Search

The reduction of energy consumption in the reverse osmosis (RO) process is critical. The forward osmosis (FO)-RO hybrid process can be suggested to reduce RO energy consumption. In this study, a numerical FO-RO process model was developed to analyze the FO-RO hybrid process. The performance of the FO-RO hybrid process was compared with the stand-alone RO process. In addition, the impacts of the control parameters for operation, and the intrinsic membrane parameters, were analyzed using sensitivity analysis. In conclusion, the FO-RO hybrid process involves less RO energy consumption than the stand-alone RO process. The FO draw flow velocity and the RO applied pressure were derived as the major factors for controlling the FO-RO process. In addition, the control parameters for operation were found to be more important than the intrinsic membrane parameters in the minimization of RO energy consumption. Subsequently, the FO elements installed in front of the RO process should be configured with a parallel connection, in order to minimize RO energy consumption. The results in this study could be used to develop guidelines for the optimal design of the FO-RO hybrid process.

Despite many kinds of research on pressure-retarded osmosis (PRO), feasibility studies for PRO are still insufficient. To provide a better understanding of PRO-hybridized processes, an energy efficiency analysis should reflect the hybridization features of three processes, including PRO, seawater reverse osmosis (SWRO), and membrane distillation (MD). To this end, a new dimensionless (i.e., unitless or scale-free) performance index is proposed to facilitate a fair comparison of energy efficiency between SWRO-PRO and SWRO-MD-PRO. The new performance index physically implies a ratio of the total energy recovered by PRO to the total energy consumed by SWRO and MD. The performances of hybridized processes were estimated with the new index and compared to each other after running several simulations. The simulation results showed that SWRO-MD-PRO generally has a higher energy efficiency than SWRO-PRO if an inexpensive heat source, such as waste heat, is used. However, the energy efficiencies of both PRO-hybridized processes were different according to the simulation conditions. Therefore, it can be concluded that energy optimization for PRO-hybridized processes should be conducted differently than for SWRO. The results from this study are expected to play a key role in providing a new roadmap for PRO-hybridized process research.

© 2016 Elsevier B.V. In this study, colloidal fouling behavior in pressure retarded osmosis (PRO) was systematically investigated in terms of the effects of draw solution concentration, applied hydraulic pressure at the draw side, feed solution pH, and particle size. Commercially-available cellulose triacetate (CTA) membranes were fouled with feed solution containing silica colloidal particles. Two different silica particles with mean diameter of 27 and 152 nm were used as model foulants. Our findings demonstrated that the colloidal fouling in PRO was dominantly affected by the cake layer buildup at the membrane surface. Fouling was further exacerbated by diffused salts from the draw side because retained salts within the cake layer elevated the salt concentration on the membrane surface, and consequently reduced the driving force of PRO. Substantial flux decline with the smaller particles was attributed to the high cake layer resistance due to the formation of the void-less cake layer. In addition, our approaches to mitigate the colloidal fouling revealed that the hydraulic cleaning by increasing the cross-flow rates was not effective to eliminate the compact cake layer. However, adjusting the feed solution pH showed the high potential to relieve the colloidal fouling resulting from the more stabilization of particles at low solution pH.

Since the early 2000s, pressure retarded osmosis (PRO) has been continuously investigated, based on its potential to harvest energy from a salinity gradient. However, recent negative reports on its fundamental feasibility and the closure of the largest industrial implementation have slowed its momentum, with regard to its commercialization. In this respect, this review provides insights into the current status of PRO technologies in membrane fabrication, module design, process optimization, and industrial movements for the commercialization of PRO. Notably, despite dramatic advancements in lab-scale PRO membrane performance, recent modeling studies have revealed advanced membrane properties have only a minor impact on PRO performance. In contrast, developing PRO module designs are deemed to have paramount importance, due to the drastically low module performance compared to lab-scale membrane performance, and high potential of design modification to resolve inefficient PRO module structures. Various simulation methods for optimizing PRO processes using the classic mass transfer model, thermodynamics, and machine learning optimizations are comparatively analyzed. Integrations of seawater reverse osmosis and PRO and other hybrid processes with PRO are discussed in terms of recent pilot-scale implementations and modeling results. Finally, small and large industrial movements and projects for PRO commercialization are analyzed in detail, based on their quantitative outcomes.

A performance analysis of a tri-combined process that consists of reverse osmosis (RO), membrane distillation (MD), and pressure-retarded osmosis (PRO) was conducted by using numerical approaches in order to evaluate its feasibility. In the hybrid process, the RO brine is partially used as the MD feed solution, and the concentrated MD brine is then mixed with the rest of the RO brine to be considered as the PRO draw solution. Here, the brine division ratio, incoming flow rate of RO, dimensions of the MD and PRO processes, and the supply cost of the MD heat source were considered as influential parameters. Previously validated process models were employed and the specific energy consumption (SEC) was calculated to examine the performance of the RO–MD–PRO hybrid process. The simulation results confirmed that the RO–MD–PRO hybrid process could outperform stand-alone RO in terms of reducing the SEC and the environmental footprint by dilution of the RO brine in locations where free or low-cost thermal energy can be exploited. Despite the need for further investigations and pilot-tests to determine its commercial practicability, this study provides insights into future directions for water and energy nexus processes for energy efficient desalination.

The presence of the spacer and biofilm can accompany the high complexity of the mass and momentum transport in an osmotic backwash (OBW) process of reverse osmosis (RO) membranes. For more reliable simulations, it would be essential to consider such highly complex transport phenomena across the membranes and through membrane flow channels. Therefore, we simulated the effects of spacer designs, hydrodynamic, and membrane properties on OBW in the scenario of biofouling on RO membrane surfaces. To this end, the OBW process was numerically modeled in two-dimensional spacer-filled crossflow channels based on the finite element method. Subsequently, the concentration and velocity fields inside of the membrane, biofilm, and flow channels were analyzed. Results showed that the submerged spacer could enhance the water and salt mass transfer in the membrane channel, to a greater extent than the cavity and zigzag spacers, which can ultimately enhance the OBW efficiency for a foulant removal. Additionally, the OBW performance is chiefly impacted by the structure parameter of the porous support layer. Also, the existence of biofilm in the feed channel can render the feed concentration and membrane water permeability more sensitive to the OBW process than the non-fouled channel.

We conducted a scenario study on a promising RO–PRO hybrid system to alleviate water and energy demands. We utilized a previously validated reverse osmosis (RO) process model and modified a model of a pressure-retarded osmosis (PRO) process to properly consider the spatial distribution of concentration and velocity based on a mass balance principle. Using the models, we compared four different RO–PRO hybrid configurations based on the water and energy return rate (WERR). Subsequently, the comparison of the water production rate and energy production rate confirmed the results that RO plays a dominant role to determine the WERR value. Hybrid systems that use seawater as a feed water for RO are more energy price sensitive. That is, a decrease in the RO plant size considerably diminishes the WERR values; however, the PRO plant size plays a minor role to determine the WERR value. Research and available literature on RO–PRO hybrid processes are in a relatively early stage; this study is a preliminary step to evaluate further advances in hybrid systems that can eventually alleviate water and energy demands.

A numerical model for predicting the flux decline due to colloidal fouling was developed for a forward osmosis (FO) membrane system. We derived the kinetic equation of the cake layer growth based on a first-order reaction and control volume approach. Based on the model simulation, it was found that the deposited particles on a membrane surface are proportional to the feed concentration and the permeate flux. Moreover, the simulation result reveals that the cake-enhanced osmotic pressure (CEOP) is a key factor diminishing the permeate flux for large colloidal foulants. For small colloidal foulants, the hydraulic resistance of the cake layer is dominant in flux decline at the beginning of the fouling and CEOP increasingly become significant as fouling progresses. The effects of the reverse draw solute permeation on the flux decline were also simulated. Interestingly, the increased reverse draw solute permeation obtained by increasing the solute permeability showed little effect on the flux decline. Contrarily, variation of the diffusivity significantly influenced the flux decline. Consequently, the numerical model developed in this paper suggests that the selection of draw solute for an FO membrane process should be carefully regarded, along with the fouling mechanism.

Performance of forward osmosis (FO) process is significantly affected by factors such as membrane properties, concentration polarization (CP), and fouling. In this study, FO performance of a plate and frame type membrane is investigated via a numerical simulation based on mass conservation theorem. To evaluate the FO membrane performance, permeate flux and recovery rate are simulated according to membrane orientation, flow direction of feed and draw solutions, flow rate, and solute resistivity (K). In the case of membrane orientation, all-inside case, in which the draw solution faces the active layer, displays a relatively higher performance than all-outside and all-up cases. Notably, the membrane performance is highly affected by K indicating the extent of the internal CP. During the simulation approach, the spatial variation of the concentration profile was observed on a 2-dimensional membrane area; it was expected to cause a high diffusion load on a particular area of membrane, due to the relatively higher flux at that location. Moreover, it can result in unexpected fouling in a specific area on a membrane. Accordingly, the findings in this study suggest that the numerical simulation can be applied to optimize both physical properties and operation conditions, thereby ensuring cost-effective operation of FO processes.

In the recent past, machine learning (ML) techniques such as artificial neural networks (ANN) or genetic algorithm (GA) have been increasingly used to model membrane fouling and performance. In the present study, we select genetic programming (GP) for modeling and prediction of the membrane fouling rate in a pilot-scale drinking water production system. The model used input parameters for operating conditions (flow rate and filtration time) and feed water quality (turbidity, temperature, algae pH). GP was applied to discover the mathematical function for the pattern of the membrane fouling rate. The GP model allows predicting satisfactorily the filtration performances of the pilot plant obtained for different water quality and changing operating conditions. A valuable benefit of GP modeling was that the models did not require underlying descriptions of the physical processes. GP has displayed the potential to evaluate membrane performance as a feed-forward simulator toward an “intelligent” membrane system.

Forward osmosis (FO) is an osmotic process that uses a semi-permeable membrane to effect separation of water from dissolved solutes by an osmotic pressure gradient. Unlike reverse osmosis (RO), FO does not require high pressure for separation, allowing low energy consumption to produce water. However, the internal concentration polarization in FO is an important factor affecting the performance of FO processes. This paper was intended to investigate the characteristics of FO and RO processes. A simple film theory model was applied to consider concentration polarization in FO and RO processes. This model allows the estimation of internal and external concentration polarization effects in FO process. A laboratory-scale FO device was used to find the model parameters for further calculations. The calculated flux was compared with experimental flux under a variety of operating conditions. It was found that the combination of FO and RO may result in a higher flux than FO-only process under some operating conditions. Further research will be required to investigate the effect of membrane materials on energy efficiency of FO and RO hybrid system.

This paper presents a novel methodology to determine an optimized control method for feed water temperature in a seawater reverse osmosis (SWRO) desalination process using genetic programming (GP) which is an evolutionary algorithm used to fi nd functional forms through training data. Two functional models were determined by GP with operation data collected over four years from Fujairah SWRO plant. The models showed high accuracy (>99.0%) in terms of the average error rate between the observed and the predicted values. The fi rst model involved the permeate water fl ow rate with a functional temperature correction factor (TCF), water transfer coeffi cient, and net driving pressure (NDP) and the second is the salt passage ratio with a functional TCF, salt transfer coeffi cient, and total dissolved solids (TDS) in the feed. To determine the optimized control of the feed water temperature, a new control methodology with the two functional models was proposed and applied to a simulation of the feed water temperature, which showed better performance in terms of the permeate fl ow rate. Applying the optimized control of feed water temperatures to a plant under identical operational conditions, it was found that the permeate fl ow rate could be increased by approximately 900 m 3 /day under a steady condition of 600 ppm in permeate TDS.

Seawater reverse osmosis (SWRO) desalination is rising as an alternative solution for the water shortage problem which is more severe than before. In this study, a package of process models was developed and tested by four-year SWRO plant operation data obtained from Fujairah in UAE, as a tool not only for simulating the performance of SWRO desalination process but for estimating the total profits of the plant operation. The simulation results based on the developed process models were reasonably satisfied to predict the SWRO desalination plant performance in terms of permeate water concentration and flow rate. And the results of cost estimation show a possibility that the models can successfully predict total annual profits (TAP) within the order of magnitude of USD/year, according to operating date, feed water concentration, and permeate water condition. Consequently, the developed package model is applicable to support design criteria and efficient operation of SWRO desalination plant as references.

An artificial neural network (ANN) was developed to predict the performance of a seawater reverse osmosis (SWRO) desalination plant, and was then applied to the simulation of feed water temperature. The model consists of five input parameters (i.e., feed temperature, feed total dissolved solids (TDS), trans-membrane pressure (TMP), feed flow rate, and time) and two output parameters (i.e., permeate TDS and flow rate). Then, the one-year operation data (n = 200) from the Fujairah SWRO plant was divided into three data sets (i.e., training, validation, and test data set) to develop the ANN model. The trained ANN model was subsequently found to produce good agreement between the observed and simulated data (TDS: R2 = 0.96; flow rate: R2 = 0.75) in the test data set. The results of this study show that the variation of the feed water temperature and TMP was found to significantly affect both the permeate TDS and flow rate. From subsequent simulations with various temperature controls, it is further suggested that the permeate TDS can be reduced using a linear increase control (from 27.5 to 29.5°C) for the feed temperature in an SWRO hybrid system with multi-stage flash (MSF) distillation, such as the Fujairah plant.

This study proposes a new operation methodology for energy saving in the Fujairah seawater reverse osmosis (SWRO) plant, as the optimum feed pressure is determined at the controlled operating temperature. To this end, two functional models were developed by genetic programming (GP) using two-year operational data. The data revealed that the required feed pressure for the plant operation was potentially overestimated. Based on the developed models, simulation of a three-step sequential control was carried out to reduce and optimize the required feed pressure. The simulation results first indicate that the temperature control significantly reduces the required feed pressure at a reasonably high temperature. Second, as the permeate water flow rate (PFR) is determined by the optimized feed pressure instead of the permeate pressure actually used to maintain a steady PFR in Fujairah, the required feed pressure could be substantially reduced. As a result, the proposed methodology can potentially reduce the required feed pressure, by approximately 10 bar, under the identical performance of both PFR and permeate water total dissolved solids (TDS). This study implies that the optimization of operation and management of MSF-hybridized SWRO processes can considerably improve the efficiency of the desalination process in terms of energy and, eventually, cost saving.

Fouling is one of the most serious problems in seawater desalination using reverse osmosis (SWRO) which is important to lower the production cost of desalinated water. For efficient operation of the SWRO plant, accurate models are crucial to decide the optimal operating condition and cleaning operation. The model for RO membrane system has been studied by many researchers and its usefulness has been increased as its accuracy has been improved. However, the prediction of fouling is difficult due to its extremely complicated mechanism of growth involving various foulants. In this study, the development of the fouling is predicted by monitoring the membrane resistance across the membrane and the friction coefficient through spiral-wound membrane from the operation data. Using nonlinear recursive least-squares (NRLS) method, the two properties are identified from the operating data based on the one-dimensional model of the SWRO system. By this method, the degree of fouling can be inferred from the two properties and potential cleaning time can be predicted. It can also assess the effectiveness of membrane cleaning. Using the actual data of an existing plant, the trends of resistance and friction coefficient could be monitored and the effect of cleaning pattern of the real plant can be evaluated by recursive parameter estimation online.

Over 100 papers were reviewed to elucidate factors influencing large-scale seawater desalination plants with reverse osmosis networks (SWRO). This paper consists of subjects such as SWRO systems investigation, system models of pretreatment and RO networks, systems optimization to minimize the total cost of SWRO plant design, and the future direction of SWRO technology. In order to design a large-scale seawater desalination plant, a systematic understanding of SWRO processes should be followed. After investigating all the processes, including site-specific features, seawater intakes, pretreatment systems, RO networks, energy recovery systems, post-treatment systems, brine disposal, and the environmental impact of SWRO desalination, system models are discussed for predicting the performance of each system. Based on the minimal principle of total cost required for a full-scale SWRO plant, optimized results are discussed. Studies needed for developing future SWRO technologies are suggested.

The Center for Seawater Desalination Plant (CSDP), which was established in December 2006, launched its R&D project [seawater engineering and architecture of high efficiency reverse osmosis (SEAHERO)] in the middle of 2007 and aimed to get world top-level seawater reverse osmosis (SWRO) plant technologies. SEAHERO will accomplish its technical objectives with a fund of US $165 million for 5 years. One of the most important technical targets of SEAHERO is the scale-up of the SWRO system for economies-of-scale. Through a rigorous technical review of the scale-up strategies, CSDP selected two key strategies for the scale-up. One is the scale-up of RO unit trains by assembling RO modules and the other is the scale-up of RO module size. An SWRO plant test-bed of 10 MIGD (≈45,000 m3/d) in capacity will consist of two different RO unit trains of 6 MIGD (≈27,000 m3/d) and 4 MIGD (≈18,000 m3/d). The 6 MIGD train targets the largest RO unit train in the world. The 4 MIGD train will adapt RO modules 16" in diameter, which are twice as large as modules in current RO markets. The two different RO trains divide the risk of the new technology to increase the probability of success. With the two scale-up strategies, SEAHERO is expected to achieve the leading SWRO plant technology in the world.

Scale formation of soluble salts is one of the major factors limiting the performance of reverse osmosis (RO) membranes for desalination. In this study, a dynamic model based on the crystallization theory was developed to analyze the effect of CaSO4 scale formation on RO desalination process. Taking into consideration two mechanisms in scale formation including surface and bulk crystallization, the performance of RO filtration was predicted as a function of crossflow velocity, transmembrane pressure, permeate recovery, and operation mode. The model results indicated that RO fouling due to surface crystallization is important in batch filtration whereas both surface and bulk crystallization is important in crossflow filtration. This is because concentration polarization is directly related to surface crystallization. RO fouling due to bulk crystallization appeared to increase with increasing crossflow velocity and permeate recovery. The effects of background organic matters and antiscalant on scale formation were quantified using the model. The effect of operating parameters on RO fouling and concentration polarization was explored based on the model analysis.

As a means of optimizing desalination processes, site-specificity in the determination of seawater quality conditions is a crucial point for improving the overall energy efficiency of a seawater reverse osmosis (SWRO) process. To this end, field studies were carried out at 16 sampling sites along the shoreline in South Korea to investigate the site-specific features of seawater quality. Also, two mathematical models were developed for the simulation of SWRO processes dependent on seawater quality in macroscopic and microscopic contexts, respectively. As a result, the microscopic dynamic model revealed that concentration polarization in the vicinity of the membrane surface and permeate concentration are affected by the feed seawater concentration and pressure. Then, the application of Fujairah SWRO plant operation data to the macroscopic simulation of a non-isobaric SWRO process model resulted in significant energy savings in terms of operational pressure savings, reducing 0.3 bar from the annual average value in the first pass operational pressure. These findings suggest that a cost-effective SWRO operation can be feasible using non-isobaric pressure controls by considering site-specific feed seawater concentrations. Results of the study presented here can be applied to improving the energy efficiency in SWRO plants through the optimization of pressurized systems.