to significant reductions in corrosion rate. The impact of binder type on corrosion rate was assessed using seven concrete mixtures comprising ordinary Portland cement (PC) and blends of PC with ground granulated blast-furnace slag, fly ash, condensed silica fume and a ternary blend. Corrosion rates were measured in prismatic specimens with crack widths of 0·2 mm or 0·7 mm. For 20 mm cover, all the SCMs resulted in at least a 50% reduction in corrosion rate compared with the PC control. Increase in crack width from 0·2 mm to 0·7 mm increased corrosion rate in all cases, but had far less impact than that of the SCMs. Increase in cover depth from 20 mm to 40 mm had substantial benefits for PC specimens, reducing corrosion rates by more than half; the same benefits were not observed in specimens using SCMs. This was ascribed to corrosion rates of SCM concretes being controlled primarily by resistivity of the system, while rates in PC specimens were controlled mainly by oxygen availability and thus cover depth.
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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 | 0.000 |
| 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 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".