Investigation of New Refrigerant Blends as R410A Alternatives for Air-cooled Split Air Conditioner
Bibliographic record
Abstract
The Kigali Amendment is an international agreement addressing the environmental impact of high-GWP (Global Warming Potential) refrigerants and reducing their contribution to climate change. High-GWP refrigerants are potent greenhouse gases that tightly trap heat in the Earth's atmosphere, resulting in an enhanced greenhouse effect and global warming. The amendment contributes significantly to advancing sustainable practices in the refrigeration and air conditioning industries by limiting the use of these potent greenhouse gases and encouraging the adoption of more environmentally friendly alternatives. As a result, the replacement refrigerants in this study must have lower GWP values than R410A, which aligns with the Kigali Amendment's goals. This study aimed to identify potential refrigerants to replace R410A in air-cooled split air conditioners while adhering to the Kigali Amendment's GWP requirements. By combining environmental indexes and thermodynamic properties, the study can evaluate and compare various refrigerant blends to identify those that are environmentally friendly, energy-efficient, and meet the Kigali Amendment's GWP requirement. The evaluation identifies promising R410A replacements, such as R446A for high-temperature applications and R32 for higher-temperature air conditioning. R447B, R452B, and R454B exhibit improved system performance and efficiency due to the slightest temperature glide during phase transition. R454B has the highest Coefficient of Performance (COP) and volumetric refrigeration capacity, indicating greater energy efficiency and a lower environmental footprint. These findings help select appropriate refrigerant alternatives, address environmental concerns, and adhere to Kigali Amendment regulations. This research promotes environmentally friendly refrigeration solutions and sustainable practices in the air conditioning industry.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".