Solute migration mechanisms and their prediction for melting brackish water ice using gravity-induced desalination techniques
Freshwater scarcity is one of the most serious challenges worldwide. The melting process of brackish water ice has more desalination effect than the formation process of brackish water ice. In this experiment, ice crystals produced by single-stage progressive freezing under different conditions of i...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025024806 |
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| Summary: | Freshwater scarcity is one of the most serious challenges worldwide. The melting process of brackish water ice has more desalination effect than the formation process of brackish water ice. In this experiment, ice crystals produced by single-stage progressive freezing under different conditions of icing temperature and raw water solute concentration were utilized to carry out gravity-induced desalination (GD) and conventional ice melting tests. The migration pattern of TDS, Cl−, SO42−, CO32−+HCO3−, Na+, K+, Ca2+ and Mg2+ under the conditions of different ice crystal quality was explored. The results showed that the solute concentration of ice-melt water during the GD process showed an exponential decay, and the water type changed from Na·Mg-Cl to Na-Cl·SO4. The ion removal rate showed a distribution pattern of Na+ > Cl− > K+, Ca2+, Mg2+ > CO32−+HCO3− > SO42−. The key factors affecting the ion removal rate are ion relative mass, ion radius, icing temperature, and average ion concentration. The assumption of mixed ice-melt water for GD was proposed and predictive model was constructed. The model can be used to accurately predict the solute concentration of mixed ice-melt water. Using the mixed ice-melt water solute concentration as the target solute concentration for users’ demand can significantly improve water production rates. A case study was presented to illustrate the application of the predictive model, and the case showed a 27.40 % increase in water production rate. |
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| ISSN: | 2590-1230 |