Impact of Model Errors of Burst Capacity Models on the Reliability Evaluation of Corroding Pipelines
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
This paper quantifies the impact of model error associated with the burst capacity model on the probability of burst of corroding oil and gas pipelines due to the internal pressure. Three burst pressure models that are widely used in the pipeline industry, namely the B31G Modified, det norske veritas (DNV), and pipeline corrosion failure criterion (PCORRC) models, are considered in the analyses. The time-dependent probabilities of burst of three hypothetical examples, which are representative of the oil and gas transmission pipelines in the United States, are evaluated by using the first-order reliability method (FORM) to carry out the comparative study. The analysis results indicate that the model error has a substantial effect on the burst probability evaluated. The probabilities of burst evaluated by considering the model error can be several orders of magnitude higher than those evaluated by ignoring the model error. The results underscore the critical importance of including the model error associated with the burst capacity model in the reliability analysis of corroding pipelines.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.008 |
| 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 | 0.000 | 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