Transient and dynamic performance of solar driven multiple effect distillation
Bibliographic record
Abstract
Transient and dynamic performance of solar driven multiple-effect distillation (MED) system without thermal energy storage (storing of water rather than energy) are studied and presented. A typical 25,900 m3/day operational multiple effect distillation with thermal vapor compression (MED-TVC) is used for the transient and dynamic simulation. Two scenarios are studied for the transient performance to; i) pump the feed water flow and ii) spray feed water onto the horizontal tubes bundle in each effect. The first scenario uses a constant flow rate of feed water along most of operating hours. The second scenario assumes a sinusoidal trend for the feed water flow rate during the operating hours (simulating direct PV electrical generation with no electric energy storage). The dynamic performance is due to a disturbance of a rectangular pulse forcing function on the seawater flow for duration of 50 s, which increased 25% for 5 s. The response of that disturbance on the behavior of the MED process parameters, such as the distributions of the temperatures, mass flow rates, and physical properties is presented. The physical model of each effect is divided into seven compartments including brine pool, vapor space, tubes bundles and feed water pre-heater. Transient and dynamic equations for each compartment and other system components are formulated mathematically. Mass, salt and energy balance equations are solved dynamically taking into consideration the inter-related effect of each compartment onto the other. The transient resultant flow rates of each stream (vapor production, TVC, brine disposal, etc) are presented in details and compared to conventional steady operation. When using the feed water scenario of sinusoidal feed to operate the solar MED unit, the results indicates that the salt precipitation can increase above the designed value. The results show also that the dynamic behavior of feeding water coming into the effects is flows the same trend the disturbance that took place in the main source of seawater supply. The flow rates of feed water are affected by the applied disturbance and increases gradually from normal operation to a peak value then decreases again to the normal operation state value. The system undergoes this disturbance shows to be still stable in operation as the change in its behavior is just bounded around the disturbance time, and regain, in a very short time, to the initial (normal operation) value of starting point. Key words: Solar energy, desalination, dynamic behavior, MED-TVC.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".