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Record W2012242864 · doi:10.1115/ht-fed2004-56684

Study of Particulate Flow in the Impeller of a Slurry Pump Using PIV

2004· article· en· W2012242864 on OpenAlexfundno aff
M. Mehta, Jaikrishnan R. Kadambi, Sudeep Sastry, John M. Sankovic, Mark P. Wernet, Graeme Addie, Robert Visintainer

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsnot available
FundersGlobal Institute for Water Security, University of Saskatchewan
KeywordsImpellerCentrifugal pumpParticle image velocimetrySlurryMaterials scienceSuctionMechanicsParticle (ecology)Flow (mathematics)Blade (archaeology)Composite materialMechanical engineeringGeologyEngineeringTurbulencePhysics

Abstract

fetched live from OpenAlex

Particle Image Velocimetry (PIV) technique in conjunction with refractive index matching was successfully utilized to investigate the velocities of the slurry particles in the impeller of a centrifugal slurry pump. Tests were performed in an optically clear centrifugal slurry pump at speeds of 725 rpm and 1000 rpm using a slurry made up of sodium iodide solution as the working fluid and glass beads (500μm mean diameter) as solid particles at volumetric concentrations of 1%,2%, and 3%. In the intra blade region of the impeller, the highest particle velocities were obtained on the suction side of the blade and in the blade trailing edge region as the blade sweeps through and velocity magnitude increases with the pump speed. But this magnitude was less than that of circumferential velocity of the blade tip. Relative velocity plots show that flow separation takes place on the suction side of the blade in the region below the blade tip for clear fluid flow conditions. This was expected as the pump is made to operate with a slurry and not a single-phase liquid. At higher pump speeds and particle volumetric concentrations, a marked improvement in the slurry flow in the impeller is observed i.e., the recirculation zone decreases. This results from the centrifugal forces on the particles and its inertia at that speed. Also the slurry particles are pushed on the pressure side of the blade and slide along it which can result in frictional wear. These results are discussed in this paper.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.219
Threshold uncertainty score0.204

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 head0.022
GPT teacher head0.238
Teacher spread0.216 · 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 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

Citations9
Published2004
Admission routes1
Has abstractyes

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