Assessing Energy Performance and Environmental Impact of Low GWP Vapor Compression Chilled Water Systems
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".