PR-378-083601-R02 Effect of Pressure Fluctuations on Growth Rate of Near-Neutral pH SCC
Bibliographic record
Abstract
This report summarizes the work completed in Phase 1 and Phase 2 of PRCI SCC-2-12 project: Effect of Pressure Fluctuations on Growth Rate of Near-Neutral pH SCC. The following two insights from the two-phase PRCI SCC 2-12 project can be proven to be the most important: 1) The identification of three types of pressure fluctuations and their different susceptibility to crack growth; 2) The importance of load interaction effects during variable amplitude pressure fluctuations in the prediction of crack growth rate. The work has enabled us to divide near-neutral pH SCC cracking into the following two governing processes: the dissolution growth process for crack initiation and early stage crack growth and the hydrogen facilitated fatigue growth after crack initiation and dormancy. The first process features very high rate of dissolution at the pipe surface caused by various forms of galvanic processes and reduced crack growth in the depth direction leading to crack dormancy. The hydrogen facilitated fatigue growth process has been determined to be predominant for the crack growth after crack initiation and dormancy. Depending on the location of pipeline sections, the pressure fluctuations could be characterized into three types based on the relative pressure levels of the large loading events and the minor cycles. It has been determined from extensive experimental investigations that crack growth under Type I pressure fluctuations with frequent underload cycles, which is often found within 30 km downstream of a compressor station, can be enhanced significantly because of effects of load interactions of variable amplitude of cyclic loading. The load-interactions during SCC of pipeline steels in near-neutral pH environments are complex, which include both the time independent load-history interactions and the time dependent load interactions related to the rate of diffusion of hydrogen and hydrogen embrittlement in response to various scenarios of pressure fluctuations. Based on the experimental findings obtained, strategies for mitigating near-neutral pH crack initiation and crack growth during field operations have been proposed. The experimental findings have also been integrated into a software, namely the Pipe-Online, for making crack growth and remaining life prediction. For the purpose of capturing all the crack-growth contributing events of pressure fluctuations for life predictions, a method of recording pressure fluctuations has also been developed.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".