Feasibility of Usage Possibility in Turkey of Solar Driven Ejector-Absorption Cooling System
Bibliographic record
Abstract
It appears that solar assisted refrigeration systems are a promising alternative to the conventional electrical driven units. Their main advantages are the reduction of peak loads for electricity utilities, the use of zero ozone depletion impact refrigerants, the decreased primary energy consumption, and decreased global warming impact. In this study, we have investigated the possibility of using ejector-absorption cooling systems (EACS) in Turkey. In addition, this study determines whether or not required heat for generator of EACS can be obtained from solar energy in Turkey. There are two important reasons to explain the use of EACS in Turkey. One is that the production and use of the CFCs and HCFCs will be phased out according to Montreal Protocol. The second is that, in Turkey, solar energy potential is very high due to its location in the northern hemisphere with latitudes 36–42°N and longitudes 26–45°E, the yearly average solar radiation is 3.6 kWh/m2 day, and the total yearly radiation period is ∼2610 h. The radiation data and sunshine duration information collected since 2000 for 17 cities are used for analysis in different regions of Turkey. For maximum coefficient of performance (COPmax) conditions of EACSs operated with aqua-ammonia, it is found that required optimum collector surface area was defined by using the meteorological data. In addition since the system can be used throughout the year, required minimum energy for auxiliary heater was also calculated. It is shown that the heat gain factor (HGF) varies in the range from 0.5 to 2.68 for the all the seasons in the selected cities. The maximum HGF is 2.68 for Van in July. This study shows that there is a great potential for utilisation of solar cooling system for domestic heating/cooling applications in Turkey.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".