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Record W2049372096 · doi:10.1002/htj.20339

Performance variation of an R22 window air conditioner retrofitted with a HFC/HC refrigerant mixture under different ambient conditions over a range of charge quantities

2011· article· en· W2049372096 on OpenAlexaboutno aff
M. Herbert Raj, D. Mohan Lal

Bibliographic record

VenueHeat Transfer-Asian Research · 2011
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsnot available
FundersDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsRefrigerantPsychrometricsWater chillerAir conditioningThermodynamicsMaterials scienceCharge (physics)Range (aeronautics)OverchargeEnvironmental scienceBattery (electricity)Composite materialPhysicsHeat exchanger

Abstract

fetched live from OpenAlex

Abstract R22 has been generally accepted as the most suitable refrigerant for air conditioners, due to its favorable thermodynamic properties. However, R22 is a controlled substance under the Montreal protocol. M20 is a HFC/HC refrigerant mixture that can be used as a substitute for R22. This paper presents experimental investigation on the performance comparison of a window air conditioner operated with the M20 tested under different refrigerant charge levels and outdoor conditions against that with R22. Experiments were conducted in accordance with BIS procedure in a psychrometric test facility. Refrigerant charge in the air conditioner was systematically varied from 900 to 1600 g in steps of 50 g for R22 and 697 to 1279 g in steps of 39 g [equivalent to 50 g of R22] for the M20. At each charge levels, the outdoor room conditions were changed in accordance with BIS standards. It is observed that R22 is more sensitive to deviations in charge levels as compared to the M20. A decrease in charge level of about 7% reduced the system refrigerating capacity by 11.3% with R22 while with the M20 refrigerant mixture it reduces by 6.9% only. Similarly an overcharge by 7% reduces the refrigerating capacity of the system by 13.8% with R22 while with M20 it reduces by 6.5% only. Thus M20 is less sensitive to charge deviations. © 2011 Wiley Periodicals, Inc. Heat Trans Asian Res; Published online in Wiley Online Library ( wileyonlinelibrary.com/journal/htj ). DOI 10.1002/htj.20339

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.580
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.276
Teacher spread0.231 · 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

Citations9
Published2011
Admission routes1
Has abstractyes

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