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Record W3136692793 · doi:10.11159/htff19.170

Effect of Leading-Edge Pressure in the Boundary Layer under HighFreestream Disturbances

2019· article· en· W3136692793 on OpenAlexvenueno aff
Yasar Arafath Udhuman, Alakesh Chandra Mandal

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsnot available
Fundersnot available
KeywordsFreestreamBoundary layerEnhanced Data Rates for GSM EvolutionLayer (electronics)Materials scienceComputer scienceMechanicsPhysicsComposite materialArtificial intelligenceTurbulence

Abstract

fetched live from OpenAlex

Some initial observations from our ongoing study on the effect of leading-edge geometry and the associated pressure gradient on a flat plate boundary layer under the high level of freestream disturbances are reported here.Measurements were carried out in a low-speed wind tunnel using the particle image velocimetry (PIV) and the hotwire anemometry techniques.Freestream turbulence (FST) was generated by placing a turbulent generating grid at the entrance of the tunnel test section.Two flat plates with the same thickness but with different leading edge (LE) geometries, i.e. an asymmetrically modified super-elliptic (AMSE) leading edge and a super-elliptic (SE) leading edge were used.Trailing-edge flap was used to alter the pressure distribution around the leading edges.Experiments were carried out for two different freestream cases, i.e. without and with a contoured wall at the top of the test section above the plate.To refer in the text, we call the flow to be zero pressure gradient (ZPG) flow in the absence of the contoured wall inside the test section.Under ZPG flow, pressure distributions around the leading edges for flap deflections at 0° and 4° were found from the velocity measurements in the freestream; anti-clockwise flap deflection with respect to the streamwise direction is considered to be positive.For a low aspect ratio leading edge, SE, a strong pressure suction peak is found to exist near the leading edge for 0° flap deflection, whereas the suction peak value is considerably reduced for 4° flap deflection.The streamwise extent of the non-zero pressure gradient region over the working surface of the plate also reduces compared to 0° flap deflection.As AMSE leading edge is an aerodynamically optimized configuration [1], no appreciable pressure suction peak is observed even without flap deflection.Measurements in the spanwise plane of the boundary layer under the high level of FST were conducted using the timeresolved PIV (TR-PIV) technique.The results show high-and low-speed streaks inside the boundary layer for the AMSE leading edge at 0° flap deflection, consistent with previous studies [e.g.2-4].However, by changing the leading edge geometry to SE, we find that the flow is populated with lambda-shaped structures instead of high-and low-speed streaks.Similar structures are also reported for wake-induced boundary layer transition [5,6].For this leading edge at 0° flap deflection, a strong suction peak is found to occur around the leading edge which leads to these lambda-shaped structures.However, the positive flap deflection for this leading edge eliminates the suction peak around the leading edge which results in the disappearance of these structures leading to the dominance of streaky structures.In order to confirm that the sharp pressure drop near leading edge plays a key role in the generation of such structures, an adverse pressure gradient is intentionally imposed on the flow using a contoured wall at the top in the test section.Measurements in the spanwise plane of the flat plate with AMSE leading edge are then carried out under this condition.The flow which was populated with streaky structures without the contoured wall at 0° flap deflection, is found to be populated again similar lambda-shaped structures with the presence of the contoured wall at 0° flap deflection.However, the positive flap deflection again eliminates these structures and the flow is dominated by the streaky structures.These observations clearly indicate that the pressure distribution around the leading edge determines the development of flow structures downstream of the leading edge of a flat plate.

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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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.003
GPT teacher head0.190
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 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
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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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