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Ice Risk Analysis for Floating Wind Turbines and Associated Subsea Infrastructure, Offshore Newfoundland and Labrador

2024· article· en· W4404688783 on OpenAlexaffabout
Freeman Ralph, Tony King

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsCentre For Cold Ocean Resources Engineering
Fundersnot available
KeywordsSubseaSubmarine pipelineOffshore wind powerWind powerMarine engineeringOceanographyGeologyEnvironmental scienceEngineering

Abstract

fetched live from OpenAlex

Ice risk to floating wind turbines and associated subsea infrastructure has been evaluated for an area of interest (AOI) covering the northern Grand Banks, Flemish Pass and Orphan Basin, primarily conducted through two publicly-funded R&D projects. Iceberg and sea ice loads corresponding to a 50-year return period were estimated for the study area, considering both the influence of ice management and mooring system compliance. Iceberg contact rates with mooring lines was also assessed and the frequency and severity of atmospheric icing of turbines was modelled using available data. Iceberg risk to subsea electrical cables was estimated using an updated iceberg contact frequency model, and physical testing and modelling programs were used to develop numerical models for assessing the response of a cable, given iceberg contact occurs. Based on the results of these two projects, it was concluded that the ice risk to floating wind turbines and associated subsea infrastructure in the AOI is minimal. The changing ice regime in the region, resulting in an ongoing decline in sea ice and iceberg presence, indicates that ice risk may be even less of a concern in the future.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.535
Threshold uncertainty score0.650

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.006
GPT teacher head0.204
Teacher spread0.198 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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