Performance of Quonset-Type Greenhouse Integrated With Thin Film Photovoltaic Thermal System Combined With Earth-Air Heat Exchanger for Hot and Dry Climatic Conditions
Bibliographic record
Abstract
Abstract The present study proposes a Quonset-type greenhouse integrated with a thin-film photovoltaic thermal (GiPVT) system combined with an earth-air heat exchanger (EAHE) for crop cultivation in harsh hot climate conditions. A periodic thermal model in terms of input climatic and design parameters has been developed to evaluate the GiPVT system’s thermal performance. This model is based on the energy balance equations of the GiPVT system, and it calculates PV roof temperature, greenhouse air temperature, and plant temperature for a given climatic data, i.e., solar irradiation and ambient air temperature. Furthermore, the thermal load leveling for the GiPVT system is determined to assess the thermal comfort status within the enclosed space of the system. The results indicate that EAHE successfully reduces greenhouse air temperature and increases the thermal comfort level inside the GiPVT system. Corresponding to the optimum flowrate of 0.5 kg/s, the maximum temperature of the plants and greenhouse is reduced by 20 °C and 21 °C, respectively. Moreover, the present GiPVT system produces 29.22 kWh of electrical energy per day, making the system self-sustainable.
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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 | 0.000 | 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".