Energy, exergy and economical analysis of N2O based cascade refrigeration system for ultralow temperature cooling applications using different eco-friendly refrigerants in high temperature cycle
Bibliographic record
Abstract
Implementing the Montreal Protocol has limited the use of conventional refrigerants and has led industries to find optimal or economical eco-friendly refrigerants to reduce environmental hazards. The present study analyzes an N2O-based cascade refrigeration system for achieving ultralow cooling temperatures using different eco-friendly refrigerants with low GWP and ODP in a high-temperature cycle. 3E (Energy, Exergy, and Economy) analysis of a cascade refrigeration system using eco-friendly refrigerants such as R290, R1270, RE170, R600, R600a, HFE7100, and HFE7000 in the upper cycle and N2O in the lower cycle was conducted. The R744A/R600 pair performed best among the other refrigerant pairs due to its lower discharge pressure and compression ratio. The refrigerant pair R744A/R600 results in a higher cascade cycle COP of approximately 0.87, with 48% exergetic efficiency, while the refrigerant pair R41/HFE7100 has the lowest COP (0.68) and lowest exergetic efficiency (42%). The minimal operational cost varies from 73006 to 76907 USD per annum for refrigerant pair R744A/R600, while for the other pairs, the cost varies from 98625 USD to 114674 USD. The R744A/R600 refrigerant pair provides COP values that are 1.38 to 5.38% greater than the others, with a 1.01 to 3.45% variation in exergy efficiency.
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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 | 0.001 |
| 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) | 0.002 | 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".