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Record W3216708896 · doi:10.17736/ijope.2021.jc834

Modelling of a DP Drillship Advancing in Managed Ice Fields: Comparison Between Numerical Simulations and Ice Basin Tests

2021· article· en· W3216708896 on OpenAlexaboutno aff
Mohammed Islam, Mohamed Sayed, David J. Watson

Bibliographic record

VenueInternational Journal of Offshore and Polar Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyStructural basinGeotechnical engineeringGeomorphology

Abstract

fetched live from OpenAlex

The present paper reports on comparisons between results from ice basin tests and numerical simulations. The tests were conducted in the model ice basin of the National Research Council Canada in St. John’s, Newfoundland. Those tests examined the performance of a vessel controlled by a dynamic positioning (DP) system in managed ice conditions at a scale of 1:40. A numerical ice dynamics model was used to simulate ice basin test conditions. The results indicate that surge direction thrust and ice force are in good agreement. Ice basin measurements, however, produced higher sway-direction ice forces and yaw-direction moments. It appears that the treatment of sidewall boundaries and the resulting confinement of the ice cover may have contributed to that discrepancy. An additional contribution may be due to differences between the DP algorithms, which were used in the numerical simulations and ice basin tests. Numerical simulations also examined the role of floe shapes. The results indicate that floe shapes obtained from field observations reduce sway-direction ice forces and yaw-direction moments below values obtained when using near-square floe geometries.

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 categoriesnone
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 score0.390
Threshold uncertainty score0.600

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.249
Teacher spread0.233 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2021
Admission routes1
Has abstractyes

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