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Record W2062776794 · doi:10.1139/t08-115

Three-dimensional numerical analysis of centrifuge experiments on a model jack-up drilling rig on sand

2009· article· en· W2062776794 on OpenAlexvenueno aff
Britta Bienen, Mark Cassidy

Bibliographic record

VenueCanadian Geotechnical Journal · 2009
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
FundersAustralian Research Council
KeywordsCentrifugeEngineeringGeotechnical engineeringFoundation (evidence)Structural engineeringShallow foundationOffshore wind powerNonlinear systemTorsion (gastropod)Soil structure interactionMarine engineeringFinite element methodBearing capacityMechanical engineeringTurbine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.489
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.223
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2009
Admission routes1
Has abstractyes

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