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LDA Measurement in Cylindrical Containers without Using Planar Secondary Units

2012· article· en· W1984494312 on OpenAlexaff
A. S. Ramamurthy, Rahim Tadayon, Mustafa Al kayed

Bibliographic record

VenueJournal of Hydraulic Engineering · 2012
Typearticle
Languageen
FieldEngineering
TopicCyclone Separators and Fluid Dynamics
Canadian institutionsConcordia University
Fundersnot available
KeywordsHydrocycloneTurbulenceLaser Doppler velocimetryOpticsReynolds stressMechanicsFlow (mathematics)Measure (data warehouse)Particle image velocimetryShear stressPhysicsPlanarReynolds numberGeometryMathematics

Abstract

fetched live from OpenAlex

To measure velocity components using the laser Doppler anemometry (LDA)in a cylindrical surface, as in a hydrocyclone, traditionally, one encloses the top circular tube of the hydrocyclone with a flat surface box to minimize the refraction effects of laser beams caused by the curved solid walls. In this brief study, an alternative procedure is suggested to reorient the laser beams to measure the mean and fluctuation velocity components. Adopting the beam orientation suggested—at a single point in the flow field—the axial and circumferential mean velocity components, along with the corresponding turbulent normal and shear stress components, can be determined. Test results confirm that the proposed method is valid to get data related to the mean velocities and the Reynolds stresses at a single point in the flow field of a hydrocyclone. The suggested procedure with slight modifications can be applied to measure velocities in the flow field formed by other circular surfaces, such as cones.

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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.022
GPT teacher head0.221
Teacher spread0.199 · 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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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