Reliable and Efficient Targeting for Optimal Design of SWRO Desalination Processes

This work introduces a systematic seawater reverse osmosis (SWRO) membrane network synthesis approach, based on the coordinated use of process superstructure representations and global optimization. Thermodynamic insights are employed in the development of lean network representations that lead to significantly improved overall search speed as compared to previously proposed superstructure representations. Besides the extraction of the globally optimal reverse osmosis process network solution for given feed water conditions and product specifications as a design performance target, the approach further enables the systematic development of structurally distinct design alternatives. These solutions provide the design engineer with a better understanding of the design space and trade-offs between complexity and efficiency. This is achieved through the introduction of distinct membrane network design classes, which are established by partitioning the search space based on network size and connectivity. Corresponding lean superstructures are then systematically generated for each class, which capture all structural and operational variants within the corresponding design class. This enables multiple distinct optimal designs to be extracted through global optimization. The approach is illustrated with a numerical example, so as to enable comparison with previous work in the field of SWRO network synthesis.