Crack in Corrosion Defect Assessment in Transmission Pipelines
Bibliographic record
Abstract
Cracks may occur coincident with corrosion representing a new hybrid defect in gas and oil pipelines known as crack in corrosion (CIC) that is not directly addressed in the current codes or assessment methods. Hence, there is a need to provide an assessment of CIC and evaluate the line integrity, as well as identify the requirements for defect repair or line hydrotest. An experimental investigation was undertaken to evaluate the collapse pressures of lines containing corrosion, cracks, or (CIC) defects in a typical line pipe (API 5L Grade X52, 508 mm diameter, 5.7 mm wall thickness). The mechanical properties of the pipe were measured using tensile, Charpy, and J-testing for use in applying evaluation criteria. Rupture tests were undertaken on end-capped sections containing uniform depth, finite length corrosion, cracks, or CIC defects. Failure occurred by plastic collapse and ductile tearing for the corrosion defects, cracks, and CIC geometries tested. For the corrosion defects, the corroded pipe strength (CPS) method provided the most accurate results (13% conservative on average). The API 579 (level 3 failure assessment diagram (FAD), method D) provided the least conservative collapse pressure predictions for the cracks with an average error of 20%. The CIC collapse pressures were bounded by those of a long corrosion groove (upper bound) and a long crack (lower bound), with collapse dominated by the crack when the crack depth was significant. Application of API 579 to the CIC provided collapse pressure predictions that were 18% conservative. Sixteen rupture tests were successfully completed investigating the failure behavior of longitudinally oriented corrosion, crack, and CIC. The pipe material was characterized and these properties were used to predict the collapse pressure of the defects using current methods. Existing methods for corrosion (CPS) and cracks (API 579, level 3, method D) gave conservative collapse pressure predictions. The collapse pressures for the CIC were bounded by those of a long corrosion groove and a long crack, with collapse dominated by the crack when the crack depth was significant. CIC failure behavior was determined by the crack to corrosion depth ratio, total defect depth and its profile. The results showed that the failure pressures for CIC were reduced when their equivalent depths were similar to those of corrosion and using crack evaluation techniques provided an approximate collapse pressure.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".