Minimum return dilution method to regulate discharge of brine from desalination plants
Bibliographic record
Abstract
The mixing zone approach in regulating the discharge of brine and other toxic dense discharges has many limitations when applied in environmentally sensitive areas. A well-defined minimum return dilution is advocated in this study as an alternative method to regulate the disposal of brine and other toxic dense discharges. This study examined experimentally the development and dilution of turbulent vertical dense jets (or fountains) at small Froude numbers. The study complements an earlier larger Froude number investigation. The mean and fluctuating temperature fields were measured with fast responding thermocouples, and an emphasis was given to the minimum return dilution, which occurred just outside the edge of the discharge pipe. The study has revealed that at small Froude numbers (Fr < 5) the normalized minimum dilution, μmin/Fr, decreased linearly with the Froude number and it became constant only at larger Froude numbers (Fr > 7). Simple design equations for the calculations of minimum return dilution and maximum excess temperature and salinity at the level of the source are provided for small and large Froude number regimes. This study also recognized the advantage of using a vertical discharge configuration (inclination θ = 90o with horizontal) as opposed to an inclined configuration (0o ≤ θ < 90o) when discharging brine into water environments. The inclined discharge configuration has the potential of producing higher concentrations of brine and temperature near the source when ambient currents are in a direction opposite to the discharge.
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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 | 0.000 | 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) | 0.001 | 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".