Forward osmosis for multi‐effect distillation brine treatment: Performance and concentration polarization evaluation
Bibliographic record
Abstract
Abstract The discharge of reject brine from seawater desalination processes is a threat to marine ecosystems. This study investigated the feasibility of forward osmosis (FO) for the treatment of reject brine from multi‐effect distillation (MED) systems. The performances of two commercial FO membranes (ie, cellulose triacetate (CTA) and polyamide thin film composite (TFC) membranes) were compared. The effects of operating conditions, such as draw solution concentration, cross‐flow velocity, and temperature, on concentration polarization and consequently on the water flux, were quantitatively analyzed using a mathematical model. Results showed that the batch FO process could effectively reduce the volume of MED brine to 54.9% using 3 mol/L NaCl. As the draw solution concentration increased from 1‐5 mol/L, a significant increase in the initial water flux from 3.23‐17.88 L · m −2 · h −1 and from 3.55‐24.04 L · m −2 · h −1 was observed for the CTA and TFC membranes, respectively. However, the proportions of the effective osmotic pressure differences decreased from 20.7% to 11.9% and from 23.5% to 6.2% for the CTA and TFC membranes, respectively, indicating the concentration polarization (CP) was severe for high‐salinity brine treatment. The positive effects of increasing cross‐flow velocity on CP were limited. Moreover, the high temperature of the MED brine effectively mitigated the internal concentration polarization (ICP), thereby enhancing the water flux. Overall, this study provides valuable guidance for the application and optimization of FO in MED brine treatment.
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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 | 0.000 | 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) | 0.000 | 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".