Experimental study of effect of geometry on reinstallation of jack-up next to footprint
Bibliographic record
Abstract
Mobile jack-up drilling rigs often need to return to a site where a previous installation has left footprints in the seabed. Reinstallation near these depressions is a problematic operation because the jack-up's circular spudcan footings become subjected to eccentric and (or) inclined loading conditions. This can lead to structural failures within the jack-up legs and (or) excessive leg tilt and hull displacement. This paper reports a comprehensive set of geotechnical centrifuge experiments that investigated the effect of footprint geometry on the reinstallation response. Artificial conical shaped footprints were manually cut in the centrifuge sample, ensuring consistent shapes and minimizing any variation of undrained shear strength due to the process of initially installing and retrieving a spudcan. The effect of footprint geometry was thereby isolated. The vertical, horizontal, and moment loads induced on a model footing when penetrated at varying offsets are presented and these provide evidence on the effect of different footprint depths and angles on installation. The footprint geometry governed the horizontal force and moment observed during reinstallation between the level of the touchdown and the footprint toe. Further experimentation has shown that an equivalent skirted footing induced significantly higher horizontal forces (although it can be assumed to be significantly stiffer).
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".