Factors Affecting the Generation of High-pH Environments Required for Stress Corrosion Cracking (SCC)
Bibliographic record
Abstract
A series of seven experiments have been performed to investigate the effects of various environmental and operational parameters on the generation of high-pH SCC environments under disbonded permeable coating. The parameters investigated include: • the rate of CO2 generation; • direct CO2 production in the disbonded region under the coating; • preferential gas-phase transport of CO2; • the magnitude of the cathodic current density; and • simulated trapped water composition. In general, the total carbonate/bicarbonate concentrations of the simulated trapped water increased with: • increased CO2 flow rate; • direct production of CO2 under the disbonded coating; • increased cathodic current density; and • rapid gas-phase transport of CO2 through holidays above the level of the solution. Ca2+ and Mg2+ cations in groundwaters could buffer the solution in the disbondment at a range of pH 8 to 9 lower than the pH required for the occurrence of high pH SCC. Formation of insoluble carbonate minerals was detected in the simulated disbondment and in the coating with solutions rich in Ca2+ and Mg2+. However, the presence of poorly soluble Ca2+ and Mg2+ cations did not affect the total carbonate/bicarbonate concentration in the inner cell. These observations suggest that environments conducive to high-pH SCC are more likely to occur under the following circumstances: • in regions where the CO2 generation rate is higher, typically wetter and warmer locations; • for coating systems or in regions where there can be microbial activity under the disbonded coating; • in areas where the pipe is not permanently below the water table and where the coating has defects or holidays; and • in areas with a history of higher cathodic current density (which generally results in higher carbonate/bicarbonate concentration) and periodic loss of cathodic polarization.
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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 | 0.000 | 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) | 0.000 | 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".