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Record W4388537262 · doi:10.3397/no_2023_0083

Numerical Simulation of Aeroacoustics Generated by Flow around 30P30N High-lift Aerofoil using Hybrid CFD/BEM approach

2023· article· en· W4388537262 on OpenAlexaff
Masaaki Mori

Bibliographic record

VenueNOISE-CON proceedings · 2023
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsCybernet Systems Corporation (Canada)
Fundersnot available
KeywordsAirfoilComputational fluid dynamicsPhysicsAcousticsBoundary element methodAeroacousticsLift (data mining)MechanicsAngle of attackFinite element methodSound pressureAerodynamicsComputer science

Abstract

fetched live from OpenAlex

In this study, we have performed the acoustic simulation generated by the flow around the 30P30N airfoil with a slat and a flap by means of Boundary element Method using quadrupole sources extracted from the unsteady CFD simulations. The CFD simulations are performed using Ansys Fluent with LES Dynamic Model, and compressible flow fields have been solved. The attack angles of the airfoil are 5.5 and 9.5 degree. When the BEM calculation for the acoustic propagation was performed, the FMM (Fast Multipole Method) and FMBEM were used to calculate quickly the contributions from the quadrupole sources and acoustic propagation, reflection and diffraction on the boundaries, those are the walls of the 30P30N airfoil. The results of the acoustic simulations show a relatively good agreement with the experimental data and other researchers' simulation results. The directivities of the acoustic pressure for the primary peak frequency are shown and they depend on the attack angle of the airfoil. The far-field SPL also depends on the attack angle of the airfoil and decreases as the attack angle increases. We have also investigated the quadrupole sources in frequency domain, and the results showed that the quadrupole sources at far-field SPL peak frequencies near the wake of slat and the suction side of the main element of the airfoil are stronger than those in other regions.

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 categoriesMeta-epidemiology (narrow)
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 score0.159
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.016
GPT teacher head0.227
Teacher spread0.211 · 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.

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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueNOISE-CON proceedingsSame topicAerodynamics and Acoustics in Jet FlowsFrench-language works237,207