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Record W4389393313 · doi:10.3389/fenrg.2023.1293993

Analyzing the carbon dioxide emissions of R134a alternatives in water-cooled centrifugal chillers using the life cycle climate performance framework

2023· article· en· W4389393313 on OpenAlexaboutno aff
Michael O. Akinseloyin, C. Hall, Emily M. Stallbaumer-Cyr, Jordan A. Morrow, Melanie M. Derby

Bibliographic record

VenueFrontiers in Energy Research · 2023
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsnot available
FundersOffice of Naval ResearchKing Saud University
KeywordsChillerEnvironmental scienceGreenhouse gasRenewable energyLiquefied natural gasLife-cycle assessmentWaste managementEnvironmental engineeringFossil fuelEngineeringNatural gasThermodynamicsElectrical engineering

Abstract

fetched live from OpenAlex

Introduction: To reduce greenhouse gases, the Kigali Amendment to the Montreal Protocol seeks a phasedown of hydrofluorocarbons. R134a alternatives were analyzed for use in a water-cooled chiller: R450A, R513A, R516A, R1234ze (E), R515A, and R515B. Methods: A thermodynamic model of the chiller was employed to calculate compressor power, an input to the life cycle climate performance (LCCP) framework to estimate total equivalent carbon dioxide emissions, CO 2eq . Emissions were calculated for an 809 kW [230 Tons of refrigeration (RT) nameplate] water-cooled centrifugal chiller at constant cooling capacity using five power sources (i.e., coal, distillate fuel oil, natural gas, nuclear, and wind) for a median chiller lifetime of 27 years. Two chiller operating profiles were considered: one using operational data from a university campus and a second from literature based on the Atlantic Fleet operation. Results and discussion: When powered via fossil fuels, over 90% of emissions were due to the indirect emissions from energy; therefore, the global warming potential (GWP) of the refrigerant was not the primary contributor to the total CO 2eq emissions. With natural gas, total LCCP emissions were reduced for R450A (7.8%), R513A (4.7%), R516A (9.4%), R1234ze (E) (10%), R515A (8.4%), and R515B (6.4%) compared to R134a for the university campus load profile. For the round-the-clock Atlantic Fleet profile, there were emission reductions for R450A (3.6%), R513A (0.25%), R516A (2.3%), R1234ze (E) (2.4%), R515A (1.5%) and R515B (2.4%) compared to R134a. When coupled with renewable energy, the indirect emissions from the chillers substantially decreased, and GWP-dependent leakage emissions accounted for up to 74% or 40% of emissions from R134a alternatives powered by wind and nuclear, respectively. For operation using the load profile from the university campus chillers, R450A had the highest coefficient of performance (COP) of 5.802, while R513A had the lowest COP (5.606). Tradeoffs between alternative refrigerants exist in terms of operation, temperature glide, size of heat exchangers, system design, flammability, cost, availability, and material compatibility. In terms of flammability, R134a, R513A, R450A, R515B and R515A are A1 (nonflammable) fluids. R450A and R516A also have temperature glides of 0.4 K and 0.056 K, respectively, which can affect condenser design. In terms of equipment modification (sizing), R513A require fewer modifications.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.247

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.296
Teacher spread0.270 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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