Influence of Geotechnical Loads on Local Buckling Behavior of Buried Pipelines
Bibliographic record
Abstract
Buried pipelines can be subjected to differential ground movement events. The ground displacement field imposes geotechnical loads on the buried pipeline and may initiate pipeline deformation mechanisms that exceed design acceptance criteria with respect to serviceability requirements or ultimate limit states. The conventional engineering approach to define the mechanical performance of pipelines has been based on combined loading events for “in-air” conditions. This methodology is assumed to be overly conservative and ignores soil effects that imposes geotechnical loads and also provides restraint, on buried pipelines. The importance of pipeline/soil interaction and load transfer mechanisms that may affect local buckling of buried pipelines is not well understood. In this study a three-dimensional continuum finite element (FE) model, using the software package ABAQUS/Standard, was developed and calibrated based on large-scale tests on the local buckling of linepipe segments for in-air and buried conditions. The effects of geotechnical boundary conditions on pipeline deformation mechanism and load carrying capacity were examined for a single small diameter pipeline with average diameter to thickness ratio and deep buried condition. The calibrated model successfully reproduced the large-scale buried test results in terms of the local buckling location, pipeline carrying load capacity, soil deformation and soil failure mechanism.
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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".