Soil Loads on Polyethylene Natural Gas Pipelines Subjected to Relative Axial Ground Displacements
Bibliographic record
Abstract
The performance of buried natural gas pipeline systems in areas subjected to permanent ground displacements is an important engineering consideration since geotechnical hazards can be a major cause of damage to these utilities. Although pipe-soil interaction models exist, there is only limited experience with pipeline materials other than steel, and particularly in relation to polyethylene (PE). With this background, a detailed research program involving full-scale physical model testing of buried pipeline systems was undertaken, and performance of straight PE pipes subject to relative axial soil movement was investigated as a part of this work. A closed-form solution was derived to account the nonlinear material response of MDPE pipes subject to relative axial soil movement, and the analytical results are compared with the results obtained from the full-scale testing. This closed-form solution provides a rational framework to estimate the response of the pipe (level of strain, force) and even the mobilized frictional length along the pipe for a known amount of ground displacement. The approach, in turn, could be used in estimating the relative axial soil displacement needed for pipe failure, which is an important consideration in the evaluation of the field performance of MDPE pipe systems located in areas of potential ground movement.
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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) | 0.002 | 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".