This study seeks to evaluate the performance and economic feasibility of the forward osmosis (FO)–reverse osmosis (RO) hybrid process; to propose a guideline by which this hybrid process might be more price-competitive in the field. A solution-diffusion model modified with film theory was applied to analyze the effects of concentration polarization, water, and salt transport coefficient on flux, recovery, seawater concentration, and treated wastewater of the FO process of an FO-RO hybrid system. A simple cost model was applied to analyze the effects of flux; recovery of the FO process; energy; and membrane cost on the FO-RO hybrid process. The simulation results showed that the water transport coefficient and internal concentration polarization resistance are very important factors that affect performance in the FO process; however; the effect of the salt transport coefficient does not seem to be large. It was also found that the flux and recovery of the FO process, the FO membrane, and the electricity cost are very important factors that influence the water cost of an FO-RO hybrid system. This hybrid system can be price-competitive with RO systems when its recovery rate is very high, the flux and the membrane cost of the FO are similar to those of the RO, and the electricity cost is expensive. The most important thing in commercializing the FO process is enhancing performance (e.g.; flux and the recovery of FO membranes).

This study seeks to evaluate the economic feasibility of membrane distillation (MD) and reverse osmosis (RO)-MD hybrid system for seawater desalination. A theoretical cost model was applied to analyze the effects of flux, recovery, membrane properties, and energy price on RO, MD, and RO-MD hybrid system. The simulation results showed that MD stand-alone system and RO-MD hybrid system can be cost-competitive compared with RO systems when the recovery and flux of MD system are higher than those of RO system and the steam cost is relatively cheap. It is also revealed that the water costs of RO-MD hybrid system and RO system are same under similar operating conditions, but the water cost of MD stand-alone system is higher. The effect of thermal energy cost on water cost for MD and RO-MD systems was also analyzed. Based on these results, guidelines for an analysis of economic feasibility of MD and RO-MD were suggested.

Membrane distillation (MD) is a thermally driven membrane process using porous hydrophobic membranes. MD has been investigated as an alternative desalination technology due to its advantages over multi-stage flash (MSF) and reverse osmosis (RO). Nevertheless, it is difficult to design and optimize the MD systems under various conditions, because both thermal and hydrodynamic effects play an important role. Therefore, this study focused on performance analysis of MD systems in different configurations. Direct contact MD (DCMD) and vacuum MD (VMD) were experimentally compared using laboratory-scale systems. A simple model was also applied to analyze the difference between two configurations theoretically. Experimental results indicated that permeate flux in DCMD and VMD were sensitive to the operating conditions. Using same membranes, two MD systems showed different flux behaviors. The influences of operating parameters for DCMD and VMD on overall efficiency were also investigated. The model results also confirmed the difference between these two systems theoretically.

The reverse osmosis (RO) technology is currently the leading desalination method. However, until recently, application of RO technology on a large scale has been primarily limited by membrane fouling. The mechanism of fouling is complex, which is not well understood in full-scale plants. Although many studies about modeling and prediction of fouling have been done, in most cases, the experimental data set of lab or pilot scale systems, which may not show fouling characteristics well in full-scale systems were used. In this study, both artificial neural network (ANN) model and tree model (TM) was evaluated to analyze long-term performance of full scale reverse osmosis desalination plant. The results of application of the ANN and TM indicated high correlation coefficients between the measured and simulated output variables. However, it is not easy to use ANN for the full scale plant operation because the final model is not expressed as a form of mathematical functions. TM has advantages over ANN because the model can be obtained as forms of simple function and it showed reasonably high R2. Therefore, TM is shown to be more adequate than ANN for developing models in which the full-scale RO plant data is considered as an input.