Modeling and Analysis of Desalination in A Solar Dome Using CFD
Bibliographic record
Abstract
Although solar energy has gained popularity in the distillation of brine to produce potable water due to the increasing costs of fossil fuels and environmental concerns, its use in this process remains limited by factors such as applicability and cost.Consequently, there is a need to investigate modeling, transmission characteristics, and estimation of solar basin parameters to develop an efficient design.In response to this need, a two-dimensional model of evaporation and condensation processes in static solar energy was created using the computational fluid dynamics (CFD) approach.The simulation aimed to facilitate the development of a solar dome device.The solar dome's water temperature ranged from 48 to 59℃ at peak times, with an evaporation rate of 41 W/m²℃, an evaporation coefficient of 6 W/m²℃, and a freshwater production rate of 0.45 kg/m³ h.Both the volume of freshwater produced and the water temperature were found to be satisfactory.CFD was employed to calculate the convective and evaporative heat transfer coefficients.This study illustrates that CFD is a powerful tool for designing, evaluating, and diagnosing solar desalination systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".