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Record W4403489886 · doi:10.23977/jemm.2024.090214

Numerical investigation on the aerodynamic characteristics of the multi-blade propellers under different inflow conditions

2024· article· en· W4403489886 on OpenAlexvenueno aff

Bibliographic record

VenueJournal of Engineering Mechanics and Machinery · 2024
Typearticle
Languageen
FieldEngineering
TopicCavitation Phenomena in Pumps
Canadian institutionsnot available
Fundersnot available
KeywordsBlade (archaeology)AerodynamicsInflowMarine engineeringAerospace engineeringStructural engineeringEngineeringComputer scienceGeologyMechanicsPhysics

Abstract

fetched live from OpenAlex

EVTOL (Electric Vertical Take-off and Landing) vehicles have the advantages of no runway for take-off, high safety, low noise, zero-emission, easy maintenance, and low cost after scale operation. Under the background of the global development of a low-altitude economy, the demand for eVTOL is expected to grow rapidly. Propellers with different blade numbers are modelled, and the aerodynamic characteristics of three, four, five, and six-bladed propellers under uniform airflow environment conditions are analysed. The pressure values on the surface of each propeller blade were determined by simulating the airflow environment. The performance characteristics of the four propellers under different airflow conditions were numerically investigated. A prototype blade model was fabricated in an aerodynamic wind tunnel, and experimental values of aerodynamic pressures were obtained through calculations and simulations. The computational results help to provide insight into the physical characteristics of the airflow around the propeller blade and the resulting performance metrics.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.283

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 head0.013
GPT teacher head0.203
Teacher spread0.190 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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