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Record W4281633404 · doi:10.1139/dsa-2021-0031

Aerodynamics effect of holes in UAV wings modified for VTOL capability

2022· article· en· W4281633404 on OpenAlexvenueno aff
Laith Sawaqed, Ahmad H. Bani Younes, Mohammad I. Aldalal’ah

Bibliographic record

VenueDrone Systems and Applications · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced Aircraft Design and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsDragLift-to-drag ratioAerodynamicsWingLift-induced dragLift (data mining)Aerospace engineeringTurbulenceWind tunnelAngle of attackComputational fluid dynamicsMarine engineeringWing configurationMechanicsWing twistDrag coefficientLift coefficientWingtip vorticesPhysicsEngineeringComputer scienceVortexHorseshoe vortexReynolds numberVorticity

Abstract

fetched live from OpenAlex

This research investigates the possibility of modifying the X8 Skywalker from a fixed-wing unoccupied aerial vehicle into a convertiplane to utilize the advantages of vertical take-off and landing and maintain the benefits of fixed-wing design. In this study two configurations were tested; the first one includes sharp holes embedded in the wings for the propellers and the second one has filleted holes. The purpose of the study is to analyze the new configurations’ ability to generate enough lift after reducing the wings area. The aerodynamic coefficients are calculated through computational fluid dynamics. Simulation results were validated experimentally by using the wind tunnel. Even though the holes reduced the wing area by about 20%, the proposed modifications could lead to a lift to drag ratio around 7. The results showed that the new configurations can generate five times the lift compared to the drag, while the maximum lift to drag ratio dropped by 50% compared to the original design. At the same time, the filleted hole configuration showed less drag and turbulence effects, especially at a low angle of attack, compared to the sharp hole 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.008
GPT teacher head0.232
Teacher spread0.224 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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