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Record W2007688073 · doi:10.1080/01457630701328197

Bounds on Two-Phase Frictional Pressure Gradient in Minichannels and Microchannels

2007· article· en· W2007688073 on OpenAlexafffund
Mohamed M. Awad, Yuri S. Muzychka

Bibliographic record

VenueHeat Transfer Engineering · 2007
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Boiling Studies
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaMemorial University of Newfoundland
KeywordsLaminar flowPressure gradientDimensionless quantityMechanicsMaterials scienceFlow (mathematics)ThermodynamicsPhase (matter)Pressure dropPhysics

Abstract

fetched live from OpenAlex

Simple rules are developed for obtaining rational bounds for two-phase frictional pressure gradient in minichannels and microchannels. The lower bound is based on the Ali et al. correlation for laminar-laminar flow. This correlation is based on the modification of simplified stratified flow model derived from the theoretical approach of Taitel and Dukler for the case of two-phase flow in a narrow channel. The upper bound is based on Chisholm correlation for laminar-laminar flow. The model is verified using published experimental data of two-phase frictional pressure gradient in circular and non-circular shapes. The published data include different working fluids such as air-water and nitrogen-water mixtures, as well as different channel diameters. The bounds models are also presented in a dimensionless form as two-phase frictional multiplier versus Lockhart-Martinelli parameter for different working fluids such as air-water mixture and nitrogen-water mixture. It is shown that the published data can be well bounded.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.011
GPT teacher head0.242
Teacher spread0.230 · 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 source (direct Gemma or distilled Codex), 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

Citations14
Published2007
Admission routes2
Has abstractyes

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