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Record W2522170964 · doi:10.1115/gt2016-57875

Entrance Aspect Ratio Effect on S-Duct Inlet Performance at High-Subsonic Flow

2016· article· en· W2522170964 on OpenAlexaff
Asad Asghar, Robert Stowe, W. Allan, Derrick Alexander

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsMartec (Canada)Defence Research and Development CanadaRoyal Military College of Canada
Fundersnot available
KeywordsDuct (anatomy)Mach numberInletOverall pressure ratioNacelleStatic pressureMechanicsMaterials scienceTotal pressureAcousticsPhysicsEngineeringAerospace engineeringMechanical engineeringGas compressor

Abstract

fetched live from OpenAlex

This paper reports the internal performance evaluation of S-duct diffusers with different entrance aspect ratios as part of an ongoing parametric investigation of a generic S-duct inlet. The generic S-duct diffusers were a rectangular-entrance (aspect ratio 1.5 and 2.0) transitioning S-duct diffuser in high subsonic (Mach number > 0.8) flow. The test section was manufactured using rapid prototyping for facilitating the parametric investigation of the geometry. Streamwise static pressure and exit-plane total pressure were measured in a test-rig using surface pressure taps and a 5-probe rotating rake, respectively and the baseline and a variant was simulated through computational fluid dynamics. The investigation indicated the presence of streamwise and circumferential pressure gradients leading to a three dimensional flow in the S-duct diffuser and distortion at the exit plane. The static pressure recovery increased for the diffuser with higher aspect ratio. Total pressure losses and circumferential and radial distortions at the exit plane were higher than that of the podded nacelle type of inlet. The increase in the total pressure recovery was observed for the increase in the aspect ratio for the baseline area ratio (1.57) S-ducts, but without a clear trend for the other area ratio (1.8) ducts. The work represents the beginning of the development of a database for the performance of a particular type of generic inlet. This database will be useful for predicting the performance of aero-engines and air vehicles in high subsonic flight.

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 score0.121
Threshold uncertainty score0.709

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)0.0000.001

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 head0.170
Teacher spread0.167 · 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

Citations5
Published2016
Admission routes1
Has abstractyes

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