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Record W4240467492 · doi:10.32920/ryerson.14654919.v1

Aerodynamic analysis of multirotor vehicles using a higher-order potential flow method

2021· preprint· en· W4240467492 on OpenAlexafffund
Devin F. Barcelos

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicAerospace and Aviation Technology
Canadian institutionsToronto Metropolitan University
FundersOntario Centres of Excellence
KeywordsMultirotorWakeThrustAerodynamicsBlade element theoryBlade element momentum theoryRotor (electric)Robustness (evolution)Aerospace engineeringMechanicsVortexControl theory (sociology)EngineeringPhysicsComputer scienceMechanical engineeringTurbineTurbine blade

Abstract

fetched live from OpenAlex

A higher-order potential flow method is adapted for the aerodynamic performance prediction of small rotors used in multirotor unmanned aerial vehicles. The method uses elements of distributed vorticity which results in numerical robustness with both a prescribed and relaxed wake representation. The radial loading and wake shapes of a rotor in hover were compared to experiment to show strong agreement for three disk loadings. The advancing flight performance prediction of a single rotor was compared to a single rotor was compared to a blade element momentum theory based approach and to experiment. Comparison showed good thrust and power agreement with experiment across a range of advance ratios and angles of attack. Prediction in descending flights showed improvements in comparison to the blade element momentum theory approach. The model was extended to a quadrotorm configuration showing the differences associated to vehicle orientation and rotor rotational direction.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.200
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.013
GPT teacher head0.269
Teacher spread0.256 · 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.

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

Citations2
Published2021
Admission routes2
Has abstractyes

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