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Experimental investigation of airflow over helicopter platform of a polar icebreaker

2015· article· en· W1520669222 on OpenAlexafffundabout
Mostafa Rahimpour, Peter Oshkai

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerospace and Aviation Technology
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsInflowParticle image velocimetryAirflowGeologyFlow (mathematics)PolarMeteorologyEnvironmental scienceMistMechanicsMarine engineeringPhysicsEngineeringTurbulence

Abstract

fetched live from OpenAlex

The airwake over the helicopter platform of a Canadian Coast Guard (CCG) polar icebreaker was studied experimentally. By application of high speed particle image velocimetry (PIV) on a 1:522 scaled model of the polar icebreaker, quantitative flow filed data were obtained in several vertical and horizontal planes. Present investigation was conducted with two types of the inflow conditions: (i) a uniform flow and (ii) a simulated atmospheric boundary layer (ABL). The incidence angle (α) varied between 0° to 330° with the increment of 30°. The unsteadiness of the flow was demonstrated by calculation of standard deviation of vertical airflow velocity (σ) over the helicopter platform, which directly influences the pilot workload. It was observed that, despite having relatively the same trend in different angels of incidence, the maximum value of σ is generally higher in the case of simulated ABL. It could be attributed to higher velocity gradients in oncoming flow associated with the simulated ABL inflow condition. Additionally this investigation showed that, in both inflow conditions, incidence angles of 0° and 300° were associated with the highest values for σ.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.202

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 head0.018
GPT teacher head0.224
Teacher spread0.206 · 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 designBench or experimental
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
Published2015
Admission routes3
Has abstractyes

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