Determining of Climatic Parameters Using CFD in Different Window Span in Naturally Ventilated Greenhouses
Bibliographic record
Abstract
The aim of this study was to compare with the measured inner air temperature and relative humidity values and the simulated values determined with Computational Fluid Dynamics (CFD) in the naturally ventilated gable-roofed single glass greenhouse located North-South direction, having 45o and 90° window spans and under no cultivation.
 The measured values were recorded every 2 hours from 8 am to 18 pm using the relative humidity and air temperature sensors placed in 7 different locations. Measurements were made in case of the 45° and 90° window span openness. For CFD simulations, the SolidWorks 2011 software was used. The values of air temperature and relative humidity inside the greenhouse were simulated depending on the outside ambient conditions and structural and physical properties of greenhouse. Then, the measured values were compared with the simulated values and error rate for each sensors were determined.
 As a result, it was determined minimum error rates of the measured and simulated air temperature and relative humidity in greenhouses is 4.8% and 4.7%, respectively. The study showed that the CFD can be used as a powerful tool for determining inner climatic factors in naturally ventilated greenhouses.
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 | 0.001 | 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 | 0.001 | 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".