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Record W4380589236 · doi:10.4271/2023-01-1443

Experimental Evaluation of Icephobic Coatings on a UAV Propeller Operated in an Icing Wind Tunnel

2023· article· en· W4380589236 on OpenAlexaff
Derek Harvey, Éric Villeneuve, C. Volat, Mathieu Béland, Maxime Lapalme

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2023
Typearticle
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsPropellerMaterials scienceIcing conditionsGlazeSurface roughnessWind tunnelComposite materialAirspeedIcingSiliconeCoatingWind speedEnvironmental scienceMarine engineeringPhysicsMeteorologyCeramicEngineeringAerospace engineering

Abstract

fetched live from OpenAlex

In this research, the performance of two commercially available icephobic coatings is evaluated on an 81% scaled-down version of the Bell Flight APT 70 drone propeller. Tests are performed in an icing wind tunnel (IWT) under selected severe icing conditions to test the ice protection capability of coatings against both glaze and rime ice. Two different coating formulations are used, one is a polydimethylsiloxane (PDMS) acetoxy terminated coating, the other an epoxy-silicone. The coatings were briefly characterized in terms of their surface roughness, water contact angle and ice adhesion reduction factor compared to aluminum using the centrifugal adhesion test (CAT). Blade sets were prepared for both coatings and a third uncoated set was tested for reference purposes. Tests in the IWT were performed to simulate a true airspeed of 35 m/s and a constant propeller rotational speed of 5 500 RPM. Two conditions of liquid water content (LWC) and droplet median volumetric diameter (MVD) were considered: LWC = 0.8 g/m3, MVD = 20 μm and LWC = 0.2 g/m3, MVD = 40 μm. The first condition was performed at static air temperatures of -5°C, -12°C and -20°C while the second was only performed at -5°C. The performance of the propeller is evaluated by means of the relative change in thrust coefficient, the torque coefficient and propeller efficiency. Tests were conducted such that operating conditions are maintained until vibration limits exceed the tolerated threshold to allow the possibility for multiple ice shedding events. Results demonstrated that the PDMS coating successfully reduced ice adhesion for all tests conditions while the epoxy-silicone only reduced ice adhesion for tests conditions at -5°C. The ice protection provided by either coating is shown to be insufficient to ensure safe flight under icing conditions due to significant propeller performance degradation and severe vibrations caused by non-symmetrical ice shedding.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.034
GPT teacher head0.289
Teacher spread0.255 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

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