<i>2013 Frank Newman Speller Award Lecture:</i> Integrity Management of Natural Gas and Petroleum Pipelines Subject to Stress Corrosion Cracking
Bibliographic record
Abstract
Stress corrosion cracking (SCC) can be a serious threat to the integrity of natural gas and petroleum pipelines. This paper describes how the pipeline industry responded to this threat by performing a comprehensive research program to determine the cause(s) of the failures and investigate various techniques for preventing future failures. The paper focuses on a relatively concise list of discoveries that have had a measurable impact on mitigation of the SCC threat. Starting with the first recognized SCC failure in 1965, the research is described in which the intergranular form of cracking (known as high-pH SCC or classical SCC) was investigated to identify the causative agent and the controlling metallurgical, environmental, and stress-related factors. In the 1980s, a second, transgranular form of SCC (near-neutral-pH SCC) was discovered in Canada, resulting in a similar scope of research activities designed to develop mitigation methods for this form of cracking. The paper then discusses how the information developed in these research programs is incorporated into pipeline integrity management programs.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.031 | 0.015 |
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".