Near Neutral pH Stress Corrosion Crack Growth Model Evaluation: PipeOnline™
Bibliographic record
Abstract
Abstract The pipeline industry has long sought a unified near-neutral pH stress corrosion cracking (NNpHSCC) growth model, which fully describes salient growth elements. In response to this gap, the Pipeline Research Council International (PRCI) has funded a multi-year research project, partnering with the University of Alberta (Project SCC-2-12). With the project nearing completion, application of the proposed near-neutral pH stress corrosion cracking growth model to two operating pipelines with known populations of stress corrosion crack features is presented. The remaining life of each crack feature detected by crack in-line inspection tools, under known loading, is calculated for two segments of operating pipelines in North America. The PRCI developed model, referred to as PipeOnline™, is compared to the legacy Enbridge linear growth and Paris Law models. A calibration technique for correcting the length and depth of the ILI feature calls provided by the in-line inspection vendor is reviewed, which takes into account tool tolerance and corrects length and depth to more closely match field findings. Efficiency improvements gleaned from this calibration technique are illustrated. While this calibration methodology is unique to the pipeline operator, the method is reviewed to allow other operators to readily implement the technique if it is found to be warranted. The PipeOnline model is tested for the post-calibration dimensions and compared to the legacy growth model. Each of the required inputs is defined, and methods of quantification are shown. Negligible growth thresholds are reviewed, and the truncation of stress cycles below the growth threshold is discussed. The strategy of deployment is shown, along with the proportion of features that are predicted to remain in dormancy. Methods to account for mean stresses and load application frequency are presented. The resulting PipeOnline re-inspection interval is compared to that predicted by typical existing growth models and then contrasted with excavation results on the asset. Calibration of the governing equation coefficients with rationale for each term is proposed for the pipeline segments examined in the study, and recommendations made for potential implementation for other operators, along with follow-on research.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".