Quantitative Interpretation of Half-Cell Potential Measurements in Concrete Structures
Bibliographic record
Abstract
The interpretation of half-cell potential measurements in reinforced concrete structures can be a major challenge for civil engineers. The main reason for this is that half-cell potential mapping provides information to predict the probability of corrosion in concrete, but it does not give clear insight on the rate and the nature of corrosion. Although for general uniform corrosion, half-cell data can provide valuable information about the probability of corrosion. In the case of localized corrosion, the predictions of half-cell measurements can be misleading. The main objective of the present work is to provide practicing engineers a tool that they can use to better interpret the results of half-cell potential measurements. This tool quantitatively relates the potential readings on the surface of the concrete to the rate of probable localized reinforcement corrosion through concrete resistivity, cover thickness, and temperature, allowing the engineers to gain supplementary information from half-cell tests. Experimental comparisons presented in this paper demonstrate the potential benefits of the proposed approach when typical half-cell measurements may not be able to predict the localized corrosion mechanism.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".