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Thermodynamic assessment, screening and trade-offs in alternative working fluids selection for refrigeration, heat pumping and organic Rankine cycles

2019· article· en· W2989951195 on OpenAlexaboutno aff
В.В. Митропов, O. B. Tsvetkov, Yu.A. Laptev, Alexander Babich

Bibliographic record

VenueJournal of Physics Conference Series · 2019
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsRefrigerantGlobal-warming potentialChlorofluorocarbonRefrigerationFlammable liquidFlammabilityMontreal ProtocolEnvironmental scienceGlobal warmingDegree RankineOrganic Rankine cycleThermodynamicsOzone depletionVapor-compression refrigerationFreonProcess engineeringWaste managementChemistryOzone layerOzoneWaste heatEngineeringOrganic chemistryGas compressorGreenhouse gasClimate changeEcologyHeat exchanger

Abstract

fetched live from OpenAlex

Abstract Global warming and ozone depletion are leading effects attaching the consideration of environmental organizations. Conversion to alternative hydrofluorocarbons (HFC) refrigerants without chlorine atoms progressed over the last two decades. However recently because of the significant global warming impact of HFCs the hydrofluoroolefins (HFOs) were proposed as new generation alternative refrigerants. This article discussed fluorinated propene based isomers, summarizes refrigerant numbering scheme, flammability, fundamental parameters and thermodynamic properties of isomers containing five-, four- and three-fluorine atoms respectively. In the present study evaluated the refrigerant performance in an idealized vapor compression refrigeration cycle. Presented HFC and HFO blends as non-flammable refrigerants with relatively low global warming potential values.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.531
Threshold uncertainty score0.425

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 communication0.0000.001
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 head0.017
GPT teacher head0.250
Teacher spread0.233 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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