MétaCan
Menu
← Back to cohort
Record W4407413035 · doi:10.2514/6.2025-2221

Linear Stochastic Estimation of the Turbulent Field Parallel to the Wall in a Three-Dimensional Wall Jet

2025· article· en· W4407413035 on OpenAlexaff
Bonnie Sim, Joseph W. Hall

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsTurbulenceJet (fluid)MechanicsPhysicsField (mathematics)Statistical physicsMathematics

Abstract

fetched live from OpenAlex

The turbulent flow field in a three-dimensional wall jet with Reynolds number of Re= 134,000 was investigated using 89 simultaneous measurement of the fluctuating wall pressure and synchronized Particle Image Velocimetry (PIV) measurements in the x-z plane (parallel to the wall and across the jet) at 0.5D away from the wall. The measurements were focused on the near to intermediate field of the wall from the nozzle exit to x/D = 18. Linear Stochastic Estimation (LSE) was used to estimate the instantaneous velocity in the x-z plane of the wall jet. The velocity estimates reveal the flow is dominated by chevron like structures that are responsible for lateral flapping in the wall jet. The chevron-like structures grow spatially larger with downstream development. The legs of these chevrons are associated with the large instantaneous alternating positive and negative lateral fluctuations that cause rapid lateral growth in the wall jet. These chevron structures grow rapidly after the collapse of the potential core and have a slower convection rate than those noted in the near field of the jet.

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 score0.002
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 studies0.0000.000
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 head0.217
Teacher spread0.210 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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