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Numerical Studies on R22 Refrigerant Compressor Using Environment Friendly Working Fluids

2014· article· en· W2050817837 on OpenAlexaboutno aff
K.G. Sai Shreenaath, Jigar Golecha, L. Bruno Augustin, M. Suresh

Bibliographic record

VenueApplied Mechanics and Materials · 2014
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsRefrigerantChlorofluorocarbonGas compressorRefrigerationEvaporatorCondenser (optics)Air conditioningIsobutaneEnvironmental scienceVapor-compression refrigerationWorking fluidWork (physics)Montreal ProtocolEngineeringProcess engineeringWaste managementOzone layerMechanical engineeringChemistryOzone

Abstract

fetched live from OpenAlex

Vapour compression refrigeration is the most widely used method in domestic and commercial air conditioning and refrigeration systems. R22 (difluoromonochloromethane) is the most widely used HCFC (hydro chlorofluorocarbon) refrigerant in residential, commercial, industrial and transport cooling systems. Montreal protocol in 1987 banned the use of CFCs (chlorofluorocarbon) due to their adverse impact on the environment causing ozone depletion and global warming. HCFCs are also being phased out, though they are less destructive than CFCs. The present work explores compressor performance using alternate environment friendly working fluids so that R22 can be replaced in future. The refrigerants used for the studies are R134a (tetrafluoroethane), R290 (propane) and R600a (isobutane). Compressor performance is analysed by varying refrigerant mass flow rate, evaporator and condenser temperatures and studying their effect on compressor size, power and discharge temperature. A numerical simulation code has been developed in MATLAB using refrigerant properties taken from REFPROP.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.444
Threshold uncertainty score0.569

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 head0.025
GPT teacher head0.231
Teacher spread0.207 · 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.

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

Citations0
Published2014
Admission routes1
Has abstractyes

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