Abstract
Reverse osmosis (RO) technique is one of the most efficient ways for seawater desalination to solve the shortage of freshwater. For prediction and analysis of the performance of seawater reverse osmosis (SWRO) process, an accurate and detailed model based on the solution-diffusion and mass transfer theory is established. Since the accurate formulation of the model includes many differential equations and strong nonlinear equations (differential and algebraic equations, DAEs), to solve the problem efficiently, the simultaneous method through orthogonal collocation on finite elements and large scale solver were used to obtain the solutions. The model was fully discretized into NLP (nonlinear programming) with large scale variables and equations, and then the NLP was solved by large scale solver of IPOPT. Validation of the formulated model and solution method is verified by case study on a SWRO plant. Then simulation and analysis are carried out to demonstrate the performance of reverse osmosis process; operational conditions such as feed pressure and feed flow rate as well as feed temperature are also analyzed. This work is of significant meaning for the detailed understanding of RO process and future energy saving through operational optimization.
Highlights
China, which has the largest population in the world and is called the world’s factory, has a much more serious problem of freshwater shortage
A reverse osmosis desalination unit is composed of dozens of cylindrical pressure vessels, and several units with a permeate water storage tank were used as the key part of a seawater desalination plant
To solve the tough problem with high efficiency and accuracy, orthogonal collocation on finite element is proposed to transform the problem into NLP
Summary
China, which has the largest population in the world and is called the world’s factory, has a much more serious problem of freshwater shortage. Abbas analyzed and simulated an industrial medium-scale brackish water reverse osmosis plant with semirigorous model, and he used it to analyze the optimal operation of RO system [13]. Geraldes considered both the investment cost and operation cost of SWRO system and provided the differential equations of the RO process with distributed method [14]. To achieve accurate prediction of RO process performance and to accelerate the computing efficiency for real time simulation, the mathematical modeling is carried out based on rigid first principle, simultaneous method within which the differential variables are fully discretized by finite element collocation. The mathematical model is verified and simulation under different conditions will be discussed
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
