A Direct Assessment of Failure Pressure of High-Strength Steel Pipelines with Considerations of the Synergism of Corrosion Defects, Internal Pressure and Soil Strain
Why this work is in the frame
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Bibliographic record
Abstract
Abstract In this work, a new, finite element analysis-based model, the CX model, was developed to investigate the effect of corrosion defect, internal pressure and soil-induced strain on the local stress distribution and corrosion reaction on pipelines. The relevant calculations and analysis were also conducted on three industry models. Results demonstrated the predicted failure pressures of various grades of pipelines by the industry models are conservative when small defects are present, while overestimation of failure pressure occurs with the increase of the steel grade and the corrosion depth. The prediction reliability decreases with the increasing corrosion depth and the steel grade. The geometry of corrosion defect affects remarkably the local stress distribution, and plays a critical role in the failure pressure prediction of pipelines. Furthermore, while elastic deformation affects the steel corrosion slightly, usually at an undetectable level, plastic deformation increases corrosion of the steel significantly. The CX model is capable of simulating the distributions of corrosion potential and corrosion current density at corrosion defect, and thus providing an essential method to predict the defect propagation.
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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 | 0.000 |
| 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