Elastoplastic consolidation solutions for scaling from shallow penetrometers to pipelines
Bibliographic record
Abstract
The build-up of friction on seabed pipelines is an important design consideration, affecting their stability and the resulting in-service strain and fatigue. The consolidation beneath a partially embedded pipeline has been investigated in the past and linked to the build-up of axial pipe–soil resistance. This paper extends previous work by providing solutions for consolidation around a new class of shallow penetrometer, to provide a basis to scale from site investigation results directly to the build-up of pipeline friction. Small-strain finite element analyses, using the Modified Cam Clay soil model, are presented for the novel toroid and ball penetrometers. The effects of initial penetrometer embedment, device roughness, strength gradient, and overload ratio have been explored in a comprehensive manner, and are compared with pipe results. The toroid penetrometer shows excellent agreement with an element of an infinitely long pipe, simplifying the scaling process. The ball penetrometer shows a faster consolidation response, typically by a factor of three, reflecting the more effective drainage mechanisms of a three-dimensional device compared to a plane strain device. The dissipation responses are fitted by simple equations to aid application in design.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".