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A New Algorithmic Method for Reverse Osmosis Desalination Analysis: Design Optimization and Parametric Study

Authors :
Rima Aridi
Mohamad Al Mawla
Elias Harika
Thierry Lemenand
Mahmoud Khaled
Mostafa Gad El-Rab
Source :
Eng, Vol 5, Iss 3, Pp 1183-1208 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

Population growth, coupled with industrial and agricultural development, has resulted in increased demand for freshwater supply. For countries with scarce water resources, desalination constitutes the only viable solution to this problem. Reverse osmosis (RO) technology has become widely used as the membrane materials have been upgraded and the costs have been reduced. Nowadays, RO is the foremost technology for desalting different types of water such as seawater, brackish, and tap water. However, its design is critical since many parameters are involved in obtaining a good design. The high use of RO encourages the establishment of a procedure that facilitates the design process and helps in obtaining an optimum-performance RO desalination system. This paper presents a procedure divided into three parts: (1) classifying RO parameters; (2) choosing the parameters in a certain order and doing the calculation process through 12 steps; and (3) then inserting the selected parameters and the obtained values on RO System Analysis (ROSA) software. These points are then summarized by creating an algorithmic chart to follow during the design phase of the RO system using ROSA. An example on the proposed list is then taken to validate the procedure, and a comparison is conducted on choosing different values for the parameters. The results of this comparative study show that choosing different parameters affects the RO system productivity. Additionally, every design has a specific optimum set of parameters, which depends upon the design constraints set by the user.

Details

Language :
English
ISSN :
26734117
Volume :
5
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Eng
Publication Type :
Academic Journal
Accession number :
edsdoj.2bceb153bff84570998eb7914aec30c2
Document Type :
article
Full Text :
https://doi.org/10.3390/eng5030065