PR-378-083601-R01 Effect of Pressure Fluctuations on Growth Rate of Near-Neutral pH SCC
Bibliographic record
Abstract
This report summarizes the work completed in Year One of the three-year project: PRCI SCC-2-12 Effect of Pressure Fluctuations on Growth Rate of Near-Neutral pH SCC. The investigation in Year One has been primarily focused on the validation of the software being developed for crack growth and remaining life prediction using SCADA Data. A total of 9 pressure spectra, 4 for oil pipelines and 5 for gas pipelines, have been collected and used as inputs for the software. It was found that a pressure spectrum can be quantified using a parameter termed as Spectra Factor to represent the severity of load/pressure interactions in terms of crack growth rate. A spectra factor higher than one indicates the enhanced crack growth rate by load interactions, such as the case where unloads are frequently present in the pressure spectra, while a spectra factor lower than one may be associated with a retarded crack growth, which can be seen in pressure spectra with predominant overloading events. The oil pipelines are characterized with more frequent and larger pressure fluctuations, and crack growth is directly caused by these cycles. The gas pipelines are characterized with minor cycles with high stress ratio and the subsequent underloading cycles with low stress ratios, and crack growth rate can be enhanced by a factor 10 under the combined minor-underload pressure fluctuation cyclic loading scenarios. The software allows the SCADA/pressure fluctuation data with Excel spreadsheet format to be directly analyzed producing a projected remaining life of the pipeline based on the past pressure fluctuations and assumed future pressure fluctuations.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".