MétaCan
Menu
Back to cohort
Record W1995822172 · doi:10.1115/gt2014-25691

Computational and Experimental Study of the Effect of Inlet Swirl on Mixing Mechanisms in an Axisymmetric Lobed Mixer

2014· article· en· W1995822172 on OpenAlexaff
Joshua Brinkerhoff, M. I. Yaras

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsCarleton University
Fundersnot available
KeywordsInflowMechanicsTurbulenceInstabilityVorticityInletRotational symmetryMaterials scienceVortexPhysicsGeology

Abstract

fetched live from OpenAlex

The effect of circumferential inflow swirl on the instability of the shear layer formed between the core and bypass flows discharged from an axisymmetric twelve-lobed mixer is studied through a combined experimental and computational investigation. A series of unsteady Navier-Stokes simulations are performed with 0 and 31 degrees of circumferential swirl specified in the core stream of the lobed mixer. Comparison of the axial- and swirling-inflow cases highlights the effect of swirl on the instability-driven transient flow structures that develop within and downstream of the lobed mixer. Medium- and large-scale unsteady motions are captured by the fine spatial and temporal resolution of the unsteady Navier-Stokes simulations. The simulations are validated against four-wire thermal anemometry measurements in a scaled lobed-mixer wind-tunnel model with turbulent, swirling inflow conditions. The simulation results illustrate that while the axial-inflow case develops layers of streamwise vorticity uniformly along the lobe walls, the core flow in the swirling-inflow case separates from the suction side of the lobe wall near the lobe trough. Roll-up and axial stretching of the separated flow produces Λ-shaped vortical structures upstream of the discharge plane. The Λ-shaped structures interact with the shear layers discharged from the lobe trailing edge and accelerate the breakdown of the shear layer in the swirling-inflow case relative to the axial-inflow case. The extent of this interaction is shown to strongly affect the streamwise mixing rate of the flow downstream of the discharge plane.

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 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 score0.001
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 studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.213
Teacher spread0.209 · 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".

Quick stats

Citations1
Published2014
Admission routes1
Has abstractyes

Explore more

Same topicFluid Dynamics and Turbulent FlowsFrench-language works237,207