Increasing the COP of a refrigeration cycle in natural gas liquefaction process using refrigerant blends of Propane-NH3, Propane-SO2 and Propane-CO2
Bibliographic record
Abstract
This paper investigates the feasibility of using inexpensive techniques to enhance the coefficient of performance (COP) of the refrigeration cycle used in the liquefaction of natural gas. The effect of mixing the propane refrigerant with ammonia, sulfur dioxide and carbon dioxide on the performance and the work of the compressor is studied. It is shown that the mixture of ammonia-propane and sulfur dioxide-propane enhances the overall COP by 7% and 9%, respectively. The addition of ammonia and sulfur dioxide to the propane refrigerant reduces the overall compressor work by reducing the overall mass flowrate required to absorb a constant heat from the natural gas. On the other hand, the mixture of carbon dioxide-propane degrades the overall COP by 70%. The addition of carbon dioxide increases the overall mass flowrate required to absorb a constant heat from the natural gas. Interestingly, the proposed method requires small capital and running costs.
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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".