A Limit State Function for Pipelines Containing Long Corrosion Defects
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Currently, there exist various models that predict the burst capacity of a pipeline containing corrosion defects. Recent studies have indicated that these models tend to be overly conservative for long corrosion defects. This paper, based on a PRCI-sponsored study, aims at minimizing this conservatism through a series of steps. First, different definitions for long corrosion defects prevalent in the literature were examined and compared, and the most suitable criterion was implemented. Next, three existing burst pressure models for general corrosion defects were identified and evaluated: ASME B31G-modified, a model developed at C-FER and a model developed at the University of Waterloo. The suitability of these models for long corrosion defects was assessed using a database of 50 full-scale burst test specimens containing natural long corrosion defects. Finally, based on this evaluation, the most apposite burst pressure prediction model for long corrosion defects was selected and a corresponding model error factor was derived.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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