MétaCan
Menu
← Back to cohort
Record W3119102753 · doi:10.1115/gt2020-14949

Penetration and Mixing Characteristics of Inclined Jets in Crossflow at Low Momentum Flux Ratios

2020· article· en· W3119102753 on OpenAlexaff
Rahul B. Vishwanath, Timothy M. Wabel, Adam M. Steinberg

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBoundary layerMechanicsJet (fluid)Penetration (warfare)Momentum (technical analysis)PerpendicularMaterials scienceBoundary layer thicknessFlux (metallurgy)Reynolds numberPenetration depthOpticsPhysicsGeometryTurbulence

Abstract

fetched live from OpenAlex

Abstract This study investigates the factors affecting low momentum jets that are injected at an angle relative to a crossflow stream, which is relevant to film-cooling technologies. Quantitative measurements of the jet fluid concentration were obtained based on planar laser induced fluorescence (PLIF) from acetone vapor that was seeded into the jet. The jets were injected at four different axial locations downstream of the leading edge of a flat plate, resulting in different boundary layer thicknesses at the injection location. At each location, the jet-to-crossflow momentum flux ratio was varied from 0.5–5. The jet centerline trajectories were affected not only by the momentum flux ratios, but also by the approaching crossflow boundary layer thickness, with the jets penetrating the least for the thickest boundary layers. Measurements of the jet fluid concentration along the jet centerline showed an exponential decay rate of −1.3 across all cases. However, the behavior in the immediate vicinity of the jet depended on the boundary layer thickness, with thicker boundary layers resulting in a slower decay. Hence, the concentration profiles were shifted relative to the injection point depending on the injector position on the plate. The concentration profiles perpendicular to the jet axis were self-similar when scaled with the profile half-width.

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: Bench or experimental · Consensus signal: Bench or experimental
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
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.008
GPT teacher head0.195
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 designBench or experimental
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
Published2020
Admission routes1
Has abstractyes

Explore more

Same topicFluid Dynamics and Turbulent Flows→French-language works237,207→