Evaluation of the Effect of Internal Pressure and Flaw Size on the Tensile Strain Capacity of X42 Vintage Pipeline Using Damage Plasticity Model in Extended Finite Element Method (XFEM)
Bibliographic record
Abstract
Abstract Pipelines subjected to displacement-controlled loading such as ground movement may experience significant longitudinal strain. This can potentially impact pipeline structural capacity and their leak-tight integrity. Reliable calibration of the tensile strain capacity (TSC) of pipelines plays a critical role in strain-based design (SBD) methods. Recent studies were focused mostly on high toughness modern pipelines, while limited research was performed on lower-grade vintage pipelines. However, a significant percentage of energy resources in North America is still being transported in vintage pipelines. Eight full-scale pressurized four-point bending tests were previously conducted on X42, NPS 22 vintage pipes with 12.7 mm wall thickness to investigate the effect of internal pressure and flaw size on TSC. The pipes were subjected to 80% and 30% specified minimum yield strength (SMYS) internal pressures with different girth weld flaw sizes machined at the girth weld center line. This paper evaluates the TSC of X42 vintage pipeline by utilizing ductile fracture mechanics models using damage plasticity models in ABAQUS extended finite element method (XFEM). The damage parameters required for simulating crack initiation and propagation in X42 vintage pipeline are calibrated numerically by comparing the numerical models with the full-scale test results. With the appropriate damage parameters, the numerical model can reasonably reproduce the full-scale experimental test results and can be used to carry out parametric analysis to characterize the effect of internal pressure and flaw size on TSC of X42 vintage pipes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".