Concentrated solar thermal cogeneration for zero liquid discharge seawater desalination in the Middle East: case study on Kuwait
Bibliographic record
Abstract
ABSTRACT Processes have been developed for seawater desalination and for producing the required heat and power. To produce high-pressure steam and generate heat and electrical energy, solar thermal technologies can be directly applied. The design and development of water desalination technologies in the Middle East considering the particular geographic and weather conditions are the main challenges addressed in this study. Reverse osmosis in series with thermal methods is employed to prevent the environmental impact of the conventional methods, including the release of greenhouse gases and saline water rejection into seas. A design procedure is presented to calculate the equipment size and the process parameters in a concentrated solar thermal cogeneration and desalination plant with zero liquid discharge. In this case study, the available hourly solar irradiance data of Kuwait are directly input during designing. Based on the minimum and maximum values of the available solar energy, which correspond to the shortest and longest days of a year, production capacities of 400,000 and 865,000 m 3 /d in winter and summer, respectively, are obtained for the desalination plant. The calculations yield a total reflector surface area of 2,670,000 m 2 and molten salt heat storage of 85,500 tons.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Research integrity | 0.001 | 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".