An Efficient Methodology for the Reliability Analysis of Corroding Pipelines
Why this work is in the frame
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Bibliographic record
Abstract
This paper describes an efficient methodology that utilizes the first order reliability method (FORM) and system reliability approaches to evaluate the time-dependent failure probabilities of a pressurized pipeline at a single active corrosion defect considering three different failure modes, i.e., small leak, large leak, and rupture. The criteria for distinguishing small leak, large leak, and rupture at a given corrosion defect are established based on the information in the literature. The wedge integral and probability weighting factor methods are used to evaluate the probabilities of small leak and burst, whereas the conditional reliability index method is used to evaluate the probabilities of large leak and rupture. Two numerical examples are used to illustrate the accuracy, efficiency and robustness of the proposed methodology. The proposed methodology can be used to facilitate reliability-based corrosion management programs for energy pipelines.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it