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Record W2941220760 · doi:10.2514/1.j058025

Investigation of Unsteady Pressure Fluctuations in Flow over Backward-Facing Step

2019· article· en· W2941220760 on OpenAlexafffund
Stephen J. Wilkins, Mahdi Hosseinali, Joseph W. Hall

Bibliographic record

VenueAIAA Journal · 2019
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of CanadaCompute Canada
KeywordsMechanicsTurbulenceVortex sheddingVortexPhysicsLarge eddy simulationFlow (mathematics)ConvectionDetached eddy simulationReynolds-averaged Navier–Stokes equationsReynolds number

Abstract

fetched live from OpenAlex

Flow over a backward-facing step at , based on the step height, is simulated using the Divergence Free Synthetic Eddy Method of Poletto et al. (“A New Divergence Free Synthetic Eddy Method for the Reproduction of Inlet Flow Conditions for LES,” Flow, Turbulence and Combustion, Vol. 91, No. 3, 2013, pp. 519–539.), implemented in OpenFOAM® 1606, which preserves the instantaneous fluctuating pressure field in the domain, which is normally lost. Examination of the pressure spectra at various positions normal to the wall is well represented by wall-pressure measurements at all but the highest frequencies examined here. Various spectral peaks corresponding to shear-layer movement, discrete vortex shedding from the step, and numerous shear-layer instabilities are investigated using power and cross-spectral measurements of the fluctuating wall pressures. Convective velocities obtained from the cross-spectral phase indicate that the lowest frequencies convect slowly, whereas the higher frequencies near the measured spectral peaks convect at . There is an increase in convective velocity as the measurement locations are moved farther downstream. Additionally, an increase in peak frequency was found in this examination; however, the increase in convective velocity (approximately equal to 33%) and frequency (approximately equal to 7–11%) calculated at different streamwise positions were not found to be directly proportional, indicating that the increase in peak frequency cannot be solely explained by flow acceleration but that the structures are likely undergoing streamwise or spanwise deformation as well.

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 score0.029
Threshold uncertainty score0.339

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 head0.007
GPT teacher head0.193
Teacher spread0.187 · 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

Citations8
Published2019
Admission routes2
Has abstractyes

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