Numerical investigation of the solar activated carbon/methanol adsorption refrigeration system in Tehran’s climate
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Bibliographic record
Abstract
Solar adsorption refrigeration systems are used to extract heat using solar radiation based on the adsorption phenomena. In these systems, the temperature of the solar collector plays an important role in the efficiency of a system. In this study, two different models, including the lumped and the distributed ones, are investigated to predict the temperature distribution in a specific solar collector. The operating conditions are the same for both cases. Moreover, for the solar radiation as one of the boundary conditions, the data for Tehran solar irradiation is used. The results of the temperature analysis show that the distributed model predicts a less maximum collector temperature than the lumped model which clearly results in a lower system performance. In addition, it can be concluded that because of using steel as a main material for the collector and its high thermal capacitance, it takes almost 3 days for the system to reach the periodic operating conditions.
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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 | 0.001 |
| 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 it