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Proof-of-Concept for Gas-Entrapping Membranes Derived from Water-Loving SiO2/Si/SiO2 Wafers for Green Desalination
Published on: March 1, 2020
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An efficient data-driven desalination approach for the element-scale forward osmosis (FO)-reverse osmosis (RO) hybrid
Sung-Ju Im1, Nguyen Duc Viet2, Byung-Tae Lee3
1Department of Civil and Environmental Engineering, University of California, Los Angeles, CA, 90095, United States.
Environmental Research
|July 30, 2023
Summary
This study optimizes forward osmosis-reverse osmosis (FO-RO) hybrid systems for seawater desalination. Artificial intelligence accurately predicted system performance, identifying optimal configurations for efficient freshwater production.
Area of Science:
- Environmental Science
- Chemical Engineering
- Water Treatment Technologies
Background:
- Growing global population drives demand for freshwater, increasing interest in desalination.
- Forward osmosis-reverse osmosis (FO-RO) hybrid technology offers a low-energy solution for seawater desalination.
- Scaling up FO-RO systems requires understanding optimal membrane configurations for commercial viability.
Purpose of the Study:
- To explore and optimize the performance of spiral-wound FO-reverse osmosis (SWFO-RO) and plate-and-frame FO-reverse osmosis (PFFO-RO) hybrid systems.
- To evaluate the predictive accuracy of artificial intelligence models for FO-RO system performance.
- To determine optimal operational conditions and membrane element numbers for effective seawater desalination.
Main Methods:
- Element-scale testing of SWFO-RO and PFFO-RO hybrid systems.
- Development and application of artificial intelligence (AI) models for performance prediction (water flux, reverse salt flux).
- Utilizing a Markov-based decision tree for water flux level classification.
Main Results:
- Both SWFO-RO and PFFO-RO hybrid systems achieved high water recovery under optimized conditions.
- AI models demonstrated superior prediction accuracy (R > 0.99, RMSE < 5%) compared to traditional mass balance models.
- Optimal operational parameters were identified, including feed solution flow rate, concentration, and operating pressure for high water permeability in RO.
- A configuration of five SWFO elements and four PFFO elements was found to be optimal for the hybrid system.
Conclusions:
- Optimized FO-RO hybrid systems are effective for seawater desalination, yielding high water recovery.
- AI significantly enhances the prediction and optimization of FO-RO system performance.
- Specific operational conditions and membrane element ratios are crucial for maximizing efficiency and ensuring long-term viability of FO-RO desalination.
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