Revisiting burst pressure models for corroded pipelines
Why this work is in the frame
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Bibliographic record
Abstract
A number of burst pressure models were developed to determine the remaining strength of corroded pipelines. However, no single model has been found to be acceptable for predicting the burst pressure correctly. In this paper, the burst pressure models for corroded pipelines are revisited based on the structures of three existing models. The model parameters are re-evaluated using an optimization (differential evolution) algorithm with a database developed based on finite element (FE) analysis. A series of FE analysis are performed to determine the burst pressures of corroded pipelines with varying pipe diameters, wall thicknesses, corrosion dimensions and material strength grades. The models with new sets of model parameters provide the burst pressure reduction factors that match with the FE results and experimental data better than the existing models. The study reveals that FE analysis along with an optimization algorithm can effectively be used to develop improved models for better fitness-for-service assessment of 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 | 0.000 | 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) | 0.000 | 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