A novel model for prediction of burst capacity of corroded pipelines subjected to combined loads of bending moment and axial compression
Why this work is in the frame
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Bibliographic record
Abstract
Most of the commonly used standards and codes for burst pressure prediction at a corrosion defect of steel pipelines generally just consider internal pressure alone. However, an actual oil/gas pipeline is usally subjected to external loads, such as axial compression/tension and bending moment, which may affect the burst capacity of the pipeline. In this study, a three-dimensional (3D) nonlinear finite element (FE) model validated by burst tests was developed to investigate the effect of bending moment and axial force on the burst capacity of corroded pipelines . Subsequently, the effects of external loads (i.e., bending moment, and axial force) and corrosion geometry features (involving corrosion depth , width, length, and clock position) on the pipe burst pressure were determined. Then, based on a series of FE cases, a new burst prediction model for corroded pipelines subjected to the combination loads of bending load and axial compressive force was fitted and developed. Finally, the effectiveness and reliability of the new proposed model were verified by extensive parametric FE analysis and burst test data. The results show that the prediction errors for the failure pressures between the proposed-model and the FEM were less than 10% for most 92.793% of the 222 cases. Moreover, the proposed model can also be applied to the condition that the pipeline is under single internal pressure, and its prediction accuracy is better than that of other seven well-known models of ASME B31G, Mod B31G (0.85 d L), Z662, DNV, PCORRC, CUP, and Shell-92.
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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