Differential evolution optimization of water gap membrane distillation process for water desalination

•Modeling of water-gap membrane distillation (WGMD) process with cost analysis.•Optimization using the Differential Evolution (DE) technique.•Application of single and multi-objective optimization functions.•Optimization of output productivity, energy consumption, and water production cost.•Comprehe...

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Veröffentlicht in:Separation and purification technology Jg. 270; S. 118765
Hauptverfasser: Alawad, Suhaib M., Khalifa, Atia E., Abido, Mohamed A., Antar, Mohamed A.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.09.2021
Schlagworte:
Differential evolution algorithm
Performance optimization
Single and multi-objective function optimization
Water desalination
Water gap membrane distillation
Performance optimization
Differential evolution algorithm
Single and multi-objective function optimization
Water desalination
Water gap membrane distillation
ISSN:1383-5866, 1873-3794
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Beschreibung
Zusammenfassung:•Modeling of water-gap membrane distillation (WGMD) process with cost analysis.•Optimization using the Differential Evolution (DE) technique.•Application of single and multi-objective optimization functions.•Optimization of output productivity, energy consumption, and water production cost.•Comprehensive investigation of the effects of operating and design parameters. A theoretical model to predict the performance of the water gap membrane distillation process is developed to study the impacts of the operating parameters on the permeate flux, specific energy consumption, and water production cost. The MD model is integrated with a heuristic differential evolution (DE) optimization technique to optimize the operating variables of the process to maximize the permeate flux and minimize the energy consumption and production cost. The optimized parameters include the feed temperature, coolant temperature, feed flow rate, coolant flow rate, and water gap thickness. The optimization is carried out for both single and multi-objective functions. Results indicated that about 60% increase in the value of the highest permeate flux is obtained from the optimization model compared with the theoretical model of the MD process. Moreover, the lowest values of both energy consumption and production cost are reduced by about 31% and 38%, respectively, when the optimization is applied. For the multi-objective model, optimization results showed significant improvement and achieved an optimized permeate flux 51% higher than the maximum flux obtained from the MD model without optimization, with an optimized value of specific energy consumption as low as 876 kWh/m3.
ISSN:1383-5866
1873-3794
DOI:10.1016/j.seppur.2021.118765