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Record W4389584915 · doi:10.17118/11143/21002

Thermodynamic paths along streamlines of a single-phase transcritical CO2vortex tube

2023· article· en· W4389584915 on OpenAlexafffund
Raphaël Oberti, Sébastien Poncet

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRanque-Hilsch vortex tube
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaAlliance de recherche numérique du CanadaNatural Resources CanadaHydro-QuébecUniversité de Sherbrooke
KeywordsStreamlines, streaklines, and pathlinesVortex tubeTranscritical cycleTube (container)MechanicsVortexThermodynamicsMaterials sciencePhysicsHeat exchangerHeat pump

Abstract

fetched live from OpenAlex

Abstract: The Ranque-Hilsch vortex tube is at the center of a renewed interest as a robust expansion device and a useful energy supply for transcritical CO2 vapor compression systems. This paper gives insights into thermodynamic paths along streamlines in a transcritical CO2 vortex tube employing computational fluid dynamics (CFD). A pressure-based coupled solver along with a low-Reynolds number turbulence model and the Span-Wagner equation of state constitutes the present numerical framework. Transcritical expansions are carried out at several cold mass fractions and both outer and inner vortex flow streamlines are tracked in the pressure-specific volume and pressurespecific enthalpy diagrams. The results confirm that the transcritical CO2 vortex tube is the seat of energy and temperature separations but they are inverted. A correlation between the flow transcriticality and vortex tube temperature and energy separation inversions is observed.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.252
Teacher spread0.236 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

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