Parametric study of buried steel and high density polyethylene gas pipelines due to oblique-reverse faulting
Bibliographic record
Abstract
A numerical study is carried out on buried steel and high density polyethylene (HDPE) pipelines subjected to oblique-reverse faulting. The components of the oblique-reverse offset along the horizontal and normal directions in the fault plane are determined using well-known empirical equations. The numerical model is validated using the experimental results and detailed finite element model of a 114.3 mm (4″) steel gas pipe subjected to a reverse fault offset up to 0.6 m along the faulting direction. Different parameters such as the pipe material, the burial depth to the pipe diameter ratio (H/D), the pipe diameter to wall thickness ratio (D/t), and the fault–pipe crossing angle are considered and their effects on the response parameters are discussed. The maximum and minimum compressive strains are observed at crossing angles of 30° and 90°, respectively. It is found that the dimensionless parameters alone are not sufficient for comparison purposes. Comparing steel and HDPE pipes, it is observed that HDPE pipes show larger compressive strains due to their lower strength and stiffness. For both steel and HDPE pipes, peak strains increase with increasing D/t and H/D ratio for a constant pipe diameter and fault offset. For a given H/D ratio, compressive strains increase with increasing D/t ratio in HDPE pipes, while in steel pipes considered in this study, this effect is negligible. Finally, the peak strains of the pipes are compared to those suggested by Canadian Standard Association for Oil and Gas Pipeline System, CSA Z662.
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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 | 0.001 |
| 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".