Study on Adsorption Refrigeration System Using Activated Carbon-Ethanol as Working Pair
Bibliographic record
Abstract
The adsorption refrigeration system is an alternative refrigeration system powered by thermal source so that it is possible to use waste heat and solar energy. This paper reports the experiment of the ethanol-activated carbon (AC) as the adsorbateadsorbent pair. Experimental work was conducted with two adsorption beds as thermal compressor. Ethanol-AC pair can be operated with the heat source temperatures 90o C and 100o C for different heat sink temperature 20o C, 25o C and 30o C, respectively. The experimental result shows when temperature of the hot water 100o C and the cooling water temperature 30o C, the system give the higher coefficient of performance (COP) than another testing operation condition. Additionally, the COP of the system is varying a long operating in average 0.19 due to manually intermittent operation of both adsorption beds. The maximum adsorption capacity is 0.302 kg/kg·AC while the desorption temperature, desorption pressure and heating time of the adsorption bed are 85o C, 85.52 kPa and 80 minutes, respectively, and the cooling capacity is 23.61 kJ for a operating cycle. The experimental result proved that the ethanol-AC is suitable pair with the adsorption system for cooling application. It can be operated at low temperature driven heat source, and has an environmentally friendly behavior and the working pair is easy to be found in the commercial market.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".