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Record W2991163037 · doi:10.1115/omae2019-96311

CFD Simulation of Two-Phase Vertical Annular Flow in Both Upward and Downward Direction in a Small Pipe

2019· article· en· W2991163037 on OpenAlexaff
Ekhwaiter Abobaker, Abadelhalim Elsanoose, J. Shirokoff, Mohammad Azizur Rahman

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMechanicsVolume of fluid methodComputational fluid dynamicsTurbulencePressure dropMaterials scienceFlow (mathematics)Two-phase flowMultiphase flowPressure gradientReynolds numberVolumetric flow rateFluentGeologyPhysics

Abstract

fetched live from OpenAlex

Abstract Computational fluid dynamics (CFD) simulation is presented to investigate the annular flow behavior in the vertical pipe by using ANSYS Fluent platform 17.2. The study was analyzed complex behavior of annular flow in two cases (upward and downward flow) for different air superficial velocities and range of Reynolds number for water, in order to obtain the effect of orientation flow and increasing superficial gas and liquid velocities on the base film, mean disturbance wave thickness, the average longitudinal size of disturbance wave as well as pressure gradient. For multiphase flow model, the volume of fluid method (VOF) for two-phase flow modelling was used and coupled with RNG k-ε turbulence model to predict fully annular flow structures in the upward and downward flow direction. From CFD simulation results, it is clear to see how increases in air velocity result in reductions in film thickness and increase in pressure gradient. Additionally, the results showed monotonic enhancement of film thickness occurring in tandem with increases in the liquid flow rate. However, due to the effect of gravitational force and interfacial friction, the film thickness and pressure gradient are slightly larger for the upward flow than for the downward flow. The results agree with the recent experimental data that studied the annular flow behavior and pressure drop in the upward and downward flow direction. This study will be very helpful in understanding multiphase flow behavior in natural gas wells.

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 score0.038
Threshold uncertainty score0.279

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 head0.007
GPT teacher head0.230
Teacher spread0.223 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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