Experimental Study of Temperature Distribution of Two-Stage CascadeRefrigeration System Using R508B as Working Fluid at Low Stage
Bibliographic record
Abstract
This paper presents the experimental study on temperature distribution of two-stage cascade vapor-compression system for achieving super-low temperature. Two-stage cascade vapour compression cycle is a method to achieve super low temperature under -80℃. This system requires two different types of refrigerant at higher and lower stages. However, by the Montreal protocol, several refrigerants for the low-stage system as well as high stages have been banned due to its threat to ozone layer. Alternatives retrofit refrigerant for replacing CFC and HCFC lies from HFC to natural refrigerant. In this study, azeotropic zero-ODP refrigerant, R508B blend of two HFC refrigerant R23/R116 (46.0/54.0) was utilized in the low stage cycle, this refrigerant has advantages based on normal boiling point compare to its compositing element. On this experiment, cooling chamber was filled with ethyl alcohol 0, 10, 20, and 25 liter respectively as refrigerant load. By changing the volume of cooling chamber fluid, temperature distribution of the system was observed. More ethyl alcohol mass in the cooling chamber, longer steady state condition achieved. It is also found that the change of ethyl alcohol in the cooling chamber gives little effect on the final temperature distribution.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".