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Record W3200693171 · doi:10.32393/csme.2021.179

Modélisation Thermodynamique Et Analyse Exergétique D’Un Tube Vortex Non Adiabatique Utilisant Un Fluide Naturel

2021· article· fr· W3200693171 on OpenAlexaff
N.D. Doiron, Samuelle St-Onge, Mohammed Khennich

Bibliographic record

VenueProgress in Canadian Mechanical Engineering. Volume 4 · 2021
Typearticle
Languagefr
FieldEngineering
TopicFluid Dynamics and Vibration Analysis
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsPhysicsVortexHumanitiesThermodynamicsArt

Abstract

fetched live from OpenAlex

The different definitions of exergy efficiency (RE), which have been proposed in the past for the thermodynamic evaluation of expansion and compression devices, operating above and through ambient temperature are discussed. The comparison between these efficiencies is illustrated. An expression for (RE) based on the concept of transit exergy is presented. This concept allows the quantitative and unambiguous definition of two exergy measurements: the exergy produced and the exergy consumed. The development of these (RE) in the case of a non-adiabatic vortex tube with dimensionless thermal conductivity, integrated with a compressor above or through ambient temperature is presented. The methods of calculating the transit exergy are described. Analysis based on the mentioned measurements, combined with traditional exergy loss analysis, identifies the most important factors affecting the thermodynamic performance of compression and expansion in a non-adiabatic vortex tube. It was obtained that the use of a natural reel fluid (CO2) compared to an ideal gas (Air) increases the transit (RE) by 31.5% and decreases the exergy losses by 37.3% under the same operating conditions of the two fluids in the system with the same COP.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.681
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.005
GPT teacher head0.217
Teacher spread0.212 · 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 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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueProgress in Canadian Mechanical Engineering. Volume 4Same topicFluid Dynamics and Vibration AnalysisFrench-language works237,207