Factors Affecting Corrosion of Buried Cast Iron Pipes
Why this work is in the frame
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Bibliographic record
Abstract
Although corrosion of metal in soils has been intensively investigated in the past, a review of the published literature shows that limited research has been undertaken to understand how soil properties affect the corrosion behavior of cast iron pipes, owing to the scarcity of the reported information on buried metal corrosion in its backfill soil condition. In this paper, a methodology is proposed to statistically analyze the effects of soil properties on corrosion behavior, and a comprehensive and long-term historical corrosion database of buried cast iron pipes is thoroughly interpreted. The corrosion is characterized by two time-independent parameters in each sample, that is, the proportionality (k) and exponent (n) factors of the power law model. It is found that the exponent factor n of power law model is closely associated with the level of soil aeration. It is also found that grouping corrosion data based on soil aeration produces stronger correlations between soil properties and corrosion rates compared with that when taking all soil samples as a whole. The authors conclude that an appropriate classification of soils can benefit the identification of key factors influencing corrosion of buried cast iron pipes at different exposure times. This research provides further knowledge for asset managers and engineers to accurately predict the failure of corrosion-affected cast iron pipes.
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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 | 0.000 |
| 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) | 0.001 | 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 it