الفهرس 
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Abstract
The objective of the present work is to investigate theoretically and experimentally, the optimization of the RO desalination system leading to maximum performance. The experimental work is carried out to measure and study the influence of the main design and operating parameters on the RO system in both laboratory and commercial plants.
In the theoretical work, the most popular system governing equations are chosen to be employed in the Genetic Algorithm method to approach the system optimization. Results have shown that increasing the feed water temperature increases the permeate flow rate and decreases brine flow rate. Also, it decreases the pH for permeate water and brine pH value. Higher feed water pressure leads to higher permeate flow rate and lower brine flow rate. It also decreases the permeate salinity. Results have shown also that higher feed water salinity reports lower permeate flow rate and higher brine flow rate. Both permeate and brine salinity increases with the increase of feed water salinity. Higher feed water pH value decreases the permeate flow rate and increases the brine flow rate. In the range of experimental runs, the maximum gain in recovery ratio has been obtained from the feed water pressure increase.
The increase of feed water temperature or pressure results in a recovery ratio increase while the increase of feed water salinity or feed water pH leads to a decrease in recovery ratio. In the other part of the experimental work, a 5000 m3/day RO desalination plant in Nuweiba City in Sinai, Egypt is taken as a case study. The measured data of the plant are recorded during 5 years of its normal operation. Also, experimental trials are carried out in site to investigate the influence of the main design and operating parameters on the plant performance. The RO system is found to be sensitive to the variation in the feed water temperature, pressure and salinity. Experimental results of the prototype setup and that of case study of Nuweiba city plant are presented in graphical form where the same trend is observed for both.
The present results match the same of the pervious work. In the theoretical work, the most popular system governing equations are chosen to be employed in the Genetic Algorithm method to approach the system optimization. The application of the approach on Nuweiba reverse osmosis plant showed its capability to solve such actual optimization problems.