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Record W4385560336 · doi:10.23977/jemm.2023.080303

Improved Blade Element Theory and Autorotating Rotor Aerodynamic Characteristics Analysis

2023· article· en· W4385560336 on OpenAlexvenueno aff
Jizhen Li, Bing Lan

Bibliographic record

VenueJournal of Engineering Mechanics and Machinery · 2023
Typearticle
Languageen
FieldEngineering
TopicAerospace Engineering and Control Systems
Canadian institutionsnot available
Fundersnot available
KeywordsBlade element theoryAerodynamicsWakeRotor (electric)Aerodynamic forceBlade (archaeology)Fourier seriesMechanicsPhysicsHelicopter rotorPlane (geometry)Structural engineeringMathematicsEngineeringGeometryMathematical analysis

Abstract

fetched live from OpenAlex

During forward flight, the flow field of autorotating rotor was very complicated, which caused induced velocity of the disc plane difficult to be obtained. In order to analyze aerodynamic characteristics of the autorotating rotor, improved blade element theory, using the unlimited-bladed fixed wake method to establish a mathematical model, which could obtain velocity of the disc plane induced by fixed wake of autorotating rotor. According to the Biot-Savert Theorem, the expression of axial induced velocity of disc plane could be got by integerating. The circulation and induced velocity were all expanded into Fourier series by azimuth, and then axial induced velocity could be carried out by iteration. Combined the blade element theory, aerodynamic forces of the autorotating rotor was obtained, and then analyzed its aerodynamic characteristics.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.003
GPT teacher head0.183
Teacher spread0.180 · 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
GenreMethods

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

Citations0
Published2023
Admission routes1
Has abstractyes

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