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Record W4225984889 · doi:10.1504/ijex.2022.122080

3D CFD modelling and exergy loss minimisation within a high-pressure vortex tube

2022· article· en· W4225984889 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Exergy · 2022
Typearticle
Languageen
FieldEngineering
TopicRanque-Hilsch vortex tube
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsVortex tubeExergyMechanicsVortexComputational fluid dynamicsInletMass fractionThermodynamicsExergy efficiencyTube (container)Materials scienceMass flow ratePhysicsMechanical engineeringComposite materialEngineering

Abstract

fetched live from OpenAlex

In the present study, 3D CFD simulation of a vortex tube at high operating pressure is investigated. The impact of inlet pressure and cold mass fraction is investigated in terms of the exergy losses within the vortex tube. The results show that the minimum exergy losses occur at cold mass fraction equals 0.5, meanwhile, the exergy efficiency achieves its maximum at cold mass fraction equals 0.9. It is illustrated that friction has a major impact on entropy generation rate near the wall and at the centre of the vortex tube.

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.

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 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 score0.043
Threshold uncertainty score0.743

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)0.0000.000

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 head0.008
GPT teacher head0.206
Teacher spread0.198 · 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