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Record W2076265229 · doi:10.1115/pvp2011-57918

Determination of Flow Structure in a Tube Array by Particle Image Velocimetry

2011· article· en· W2076265229 on OpenAlexaff
Njuki Mureithi, Claude Masabarakiza

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsParticle image velocimetryTurbulenceMechanicsVelocimetryTwo-phase flowParticle tracking velocimetryOpen-channel flowFlow (mathematics)Vector fieldBubbleFlow velocityFlow measurementMaterials scienceOpticsPhysics

Abstract

fetched live from OpenAlex

Particle Image Velocimetry (PIV) presents a possible approach to measuring two-phase flow parameters over a large area, leading to a snap shot of flow behavior in complex geometries such as tube bundles. Tests have been conducted in a 2m long wavy wall channel simulating the open lane within a rotated triangular array. The results show that liquid phase PIV measurements must be limited to very low void fractions. On the other hand, much information can be gained from the gas phase data. The details of the flow structure within the array are revealed. Current measurements, performed in the bubbly flow regime, show that even in this regime, the flow structure is significantly non-uniform and complex. Bubble diameters have been found to be strongly dependent on flow velocity; the effect of turbulence shear at high flow rates breaking up the bubbles to smaller sizes. The PIV measurements yield the complete averaged velocity vector field in the measurement region. The velocity profiles across the measurement section are also obtained. The non-uniform profiles show the challenges associated with attempts to estimate average void fractions and slip ratios in the array.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score0.198

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)0.0000.000

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 head0.181
Teacher spread0.176 · 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 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

Citations2
Published2011
Admission routes1
Has abstractyes

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