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Analysis of refrigerants used in supermarket commercial equipment and the potential for increasing energy efficiency and reducing environmental impact

2024· article· en· W4401366428 on OpenAlex
Volodymyr Polukhin, Olga Yakovleva

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTechnology audit and production reserves · 2024
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal ProtocolRefrigerantEnvironmental scienceRefrigerationCoefficient of performanceGlobal-warming potentialOzone layerWaste managementGreenhouse gasEnvironmental protectionEngineeringMeteorologyOzoneGeographyHeat exchangerMechanical engineeringEcology

Abstract

fetched live from OpenAlex

Refrigerants used in the commercial equipment of supermarkets are the object of the research. The Montreal Protocol calls for a complete phase-out of hydrochlorofluorocarbons (HCFCs) by 2030, and the Kigali Amendment regulates the use of hydrofluorocarbons (HFCs) from 2019. Developed countries began phasing out HFC use in 2019, while developing countries plan to freeze HFC consumption from 2024. These global efforts are aimed at reducing the depletion of the ozone layer and combating climate change. The number of supermarkets in the world varies greatly: in Europe they number from 110 thousand to 115 thousand, and in China – from 65 thousand to 70 thousand, which reflects various needs in refrigeration equipment. Stringent environmental regulations are forcing the commercial refrigeration sector to remain globally competitive. Modernization of supermarkets using natural refrigerants is important for solving emerging challenges. The results of the study show significant improvements in energy efficiency ratio (EER) and coefficient of performance (COP) when using a mixture of hydrocarbons (R290: 85 %, R600a: 15 %) compared to traditional refrigerants R404a, R449a and R502. Specifically, at the evaporation temperature of Tevap=–10 °C, EER increased by 38–44 % and COP by 26–31 % compared to R404a and R449a, respectively. At Tevap=–25 °C, EER increased by 17–34 % and COP by 2–22 % compared to R404a and R449a. Additionally, compared to R502, the hydrocarbon blend showed a 38–44 % increase in EER and 28–31 % COP at Tevap=–10 °C, and a 17–34 % increase in EER and 5–22 % COP at Tevap=–25 °C. These results highlight the advantages of the hydrocarbon mixture at different evaporation temperatures, indicating its potential to improve energy efficiency in refrigeration applications. The obtained data suggest the possibility of a wider application of the mixture of hydrocarbons in commercial refrigeration plants, offering both improved performance and compliance with safety regulations.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.546
Threshold uncertainty score0.302

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.007
GPT teacher head0.239
Teacher spread0.232 · 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