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Record W2083098174 · doi:10.1115/icmm2005-75031

Assessment of Void Fraction Correlations for Adiabatic Two-Phase Flows in Microchannels

2005· article· en· W2083098174 on OpenAlexaff
Akimaro KAWAHARA, Michio SADATOMI, Masahiro Kawaji, Kazuya Okayama, Peter M.-Y. Chung

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAdiabatic processPorosityVoid (composites)Surface tensionMaterials scienceHydraulic diameterThermodynamicsMechanicsFraction (chemistry)HomogeneousTwo-phase flowAnalytical Chemistry (journal)ChemistryComposite materialChromatographyPhysicsFlow (mathematics)

Abstract

fetched live from OpenAlex

In this paper, firstly a review is presented on our previous study of void fraction for adiabatic gas-liquid two-phase flows in horizontal microchannels. Water/nitrogen gas and/or ethanol-water-solution/nitrogen gas were pumped through circular microchannels of 50, 75, 100, 176, 251 and 530 μm in diameter. The concentration of ethanol in water was varied to change the surface tension and the liquid viscosity. The void fraction data for the 50 to 100 μm diameter channels showed non-linear variation against a homogenous void fraction, but the data for 251 and 530 μm diameter channels varied linearly with the homogeneous void fraction. Secondly, the data have been compared with the predictions of various correlations usually applied to mini/micro-channels as well as conventional size channels. Since no correlation could predict well all of our data, a new correlation has been proposed based on our data. It was found that the calculated void fraction by the proposed correlation agreed with all the data within 0.1, irrespective of channel diameters and the liquid properties.Copyright © 2005 by ASME

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
Threshold uncertainty score1.000

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)0.0010.000

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 head0.031
GPT teacher head0.352
Teacher spread0.321 · 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.

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

Citations11
Published2005
Admission routes1
Has abstractyes

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