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Record W4225753848 · doi:10.22215/etd/2022-14862

A Hybrid De-icing Strategy Utilizing Tailored Anti-Icing Coatings Paired with Electro-Thermal and Electro-Mechanical Ice Protection Systems for Use on Rotary-Wing Aircraft

2022· dissertation· en· W4225753848 on OpenAlexaff
Nicholas Tepylo

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsCarleton University
Fundersnot available
KeywordsIcingMaterials scienceCoatingComposite materialFuselageAerospace engineeringMechanical energyMechanical engineeringEngineeringPower (physics)Meteorology

Abstract

fetched live from OpenAlex

Since the beginning of aviation, ice accumulation on aircraft surfaces has been a persistent problem.On rotorcraft, the consequences can be catastrophic as small changes to the blade aerodynamics can result in a loss of the vehicle.Most small and medium-sized civil helicopters do not have a means of de-icing while in flight as these systems are heavy and require a significant amount of power.This dissertation aims to investigate hybrid ice protection systems (IPS), in which an icephobic coating is paired with an electro-thermal or electro-mechanical IPS to reduce the weight and required power of the system.While my name appears on this dissertation as the sole author and contributor, completion of this work would not have been possible without the contributions of many.I would like to express my gratitude to all those

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: Other · Consensus signal: none
Teacher disagreement score0.001
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 head0.018
GPT teacher head0.227
Teacher spread0.209 · 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
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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