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Record W4380991811 · doi:10.3390/en16124751

Assessing Energy Performance and Environmental Impact of Low GWP Vapor Compression Chilled Water Systems

2023· article· en· W4380991811 on OpenAlexafffundabout
Rami Mansouri, Baby-Jean Robert Mungyeko Bisulandu, Adrian Ilinca

Bibliographic record

VenueEnergies · 2023
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec à RimouskiUniversité du Québec à Montréal
FundersUniversité du Québec à Rimouski
KeywordsRefrigerantVapor-compression refrigerationChillerEnvironmental scienceChilled waterRefrigerationAir conditioningGreenhouse gasGlobal-warming potentialEfficient energy useGlobal warmingWater vaporMontreal ProtocolProcess engineeringEnvironmental engineeringOzone layerOzoneClimate changeMeteorologyThermodynamicsEngineeringMechanical engineeringHeat exchanger

Abstract

fetched live from OpenAlex

The global concern regarding the environmental repercussions of refrigerants has escalated due to their adverse effects. These substances deplete the ozone layer and intensify the greenhouse effect. International agreements such as the Montreal and Kyoto Protocols and COP21 have imposed restrictions on refrigerants with high global warming potential (GWP) to address these issues. This study aims to explore the feasibility, energy efficiency, and environmental impact of utilizing the HFO (hydrofluoric-olefin) refrigerant R1234ze as a substitute for HFCs (hydrofluoric-carbon) (R134a, R407C, and R410A) and HCFCs (R22) in air-cooled vapor compression refrigeration and air conditioning systems. To determine their effectiveness, we evaluate the energy performance of various refrigerant operating cycles across a wide range of ambient and evaporating temperatures. Additionally, we conduct environmental impact analyses based on the total equivalent warming impact (TEWI) parameter calculated for commercially available chillers that utilize the fluids mentioned above. Our findings indicate that vapor compression chilled water systems employing R1234ze exhibit the highest performance coefficient and the lowest annual TEWI.

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 score0.203
Threshold uncertainty score0.251

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.007
GPT teacher head0.213
Teacher spread0.206 · 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

Citations7
Published2023
Admission routes3
Has abstractyes

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