EFFECTS OF FIN SPACING AND FIN HEIGHT OF CAPILLARY-ASSISTED TUBES ON THE PERFORMANCE OF A LOW OPERATING PRESSURE EVAPORATOR FOR AN ADSORPTION COOLING SYSTEM
Bibliographic record
Abstract
Adsorption cooling systems (ACS) are a viable alternative to vapor compression refrigeration cycles where low-grade waste heat is abundant. When using water as a refrigerant in ACS, the operating pressure is quite low (< 5 kPa) and the performance of the system is severely affected when using conventional evaporators. This problem can be addressed by using capillary-assisted evaporators. In this study, a new capillary-assisted evaporator test bed is designed and built, and three enhanced tubes with different fin geometries (fin spacing and fin height) and a plain tube are tested under different chilled water inlet temperatures. The results show that enhanced tubes provide 1.65−2.23 times higher total evaporation heat transfer rate compared to the plain tube. Under equal inner and outer heat transfer surface areas, the results also show that the enhanced tube with parallel continuous fins and higher fin height (Turbo Chil-26 FPI) has 13% higher evaporation heat transfer coefficient than that of a tube with lower fin height (GEWA-KS-40 FPI).
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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 | 0.001 |
| 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) | 0.001 | 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".