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Record W2497399624 · doi:10.1002/cjce.22617

Characteristics of water holdup for oil and water mixture flows in horizontal, vertical, and inclined pipes

2016· article· en· W2497399624 on OpenAlexvenueno aff
Jing‐yu Xu, Shuo Liu, Dong Zhang, Jian Zhang

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsFroude numberInclination angleMechanicsFlow (mathematics)SlippageGeologyWork (physics)Environmental scienceGeometryMaterials scienceMathematicsPhysicsThermodynamics

Abstract

fetched live from OpenAlex

Abstract In this work, the water holdup and slippage for oil and water mixture flows in horizontal, vertical, and inclined pipes have been investigated. A large group of experimental data was collected from 21 different sources covering the whole range of inclination angles from −90° to 90° to reveal the holdup characteristics and develop the drift velocity model. The results show that in horizontal flows the water holdup is dependent to the flow pattern, and yet in vertical flows the water holdup is similar to the input one and the flow direction shows a few influences on the holdup. In inclined flows, the Froude numbers are relatively independent of inclination angles when the angles are greater than 30°. Therefore, the changes of water holdup in the pipe with small inclination angles are more severe than those with large inclination angles. In addition, a satisfactory agreement between predicted and experimental holdups substantiates the general validity of the proposed drift velocity correlation for oil and water flows, especially for those with large inclination angles.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.212

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 head0.004
GPT teacher head0.161
Teacher spread0.157 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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