Soil resistance under pipe vertical uplift in compacted clay: shallow tensile and deep shear failure mechanisms
Bibliographic record
Abstract
The paper investigates the mobilization of soil resistance against pipe vertical uplift in compacted Regina clay using both physical and numerical modelling. Results of the physical model tests reveal that the measured uplift resistance is much lower than the one estimated by the relevant equation in engineering design guidelines for buried pipelines. This discrepancy is elucidated through finite element (FE) and extended finite element (XFE) analyses of results from model tests with various pipe diameters and embedment depths. XFE numerical results reveal the presence of tensile failure in the form of a fracture that reduces the uplift resistance. This fracturing cannot be captured explicitly in FE modelling whose predictions are consistent with design guidelines. It is found that for shallow embedment depths (H/D < 5) and high cohesive strengths (c/γH > 5), the soil above the pipe is set in flexure where a hybrid tensile-shear failure mode lowers the uplift resistance. By contrast, tensile failure does not develop at greater embedment depths with lower cohesive strengths, thus yielding an uplift resistance close to the design guidelines. A correlation between the reduction in uplift resistance in compacted clay and its normalized cohesion is developed to enrich the current design guidelines by including hybrid tensile-shear failure modes at shallow embedment depths.
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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) | 0.000 | 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 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".