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Record W2766702800 · doi:10.1016/j.proeng.2017.10.094

Performance Research on Heat Pump Using Blends of R744 with Eco-friendly Working Fluid

2017· article· en· W2766702800 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

VenueProcedia Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsCarleton University
Fundersnot available
KeywordsCoefficient of performanceHeat pumpRefrigerantTranscritical cycleWorking fluidSuperheatingGas compressorThermodynamicsWork (physics)Materials scienceGlobal-warming potentialFreonEnvironmentally friendlyRefrigerationProcess engineeringNuclear engineeringEnvironmental scienceHeat exchangerEngineering

Abstract

fetched live from OpenAlex

In order to protect the environment and save energy, new refrigerants with zero ozone depleting potential, low global warming potential have been investigated by more and more researches to substitute HCFCs/ HFCs for eco-friendly working fluid. Among alternatives, non-azeotropic mixtures are becoming the more potential and important candidates. In this research, the transcritical system performances of water heater heat pump using R744/DME (dimethyl ether) binary mixture as working fluid were theoretically analyzed. On mix R744 with DME in a smaller mass fraction, both the optimum heat rejection pressure and the heating coefficient of performance (COP) are decreased. The mean relative reduction rate of optimum heat rejection pressure, however, is greater than that of heating COP. Also, the influence of superheat degree at the inlet of compressor upon the optimum heat rejection pressure and the heating COP is also discussed. The results show that the R744/DME can work as a promising alternative to replace with current widely-used Freons.

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 score0.181
Threshold uncertainty score0.609

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 head0.048
GPT teacher head0.284
Teacher spread0.237 · 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