Numerical Study of a Longitudinal Solar Dryer in Semi-Arid Area; Case Study
Bibliographic record
Abstract
A numerical simulation to predict the thermal performance of a longitudinal solar dryer has been carried out.For this, a mathematical model, based on the finite element method, has been developed to evaluate the thermal behavior of the solar dryer using a control system.The main objective of the used control system is to maintain the drying temperature inside a suitable range for the product to dry, under varying weather conditions, over the time drying process.This is achieved through many different steps.As, an example, at the beginning of drying process when solar radiation is low, the air flow rate at the inlet varies between Re=25 and Re=85.In other hand, when solar radiation is higher, fresh air is injected.The outcomes of simulation work showed that the obtained results are generally satisfactory.Nonetheless, this model can be further refined to obtain better results, as a more stable gradient temperature, over the full drying period.Moreover, it is worthy mentioned that thermal storage system can be combined with the studied solar drier, in the way to compensate the heat insufficiency, during low solar radiation days.
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 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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".