Enhancement of Pyramid Solar Still Productivity Through Wick Material and Reflective Applications in Iraqi Conditions
Bibliographic record
Abstract
The global challenge of water scarcity significantly impacts the socio-economic development of countries, especially in developing regions such as Iraq where accessible potable water is scarce. Solar distillation emerges as a promising technique for desalinating water, particularly through passive solar stills that harness direct solar radiation. This study investigates the performance enhancement of pyramid solar stills, specifically focusing on the employment of wick materials and reflectors under the climatic conditions of Iraq. Wick materials markedly augment the evaporation area and the area for solar radiation absorption, thereby boosting the still's production. Similarly, reflectors play a crucial role in elevating the water temperature in the distillation process, leading to increased evaporation and daily productivity. Results demonstrate that the use of wick materials in the pyramid solar still (CWPSS) significantly outperforms the conventional pyramid solar still (CPSS), with a production increase of 122% and a daily thermal efficiency of 53%, compared to CPSS's 34.5%. Moreover, the application of reflective materials further escalated CWPSS's productivity by 170%, although the distillation efficiency remained constant at 48%. Future research should explore advancements in wick materials, integrated systems, simulation modeling, and field testing to optimize the technology's performance under Iraqi conditions.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".