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Record W2777293346 · doi:10.1063/1.5018523

CFD simulation of slurry flow in annular pipelines

2017· article· en· W2777293346 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

VenueAIP conference proceedings · 2017
Typearticle
Languageen
FieldEngineering
TopicCyclone Separators and Fluid Dynamics
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsSlurryPressure dropMechanicsTurbulenceMaterials scienceComputational fluid dynamicsPressure gradientFlow (mathematics)Reynolds numberComposite materialPhysics

Abstract

fetched live from OpenAlex

Three-dimensional CFD modeling of two-phase slurry flows is demonstrated in this paper. The flow domain consists of a vertically oriented annular pipe with outer and inner diameter of 0.125 m and 0.025 m, respectively. A mixture velocity range of 0.0738–0.197 m/s and overall volumetric concentration range of 0.8%–1.8% with 0.23 mm grain size (dp) are used for the simulation. Eulerian model with Reynolds Stress Model (RSM) for turbulence closure is adopted to analyze the monodispersed sand particles of varying granular diameters. The objective of this work is to study the slurry flow using CFD simulation and validating the simulation with experimental studies available in the literature. The simulated pressure losses are found to be in good agreement with experimental results at different conditions. Pressure drop per meter or pressure gradient increases with flow velocity of mixture but after a peak point pressure gradient decreases with the increasing velocity. These phenomena in vertical annular flow and its reasons are described in this paper. Effects of efflux solid concentration of slurry on pressure gradient is also studied.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.858
Threshold uncertainty score0.505

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 head0.017
GPT teacher head0.254
Teacher spread0.237 · 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