Towards Solar Pond Design and Development for Masdar City Environment
Bibliographic record
Abstract
Salinity-gradient solar ponds (SGSP) are water bodies that serves as a solar thermal energy storage system.Establishing a salinity gradient and observing the role of gravity and diffusion between the different zones is key-point in achieving optimal system performance.In this work, a numerical model is developed using computational fluid dynamics (CFD) acting as an initial step in designing and building a solar pond located in Masdar City for the usage of space cooling and desalination.The model is governed by continuity, species transport, momentum, and energy equations of naturally convicted, transient and non-isothermal flow.Results show the stability of the three working zones of the pond if carefully are injected and established.Although diffusion lingers for long time, it is balanced by the gravity forces that slows its propagation and confined it to a thin layer located at corresponding interfaces between zones.This work numerically shows the diffusion influence on the extent of stability of the three core zones of the solar pond.It demonstrates how one could achieve sustainable salinity and temperature gradients to ensure reliable working principle of the sola pond.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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".