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Record W2604789553 · doi:10.5281/zenodo.439656

Evaluation Of Vapour Compression Refrigeration System Using R407C And R507

2017· article· en· W2604789553 on OpenAlexaboutno aff
Rahul V. Ikhar, H.S. Farkade

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2017
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsRefrigerationVapor-compression refrigerationCompression (physics)Materials scienceProcess engineeringRefrigerantMechanical engineeringComposite materialEngineeringGas compressor

Abstract

fetched live from OpenAlex

<em>The existing refrigerant requirements are, system performance should not be compromised, refrigerant and lubrication interaction should be as required, it should be energy efficient, environment friendly etc. After Montreal protocol, use of refrigerants like CFC and HCFC banned because of high ozone depleting potential (ODP).</em><em> So there is need to find out a refrigerant which is environment friendly, such as HFC refrigerants as working fluids in refrigeration and air conditioning systems and which can be used long term substitute for existing refrigerants. The most important qualification for refrigerants is low ozone depleting potential (ODP).</em> <em>HFC refrigerants have suitable specifications such as non-flammability, stability, and similar vapour pressure to the refrigerant CFCs and HCFCs and zero ozone depleting potential (ODP) . They are used in many applications with safety of the leakage from the system also with these refrigerants it was found that, there was no need to change in the design of the refrigeration system. So we can look forward to HFC refrigerants. R407C and R507 are HFC refrigerants which are under study.</em>

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.880
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.000
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 head0.089
GPT teacher head0.286
Teacher spread0.197 · 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.

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

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)Same topicRefrigeration and Air Conditioning TechnologiesFrench-language works237,207