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Record W3129641858 · doi:10.3390/aerospace8020053

A Numerical and Experimental Investigation of the Convective Heat Transfer on a Small Helicopter Rotor Test Setup

2021· article· en· W3129641858 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAerospace · 2021
Typearticle
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsUniversité du Québec à ChicoutimiÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of CanadaConsortium de Recherche et d’innovation en Aérospatiale au Québec
KeywordsIcingHeat transferMechanicsRotor (electric)Icing conditionsAerospace engineeringWind tunnelConvective heat transferReynolds numberComputational fluid dynamicsPhysicsMechanical engineeringMeteorologyEngineeringTurbulence

Abstract

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In-flight icing affects helicopter performance, limits its operations, and reduces safety. The convective heat transfer is an important parameter in numerical icing simulations and state-of-the-art icing/de-icing codes utilize important computing resources when calculating it. The BEMT–RHT and UVLM–RHT offer low- and medium-fidelity approaches to estimate the rotor heat transfer (RHT). They are based on a coupling between Blade element momentum theory (BEMT) or unsteady vortex lattice method (UVLM), and a CFD-determined heat transfer correlation. The latter relates the Frossling number (Fr) to the Reynolds number (Re) and effective angle of attack (αEff). In a series of experiments carried out at the Anti-icing Materials International Laboratory (AMIL), this paper serves as a proof of concept of the proposed correlations. The objective is to propose correlations for the experimentally measured rotor heat transfer data. Specifically, the Frx is correlated with the Re and αEff in a similar form as the proposed CFD-based correlations. A fixed-wing setup is first used as a preliminary step to verify the heat transfer measurements of the icing wind tunnel (IWT). Tests are conducted at α = 0°, for a range of 4.76 × 105 ≤ Re ≤ 1.36 × 106 and at 10 non-dimensional surface wrap locations − 0.62 ≤ (S/c) ≤ + 0.87. Later, a rotor setup is used to build the novel heat transfer correlation, tests are conducted at two pitch angles ((θ) = 0° and 6°) for a range of rotor speeds (500 RPM ≤ (Ω) ≤ 1500 RPM), three different radial positions ((r/R) = 0.6, 0.75 and 0.95), and 0 ≤ S/c ≤ + 0.58. Results indicate that the fixed-wing Frx at the stagnation point was in the range of literature experimental data, and within 8% of fully turbulent CFD simulations. The FrAvg also agrees with CFD predictions, with an average discrepancy of 1.4%. For the rotor, the Ω caused a similar increase of Frx for the tests at θ = 0° and those at θ = 6°. Moreover, the Frx behavior changed significantly with r/R, suggesting the αEff had a significant effect on the Frx. Finally, the rotor data are first correlated with Rem (at each S/c) for θ = 0° to establish the correlation parameters, and a term for the αEff is then added to also account for the tests at θ = 6°. The correlations fit the data with an error between 2.1% and 14%, thus justifying the use of a coupled approach for the BEMT–RHT and UVLM–RHT.

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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 score0.021
Threshold uncertainty score0.270

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 head0.011
GPT teacher head0.199
Teacher spread0.187 · 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