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Record W2150227445 · doi:10.1115/1.4030287

Experimental Investigation of Drag Reducing Fluid Flow in Annular Geometry Using Particle Image Velocimetry Technique

2015· article· en· W2150227445 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Fluids Engineering · 2015
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsParticle image velocimetryTurbulenceReynolds numberDragMechanicsPhysicsVorticityGeometryTurbulence kinetic energyReynolds stressDrag coefficientClassical mechanicsMaterials scienceMathematicsVortex

Abstract

fetched live from OpenAlex

Fully developed turbulent flow of drag reducing fluids through a horizontal flow loop with concentric annular geometry was investigated using the particle image velocimetry (PIV) technique. Experiments were conducted at solvent Reynolds numbers ranged from 38,700 to 56,400. Axial mean velocity profile was found to be following the universal wall law close to the wall (i.e., y+ < 10), but it deviated from log law results with an increased slope in the logarithmic zone (i.e., y+ > 30). The study was also focused on turbulence statistics such as near wall Reynolds stress distribution, axial and radial velocity fluctuations, vorticity and turbulent kinetic energy budget.

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.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.273
Threshold uncertainty score0.757

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.016
GPT teacher head0.248
Teacher spread0.232 · 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