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Record W4251397238 · doi:10.36884/jafm.9.si2.25789

1D Steady-State Numerical Results for Critical Two-Phase Flow – Critical Location and Pressure Profiles

2016· article· en· W4251397238 on OpenAlexafffund
Stephen J. Martel, M. Dostie, Y. Mercadier

Bibliographic record

VenueJournal of Applied Fluid Mechanics · 2016
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsUniversité de SherbrookeHydro-Québec
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of CanadaChina Electronics Technology Group CorporationFonds Québécois de la Recherche sur la Nature et les TechnologiesUniversité de Sherbrooke
KeywordsMechanicsSteady state (chemistry)Flow (mathematics)Phase (matter)GeologyPhysicsChemistry

Abstract

fetched live from OpenAlex

The use of two-phase ejectors to improve refrigeration systems encounters today a great interest. However, modeling of such devices with low void fraction at the entrance of the motive nozzle, presents significant challenges. The choking conditions and the discontinuities appearing in a two-phase flow in a nozzle are not well documented and some works are needed to better anticipated flow behavior under these conditions. This paper presents a steady state two-phase flow model including new choking criterions for one-dimensional conservative systems. The present model is a two-fluid, one pressure model with thermal equilibrium and mechanical disequilibrium. As a first step, this model is used to study the flow in the motive nozzle of an ejector.

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)0.001
metaresearch head score (Gemma)0.002
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.009
GPT teacher head0.262
Teacher spread0.253 · 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

Citations0
Published2016
Admission routes2
Has abstractyes

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