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The prospect of using ozone-safe refrigerants with low global warming potential in scroll compressors. Part 1

2021· article· en· W4200611966 on OpenAlexaboutno aff
V. A. Pronin, A. V. Kovanov, E. A. Kalashnikova, V. A. Tsvetkov

Bibliographic record

VenueOmsk Scientific Bulletin Series Aviation-Rocket and Power Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsRefrigerantScroll compressorGas compressorMontreal ProtocolGlobal-warming potentialScrollGlobal warmingRefrigerationEnvironmental scienceProcess engineeringOzone layerComputer scienceEngineeringGreenhouse gasOzoneMechanical engineeringChemistryClimate changeEcology

Abstract

fetched live from OpenAlex

The Montreal Protocol and the Kigali Amendment have determined the need and deadlines of the replacement of hydro fluorinated refrigerants. Substances of natural origin with a low global warming potential are becoming an alternative to hydrofluorocarbons that are being withdrawn from circulation. Such an alternative corrects the vector of development of refrigeration equipment and entails the need to adapt or create new models of equipment taking into account the excellent properties of new refrigerants. However, the consumer’s choice is still based on the efficiency, cost and reliability of the equipment. Having studied the possibility of using new refrigerants, in the fields of using a scroll compressor, from the point of view of the operational properties of substances, we also noted some aspects of the influence of their thermodynamic and thermophysical properties on the working processes and design of compressor elements. Thus, we present a comparative analysis of the practical application and further prospects for the using of refrigerants in a scroll compressor, highlighting the current directions of studying this issue.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.541
Threshold uncertainty score0.659

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.005
GPT teacher head0.187
Teacher spread0.183 · 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 designSimulation or modeling
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

Citations5
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueOmsk Scientific Bulletin Series Aviation-Rocket and Power EngineeringSame topicRefrigeration and Air Conditioning TechnologiesFrench-language works237,207