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Record W4377990324 · doi:10.1063/5.0150267

On dissecting the wakes of flapping wings

2023· article· en· W4377990324 on OpenAlexaff
Priyam Chakraborty, Srikanth Goli, Arnab Roy

Bibliographic record

VenuePhysics of Fluids · 2023
Typearticle
Languageen
FieldEngineering
TopicBiomimetic flight and propulsion mechanisms
Canadian institutionsUniversity of Waterloo
FundersAeronautics Research and Development BoardDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsFlappingWakePhysicsAerospace engineeringAerodynamicsKinematicsFlow visualizationMechanicsFlow (mathematics)Classical mechanicsWingEngineering

Abstract

fetched live from OpenAlex

Flapping is an energy-demanding mode of fast animal locomotion that requires physiology, wing kinematics, and unsteady mechanics to work in unison. The trailing flow or wake is a signature of flapping mechanics, which makes it a popular candidate for visualization and analysis. While there are multiple ways to analyze wakes, we need a general framework to ensure utility of the analysis in bio-inspired flapping flight. In this article, we develop a theoretical framework to analyze the transport phenomena of wakes. To illustrate, we apply the theory to a two-dimensional modeled hovering flight comprising engineered rigid flapping plates, which vary in aspect ratio, wingbeat frequency, and the use of winglet. The results potentially explain certain observations in natural flight.

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 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 score0.025
Threshold uncertainty score0.206

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.228
Teacher spread0.210 · 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.

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

Citations6
Published2023
Admission routes1
Has abstractyes

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