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Record W3038841903 · doi:10.2514/1.c035614

Aerodynamic Interactions of Quadrotor Configurations

2020· article· en· W3038841903 on OpenAlexafffund
Devin F. Barcelos, Amir Kolaei, Goetz Bramesfeld

Bibliographic record

VenueJournal of Aircraft · 2020
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Fluid Dynamics Research
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of CanadaOntario Centres of Excellence
KeywordsAerodynamicsThrustRotor (electric)Aerospace engineeringAerodynamic forceRotation (mathematics)Moment (physics)Power (physics)Flow (mathematics)MechanicsEngineeringStructural engineeringPhysicsMechanical engineeringComputer scienceClassical mechanics

Abstract

fetched live from OpenAlex

An advanced potential flow method is used to study the aerodynamic interactions between small rotors of quadrotor configurations and the impact on the overall flight performance. The aerodynamic analysis method is validated by comparing the thrust and power predictions of isolated rotors in hover and forward flight with experimental results. The aerodynamic model was next extended to consider the interactions of several rotors of various quadrotor configurations. Compared with an independent rotor, the interaction of multiple, closely located rotors increases the power requirements of the vehicle and causes a loss of thrust. For diamond configurations, the rotation direction of the lead rotors impacts the thrusts of the midrotors and, subsequently, the overall vehicle rolling moment. For square configurations, slightly higher total thrusts and slightly greater tendencies to pitch up are observed when the retreating blades of the lead rotors move back along the vehicle centerline than for the reversed rotational orientations. The diamond configuration exhibits up to 3.5% higher rotor efficiency and a lesser tendency to pitch up with increasing forward speed than the square configuration.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.246
Teacher spread0.230 · 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 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

Citations37
Published2020
Admission routes2
Has abstractyes

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