Environmental aspects of near-neutral pH stress corrosion cracking of pipeline steel
Bibliographic record
Abstract
The severity of four different soil environments toward the development of near-neutral pH stress corrosion cracking (SCC) of pipeline steel was evaluated using slow strain-rate testing (SSRT). These soils were collected from pipeline sites where near-neutral pH SCC has been observed. It was demonstrated in this investigation that SSRT can differentiate the severity of various soil electrolytes to near-neutral pH SCC. For different soils, the relative susceptibility was found to be determined by the pH values of the soil electrolytes in equilibrium with a given CO2/N2 gas mixture. The higher the pH value up to ∼7, the more conducive the soil electrolyte was to near-neutral pH SCC. The pH value in a soil electrolyte was found to depend on the level of CO2 in the soil solution and the initial HCO 3 − concentration before the introduction of CO2. For a given soil, the susceptibility depends on the actual level of CO2 in the soil electrolyte. Higher levels of CO2 lower the pH in the soil electrolyte and tend to increase the susceptibility to SCC. In laboratory tests, cathodic polarization was found to increase the susceptibility to failure, possibly by inhibiting general corrosion, which otherwise removed discrete stress-raising pits and defects from the specimen surface that acted as crack initiation sites or by increasing the extent of hydrogen-induced crack initiation or propagation. In the field, cathodic polarization is likely to prevent near-neutral pH SCC by increasing the pH at the pipe surface to values greater than 7.5. The pH was maintained near-neutral in the lab tests by continuous purging of the test solution with CO2/N2. A method is proposed for assessing the relative aggressiveness of various soil extracts to near-neutral pH SCC. Aggressive soil extracts appear to exhibit a narrower variation in pH between solutions purged with N2 and with CO2 than that for less-aggressive soil extracts purged with the same gases.
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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) | 0.017 | 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".