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Development of a CFD Model of Propeller Slipstream

2024· article· en· W4399801650 on OpenAlexaff
Benjamin Herfray, Meyer Nahon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Fluid Dynamics Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsComputational fluid dynamicsPropellerComputer scienceMarine engineeringWakeAerospace engineeringEngineering

Abstract

fetched live from OpenAlex

The growing interest in electric powertrains for aircraft has led to new aircraft designs for air taxis and Unmanned Aerial Vehicles (UAVs), Electric powertrains allow aircraft designers to consider novel propulsion layouts such ones in which many motors/propellers are distributed along the wing's leading edge, known as Distributed Electric Propulsion (DEP). This configuration confers a number of advantages, including the mitigation of airflow separation. Understanding the wake of a propeller can allow us to develop a better understanding of the dynamical behaviour of DEP aircraft, where large parts of the wings are immersed in the propeller slipstream, which can have a large influence on the forces generated by the wing. In the present work, we describe a method for simulating the wake of a given propeller in the OpenFOAM Computational Fluid Dynamics (CFD) package. The propeller model uses body forces within a finite propeller region, acting as a momentum source for fluid passing through it. Simulations using this method were performed for various propeller geometries, rotation rates, and freestream velocities, and results were compared with experimental measurements from the literature, yielding good agreement.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.539
Threshold uncertainty score0.197

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 head0.022
GPT teacher head0.245
Teacher spread0.222 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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