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Record W6920725421 · doi:10.60692/dtvxr-hqb05

The Comparative Analysis of Alternative Refrigerants on Ship Refrigeration Systems

2023· article· en· W6920725421 on OpenAlexaboutno aff

Bibliographic record

VenueGreater South Information System · 2023
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsRefrigerantRefrigerationAir conditioningOzone layerMontreal Protocol

Abstract

fetched live from OpenAlex

The usage of CFC and HCFC gases, which are extensively used in ship refrigeration and air conditioning systems, has been restricted due to harmful effects on the ozone layer and global warming. Thus, the use of alternative refrigerants becomes a possible solution. In this study, the performance parameters, environmental and economic effects of the system for various refrigerants were analyzed comparatively for marine refrigeration systems. For this purpose, the refrigerants R407C, R1234yf, R245fa, R152a, R513a, R450a, R161, R453a, and R717 are investigated as alternatives to the most commonly used R22 and R134a refrigerants on board ships. The results show that the best alternatives -in terms of performance, environment and economy- for R22 are R717 (new) and R453A (drop-in) and for R134a are R717 (new) and R152a (drop-in). In addition, drop-in, retrofit or new system suitability of the analyzed refrigerants for replacement of R22 and R134a are presented.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.614

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 integrity0.0000.000
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 head0.059
GPT teacher head0.249
Teacher spread0.190 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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