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Record W3002661950

Experimental Investigation Of One Ton Vapour Compression Refrigeration R-12 Refrigerate with Alternative ECO Friendly Refrigerants R410. R-413a And R-423a

2019· article· en· W3002661950 on OpenAlexaboutno aff
Pradeep Kumar Singh, Sachin Baraskar, Anil Verma

Bibliographic record

VenueInternational journal of advance research and innovative ideas in education · 2019
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsRefrigerantRefrigerationMontreal ProtocolEnvironmentally friendlyOzone layerEnvironmental scienceWaste managementProcess engineeringChemistryEngineeringGas compressorMechanical engineeringOrganic chemistryOzone
DOInot available

Abstract

fetched live from OpenAlex

The Montreal Protocol has sealed the use of Halogenated Hydrocarbons; Keeping in view they affect the environment in the form of Ozone layer depletion and Global warming. Thus one of the major thrust areas is to identify substitute of Halogenated Hydrocarbons, especially CFCs. The substitute refrigerant should be eco-friendly, chemically stable and compatible with existing refrigeration systems with transport and thermal properties similar to or better than CFCs. Since the refrigeration system use CFC- 12 as refrigerant universally, the search for a suitable alternative for CFC-12 is inevitable.HFC-134a is currently the leading alternative to CFC-12. Other promising substitutes are R-423as a binary mixture of R-227ea & R- 413a ternary mixture of R-134a, R-218 andR-600a. In this thesis, performance evaluation of eco-friendly alternate refrigerant R-134a, R-413a & R-423a for replacing CFC12 has been done and a suitable alternative refrigerant for retrofitting has been identified.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.544

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.024
GPT teacher head0.351
Teacher spread0.326 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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