Retrofitting of Vapour Compression Refrigeration Trainer by an Eco-friendly Refrigerant
Bibliographic record
Abstract
After years of successful deliberations for tackling the grievous problem of ozone depletion, the United Nation's environmental protection agency concluded multinational agreement called 'Montreal Protocol' for controlling the use of gases threatening the ozone layer. The successful implementation of the 'Montreal Protocol' in developed countries is being appreciated for its significant reduction in emission level of ozone depleting substances Now it is the turn of developing countries to fulfill their obligation of Montreal Protocol. The dead line for complying with the phase out of chloroflurocarbon in developing countries like India is 2010. The refrigeration industry has accepted the challenge of chloroflurocarbons phase out and new eco-friendly refrigerant like hydroflurocarbons and hydrocarbons are replacing chloroflurocarbons in all commercial and industrial application. Vapour compression refrigeration trainer is an important equipment of thermal engineering lab of mechanical engineering department which operated using chlorofluorocarbon 12. CFC12 is the most important member of CFC refrigerants which are being targeted for phase out in India by 2010. In this paper, performance valuation of many eco-friendly hydrocarbon refrigerants for replacing CFC12 in the trainer has been done and a suitable drop in alternative refrigerant for retrofitting has been identified.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".