Three-dimensional numerical analysis of centrifuge experiments on a model jack-up drilling rig on sand
Bibliographic record
Abstract
Jack-up drilling rigs are usually founded on three shallow footings. Under wind, wave, and current loading offshore, the footings of these tall multi-footing systems transfer large moment loads in addition to self-weight, horizontal load, and even torsion to the underlying soil. To be able to deploy a jack-up safely at a particular offshore site, the unit’s capacity to withstand a 50 year return period storm is required to be checked in accordance with current guidelines (Site specific assessment of mobile jack-up units, The Society of Naval Architects & Marine Engineers). As the overall system behaviour is influenced significantly by the footing restraint, models that account for the complex nonlinear foundation–soil interaction behaviour are required to be integrated with the structural and loading models. Displacement-hardening plasticity theory has been suggested as an appropriate framework to formulate force-resultant models to predict shallow foundation behaviour. Recent research has extended such a model to account for six degree-of-freedom loading of circular footings on sand, allowing integrated structure–soil analysis in three dimensions. This paper discusses “class A” numerical predictions of experiments on a model jack-up in a geotechnical centrifuge, using the integrated modelling approach, and critically evaluates the predictive performance. The numerical simulations are shown to represent a significant improvement compared with the method outlined in the current guidelines.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".