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Record W4381619376 · doi:10.11159/ffhmt23.179

Evaluating Two-Phase Flow Patterns in Airlift pumps Using Image Processing Technique

2023· article· en· W4381619376 on OpenAlexafffundvenue
Dana Fadlalla, Wael H. Ahmed, David Weales, Medhat Moussa

Bibliographic record

VenueProceedings of the ... International Conference on Fluid Flow, Heat and Mass Transfer · 2023
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsUniversity of Guelph
FundersOntario Agri-Food Innovation AllianceOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsAirliftComputer scienceImage processingFlow (mathematics)Two-phase flowEngineering drawingImage (mathematics)Computer visionEngineeringMechanicsPhysicsBioreactorChemistry

Abstract

fetched live from OpenAlex

One of the most important criteria in determining the performance of airlift pumps is to determine the two-phase flow characteristics in the pump riser.These include the determining the average void fraction and both the slug velocity and frequency of the two-phase flow in the vertical pipe.In the current work, three image processing methods were examined to describe the two-phase hydrodynamic parameters as they relate to the pump performance.Experiments were carried out using Xanthan Gum-water solutions with varying XG concentrations between 0.05-0.25 wt% in a pump riser of 31.75 mm in diameter.High-speed camera with 3000 f/s capabilities was used to obtain the flow visualisation images for the two-phase flow distribution downstream of the pump injector.The preliminary results suggested that the image processing technique using background subtraction algorithm can be an effective approach in evaluating the flow structure and consequently can be used to determine void fraction and slug characteristics.

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)0.001
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 score0.450
Threshold uncertainty score0.753

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.048
GPT teacher head0.326
Teacher spread0.278 · 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

Citations0
Published2023
Admission routes3
Has abstractyes

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Same venueProceedings of the ... International Conference on Fluid Flow, Heat and Mass TransferSame topicOil and Gas Production TechniquesFrench-language works237,207