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Record W2792568197 · doi:10.4236/ojapps.2018.82005

Experimental Investigation of the Cooling Capacity of Gaseous Carbon Dioxide in Free Jet Expansion for Use in Portable Air-Cooling Systems

2018· article· en· W2792568197 on OpenAlexafffund
Chady Al Sayed, Ludwig Vinches, Stéphane Hallé

Bibliographic record

VenueOpen Journal of Applied Sciences · 2018
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsÉcole de Technologie Supérieure
FundersFonds de recherche du Québec – Nature et technologies
KeywordsCooling capacityBody orificePressure dropMechanicsThermodynamicsDrop (telecommunication)Free coolingEvaporationMaterials scienceJet (fluid)Carbon dioxideChemistryWater coolingMechanical engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

This paper investigates the possibility of using the free expansion of gaseous CO2 in portable air-cooling systems. The cooling capacity of the gaseous CO2 free jet expansion was calculated using three different approaches and the results showed that the simplified calculations would give approximated cooling values with an 11.6% maximum error. The mass flow rate, upstream pressure and cooling capacity of the gaseous CO2 decreased with time. A maximum 48.5 watts of cooling was recorded at minute 4 and a minimum value of 10.4 watts at the end of the test. The drop in cooling capacity is due to the evaporation of the liquid CO2 inside the small cylinder which cools the two-phase CO2 mixture and causes a pressure drop (from 6 MPa to 2.97 MPa), which also affects the mass flow rate of gaseous CO2 exiting the orifice (from 0.56 g/s to 0.24 g/s). If this cooling technique is to be considered in portable compact-cooling systems, the mass, pressure and cooling capacity drop with time must be solved. One of the solutions could be to cover the cylinder with a heating coat to compensate for the heat absorbed by the evaporation of the liquid CO2.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.045
GPT teacher head0.259
Teacher spread0.214 · 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 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

Citations4
Published2018
Admission routes2
Has abstractyes

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