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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.

Background and aims The nonalcoholic fatty liver disease fibrosis score (NFS) is comprised of metabolic risk indicators that may accurately predict residual cardiovascular risk in patients with CAD. Method This is a nested case control study of the post PCI registry from single tertiary hospital. Among 5589 patients who underwent PCI from 2010 through 2014, previously diagnosed 1510 NAFLD patients and 296 consecutive NAFLD patients who had undergone both PCI and ultrasonography of abdomen within 1 year between the tests were enrolled. (median age, 64y (IQR 55–73)). We applied the NFS to the patients at baseline, using validated NFS cut-offs and 201 patients with higher NFS, defined as NFS >0.67 at PCI, were 1:1 matched with controls, based on propensity scores for higher NFS >0.67. Results Higher NFS (NFS >0.67) was more prevalent in patients with left ventricle (LV) dysfuction (LVEF at PCI Conclusion With a longitudinal assessment of the association between NAFLD status by NFS and the risk of CV death, we found post-PCI patients with persistent higher NFS were at higher risk of CV death compared with those without. KM rates of CV death according to NFS Funding Acknowledgement Type of funding source: None

Background Electrocardiographs (ECG) are obtained by a digital signal. However, they are still printed out of paper to read by physicians. Digitizing the analog ECG from the paper to digital signal make us much easier to access of bid data pool form the daily clinical practice and previous resources. Objective The goal of this study is to digitize paper ECG to detect premature ventricular contraction (PVC). Methods This system consists of 2 steps; digitization and PVC detection. Results First, for digitization, ECG are filtered by the specific cut-off value of red, green and blue, then the filtered ECG image is changed into gray scale. In order to extract ECG signal, the algorithm fine the only one of the biggest white body throughout the X-axis. The X and Y axis is matched with distance and amplitude, depending on dots per inch (DPI). Second, to detect PVC, ECG signal is filtered to eliminate baseline wandering. The characteristics of PVC is higher amplitude and longer duration than normal sinus rhythm, we set two criteria to detect the PVC: 1.5 times the duration, 1.2 points out of the amplitude. For the synchronization of timing, lead II rhythm strip was used by PVC detection and then the rest of 12-lead ECG is matched based on lead II synchronization (Figure 1). We applied this algorithm to the 300 real patient's ECG. 290 of 300 (96.7%) ECG are successfully digitized signal and PVC detection. Conclusion We successfully developed the algorithm analog ECG signal into digital signal to detect PVC. In the future, this method helps to gather big data from ECG papers to develop a new algorithm to localization of PVC. Funding Acknowledgement Type of funding source: Foundation. Main funding source(s): Korean Heart Rhythm Society 2019 Research Fund

In this study, we conducted a numerical simulation to evaluate stability in the seawater reverse osmosis (SWRO) process against seasonal variations of feed water. The impact of element configuration on SWRO operation was analyzed using a process model consisting of the solution–diffusion model. Seawater quality and temperature data collected from the intake of the Fujairah desalination plant (United Arab Emirates) were used to identify optimum internally staged design (ISD) configurations. Monitoring data were also used to simulate changes in SWRO performance. The process performance of the ISD configurations as compared to conventional design configurations in terms of specific energy consumption, permeate total dissolved solids concentration and recovery ratio. The results showed that SWRO processes with four ISD configurations met the performance requirements over 12 months despite the fluctuations in seawater quality and temperature. The pre-diction results of the ISD configurations showed stable operation during the 12 month simulation period. These configurations had a significant advantage with respect to membrane maintenance. This study’s findings could be used to optimize the element configuration of the SWRO process by predicting the process performance while accounting for seasonal variations of seawater quality and temperature.

This paper introduces an obstacle-avoiding algorithm for bipedal robots, especially in push recovery situations. Typically, There are many algorithms that plan footstep to avoid obstacles based on vision recognition data. However, if the robot is pushed, the planned footprint will change, and thus, there is no guarantee that it will avoid obstacles. Although modified stepping positions can be limited, the robot’s stability is not assured. Our proposed algorithm focuses on avoiding obstacles through vision recognition in push recovery situations and generating compensation actions for instability by restricting modified footsteps. We fuse vision feedback with our previous push recovery algorithm, which optimizes the ankle, hip, and stepping strategies. We build simple grid data using vision recognition and apply it to the inequality constraint of the stepping position. We validate the effectiveness of our algorithm using the bipedal platform GAZELLE with the Kinect V2 RGBD sensor.

Background and purpose Based on the data of patients who measured office BP (OBP) in controlled condition, home BP (HBP), and 24-hour ambulatory BP (24hABP) for diagnosis of hypertension, we developed and validated a diagnostic algorithm for hypertension. Methods Patients who have high BP (≥140/90 mmHg) at the outpatient clinic were referred to measure OBP in controlled condition, HBP and 24hABP. The OBP was measured three times at each visit for 3 days in controlled condition by using a validated oscillometric device. HBP was measured for 7 days in triplicates every morning and evening. The 24hABP was measured on the 8th day. Same study protocol was used for development and validation population. Results In the development of algorithm, 319 patients were recruited and data of 256 patients (51.8±9.7 years, 119 men) with valid HBP and 24hABP measurements were analyzed. In the validation of algorithm, 300 patients were recruited and data of 257 patients (52.4±9.8 years, 126 men) with valid HBP and 24hABP measurements were analyzed. In the development population, the prevalence of masked hypertension was 19.5% (n=50) and most of them (n=47, 94%) was in the range of 130–139/80–89 mmHg. The BP in the range of 130–144/80–94 mmHg was defined as the grey zone of OBP, because prevalence of white-coat hypertension was lowered to 1.6% from 4.3% with threshold of 145/95 mmHg. The diagnostic sensitivity, specificity, positive and negative predictive value of OBP was improved to 97.4%, 76.5, 96.5% and 81.3% after excluding the grey zone of OBP (n=125). The diagnostic agreement between 24hABP and HBP in the grey zone of OBP was 64%. The diagnostic sensitivity, specificity, positive and negative predictive value of HBP were 88.8%, 74.7, 93.5% and 61.5% after excluding the grey zone of HBP (130–134/80–84 mmHg, n=28). Based upon these results, we developed a diagnostic algorithm for hypertension by using on out-of-office BP measurements to improved diagnostic accuracy of hypertension (Figure). In the validation population, the developed algorithm showed similar diagnostic accuracy. Diagnostic algorithm for hypertension Conclusion For accurate diagnosis of hypertension, OBP measurement according to guidelines and 24hABP measurement to grey zone of OBP is preferred. To improve diagnostic accuracy of HBP measurement, 24hABP measurement to grey zone of HBP is required. Acknowledgement/Funding Part of this study was supported by a grand from Dong-A ST Co. Ltd., Seoul, Korea.

In this paper, we present new distributed coordination for a set-point regulation of asymmetric compartmental systems under periodically time-varying external inputs. The feature of the proposed coordination is to adjust system parameters, which is directly related to interflow rate among compartments and outflow rate to environment. In contrast to symmetric compartmental systems, there is a difficulty in analysis resulted from a property of compartmental matrix in the asymmetric cases; however, we solve the problem by designing an appropriate coordination range of the system parameters. In order to compensate the time-varying effect in the inputs, we assume that the structure of the inputs is a finite Fourier series, and show that the coordination of the system parameters should have the same structure with the same frequencies. The remainder of the coordination is to determine coefficients of the Fourier series of the system parameters. We develop a distributed update law for obtaining the coefficients. We apply the distributed coordination to water irrigation systems and water distribution systems, and show the effectiveness of the proposed distributed coordination schemes through numerical simulations.

In this study, Internally Staged Design (ISD) was numerically optimized in order to demonstrate the long-term performance of full-scale seawater reverse osmosis (SWRO) membrane systems in the presence of colloidal foulants. To this end, a numerical model based on a finite difference method was developed and optimized with various feed water qualities, such as fouling potential and total dissolved solids (TDS). As a result, the optimized ISD exhibited greater water flux and higher energy efficiency in long-term operation (90 days) compared to conventional designs, where single-type membrane elements were employed over a pressure vessel while achieving potable TDS concentration in permeate (

The presence of flow control devices and/or obstacles in the fluid flow such as baffles and spacers complicates the solid-fluid mixing pattern, which remains difficult to describe by classical analytical solutions. In this study, the removal of fine particles in a tertiary sedimentation tank mounting an adjustable baffle was investigated using the computational fluid dynamics code-COMSOL. The solid-fluid motion was solved by consecutively applying the equations of the continuity and momentum using the finite element method. The experiment was conducted by the sedimentation tank with the adjustable baffle inclined at 30° in a pilot scale plant. It's used as the reference data set for numerical simulations that were run on a 2-dimensional domain by modifying the configuration settings of angles for an adjustable baffle (i.e., 30°, 45°, and 60°) and without one. Results showed that the simulation results matched well with the experimental data for an adjustable baffle at 30° (NSE=0.97). The sedimentation tank with the adjustable baffle at different angles had a lower overflow rate (in the area of flow rebound) and mixing intensity (in the area of flow curve) than without one, eventually leading to enhanced particle removal efficiency. This tendency became more pronounced as the particle motion stabilized over time. The sedimentation tank mounting the adjustable baffle at 30° provided the best settling efficiency among the four different flow patterns. However, the conventional index that represents the mixing properties did not correctly address their relative efficiency for fine particle removal. Therefore, a numerical simulation tailored to a given geometry should be conducted to fully elucidate the fluid dynamics in the sedimentation tank with complex devices or obstacles.

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.

A transient model of seawater reverse osmosis (SWRO) system enables systematic assessment of membrane performance in response to changes in time-series parameters, operating conditions, or ancillary equipment. In this study, we describe the effects of energy recovery device (ERD) and feed pressure control on the SWRO plant in terms of energy consumption (reduced) and water quantity (increased) using a numerical model at pilot scale. In the simulation, two types of isobaric ERD, i.e. pressure exchanger (PX) and dual work exchanger energy recovery (DWEER), were used to quantify changes of the mass flow rates of inflow and outflow in the system. Also, temporal variation in the raw feedwater quality was addressed in the model with adaptive feed pressure control to maintain the amount of produced water under fouled membrane conditions. Results showed that the observed recovery and rejection rates in the pilot-scale plant had an excellent agreement with their predicted values under different seawater fe...

© 2015 by the authors. Global energy consumption has been highly dependent on fossil fuels which cause severe climate change and, therefore, the exploration of new technologies to produce effective renewable energy plays an important role in the world. Pressure-retarded osmosis (PRO) is one of the promising candidates to reduce the reliance on fossil fuels by harnessing energy from the salinity gradient between seawater and fresh water. In PRO, water is transported though a semi-permeable membrane from a low-concentrated feed solution to a high-concentrated draw solution. The increased volumetric water flow then runs a hydro-turbine to generate power. PRO technology has rapidly improved in recent years; however, the commercial-scale PRO plant is yet to be developed. In this context, recent developments on the PRO process are reviewed in terms of mathematical models, membrane modules, process designs, numerical works, and fouling and cleaning. In addition, the research requirements to accelerate PRO commercialization are discussed. It is expected that this article can help comprehensively understand the PRO process and thereby provide essential information to activate further research and development.

Groundwater contamination with arsenic (As) is one of the major issues in the world, especially for Southeast Asian (SEA) countries where groundwater is the major drinking water source, especially in rural areas. Unfortunately, quantification of groundwater As contamination is another burden for those countries because it requires sophisticated equipment, expensive analysis, and well-trained technicians. Here, we collected approximately 350 groundwater samples from three different SEA countries, including Cambodia, Lao PDR, and Thailand, in an attempt to quantify total As concentrations and conventional water quality variables. After that, two machine learning models (i.e. artificial neural network (ANN) and support vector machine (SVM)) were applied to predict groundwater As contamination using conventional water quality parameters. Prior to modeling approaches, the pattern search algorithm in MATLAB software was used to optimize the ANN and SVM model parameters, attempting to find the best param...

Of growing amount of food waste, the integrated food waste and waste water treatment was regarded as one of the efficient modeling method. However, the load of food waste to the conventional waste treatment process might lead to the high concentration of total nitrogen (T-N) impact on the effluent water quality. The objective of this study is to establish two machine learning models-artificial neural networks (ANNs) and support vector machines (SVMs), in order to predict 1-day interval T-N concentration of effluent from a wastewater treatment plant in Ulsan, Korea. Daily water quality data and meteorological data were used and the performance of both models was evaluated in terms of the coefficient of determination (R2), Nash-Sutcliff efficiency (NSE), relative efficiency criteria (drel). Additionally, Latin-Hypercube one-factor-at-a-time (LH-OAT) and a pattern search algorithm were applied to sensitivity analysis and model parameter optimization, respectively. Results showed that both models could be effectively applied to the 1-day interval prediction of T-N concentration of effluent. SVM model showed a higher prediction accuracy in the training stage and similar result in the validation stage. However, the sensitivity analysis demonstrated that the ANN model was a superior model for 1-day interval T-N concentration prediction in terms of the cause-and-effect relationship between T-N concentration and modeling input values to integrated food waste and waste water treatment. This study suggested the efficient and robust nonlinear time-series modeling method for an early prediction of the water quality of integrated food waste and waste water treatment process.

Chlorophyll-a (Chl-a) is a direct indicator used to evaluate the ecological state of a waterbody, such as algal blooms that degrade the water quality in lakes, reservoirs and estuaries. In this study, artificial neural network (ANN) and support vector machine (SVM) were used to predict Chl-a concentration for the early warning in the Juam Reservoir and Yeongsan Reservoir, which are located in an upstream region (freshwater reservoir) and downstream region (estuarine reservoir), respectively. Weekly water quality data and meteorological data for a 7-year period were used to train and validate both the ANN and SVM models. The Latin-hypercube one-factor-at-a-time (LH-OAT) method and a pattern search algorithm were applied to perform sensitivity analyses for the input variables and to optimize the parameters of the two models, respectively. Results revealed that the two models well-reproduced the temporal variation of Chl-a based on the weekly input variables. In particular, the SVM model showed better performance than the ANN model, displaying a higher prediction accuracy in the validation step. The Williams-Kloot test and sensitivity analysis demonstrated that the SVM model was superior for predicting Chl-a in terms of prediction accuracy and description of the cause-and-effect relationship between Chl-a concentration and environmental variables in both the Juam Reservoir and Yeongsan Reservoir. Furthermore, a 7-day interval was determined as an efficient early warning interval in the two reservoirs. As such, this study suggested an effective early-warning prediction method for Chl-a concentration and improved the eutrophication management scheme for reservoirs.

This paper presents a desalination process powered by a microgrid. Desalination is critically important for many countries demanding potable water beyond that available in nature. The desalination process requires a stable power supply system. As the stable power supply system, microgrid, which is a distributed small capacity power system integrating renewable energy with energy storage, has become important. In this paper, small capacity desalination plant powered by a microgrid is implemented and its features are described. The desalination plant is operated by electricity provided from either renewable energy resource such as solar cell or power grid. Overall control of the desalination plant is carried out by a programmable logic controller and status of water production is monitored by energy management system. The implemented desalination plant consumes 5 kW and produces 1 m3/h of fresh water.

The integration of pressure retarded osmosis (PRO) into desalination processes is studied here, specifically in the aspects of energy recovery. In particular, hybridization with thermal and reverse osmosis process is analyzed in detail, showing how PRO can improve the energy efficiency of the desalination process. Some remaining issues regarding this hybridization are discussed.

This study introduces a schematic methodology for smart water grids (SWGs) for use in water management platforms, which integrates information and communication technology (ICT) into a single water management scheme. SWG technology is seen as a promising solution for resolving recent critical global water problems. To ensure the security of water quantity, safety of water quality, and ICT-based water management solutions, SWG technology should integrate five prime research areas: (1) platform configuration in both water and ICT networks, (2) guarantee water resources including both natural and manufactured water, (3) intelligent control of water flow using bi-directional communication in water infrastructure, (4) better management scheme dealing with risk-minimization for assets in the water infrastructure, and (5) energy efficiency in operating and maintaining water infrastructure. Two platforms (i.e. water and ICT platforms) are introduced as examples of well-designed platforms for the managemen...

Blocking the natural bi-directional flow in an estuarine system using an artificial dyke has commonly caused serious water quality problems. In the southwestern part of South Korea, a parallel triple-reservoir system was constructed by blocking the mouth of three different rivers (Yeongsan, Okcheon, and Kumja), which were then interconnected using two open channels. This system has experienced a deterioration in water quality due to pollutants accumulated from the upper watershed, and has continually discharged pollutant loads to the outer ocean. Therefore, the objective of this study is to establish an effective dam operation plan for reducing nutrient loads released from the integrated reservoir. In this study, the CE-QUAL-W2 model, which is a 2-dimentional hydrodynamic and water quality model, was applied to predict the pollutant load released from each reservoir in response to different flow scenarios for the interconnecting channel. The model was calibrated using two novel methods: a sensitivity analysis to determine meaningful model parameters, and a pattern search to optimize the parameters. From the scenario analysis using flow control, it was determined that the total nitrogen (TN) and total phosphorus (TP) loadings could be reduced by 27.2% and 6.6%, respectively, under the optimal channel flow scenario by regulating the chlorophyll-a concentration in the reservoir. The results confirm that effective dam operation could contribute to a decrease in pollutant loads in the receiving seawater body. As such, this study suggests operational strategies for a multi-reservoir system that can be used to reduce the nutrient load being discharged from reservoirs.

Laser Lift-Off (LLO) is a process that removes a GaN or AIN thin layer from a sapphire wafer to manufacture vertical-type LEDs. It consists of a light source, an attenuator, a mask, a projection lens and a beam homogenizer. In this paper, we design an attenuator and a projection lens. We use the ‘ZEMAX’ optical design software for analysis of depth of focus and for a projection lens design which makes 7×7 ㎟ beam size by projecting a beam on a wafer. Using the ‘LightTools’ lighting design software, we analyze the size and uniformity of the beam projected by the projection lens on the wafer. The performance analysis found that the size of the square-shaped beam is 6.97×6.96 ㎟, with 91.8 % uniformity and ±30 μm focus depth. In addition, this study performs dielectric coating using the ‘Essential Macleod’ to increase the transmittance of an attenuator. As a result, for 23 layers of thin films, the transmittance total has 10-96% at angle of incidence 45-60° in S-polarization.

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.

© 2015 Elsevier B.V. Forward osmosis (FO) has been increasingly studied in the past decade for its potential as an emerging low-energy water and wastewater treatment process. However, the term "low-energy" may only be suitable for those applications in where no further treatment of the draw solution (DS) is required either in the form of pretreatment or post-treatment to the FO process (e.g. where the diluted DS is the targeted final product which can be used directly or simply discarded). In most applications, FO has to be coupled with another separation process in a so-called hybrid FO system to either separate the DS from the final product water or to be used as an advanced pre-treatment process to conventional desalination technologies. The additional process increases the capital cost as well as the energy demand of the overall system which is one of the several challenges that hybrid FO systems need to overcome to compete with other separation technologies. Yet, there are some applications where hybrid FO systems can outperform conventional processes and this study aims to provide a comprehensive review on the current state of hybrid FO systems. The recent development and performance of hybrid FO systems in different applications have been reported. This review also highlights the future research directions for the current hybrid FO systems to achieve successful implementation.

A fouling model for the seawater reverse osmosis (SWRO) process is required to propose an appropriate strategy for membrane maintenance (i.e., membrane cleaning and replacement). In this study, a fouling model that considered the concentration polarization was properly developed to simulate the long-term performance of the SWRO process based on models from the literature. The model was practically applied to one-year operation data obtained from the Fujairah SWRO desalination plant with parameter estimation, and good agreement between the measured data and simulated results was obtained for both the rejection and recovery rates. Compared to an integrated model consisting of two models from the literature, the fouling model proposed in this study showed reliable performance for membrane fouling such as the increase in the permeate TDS concentration according to operating time. In addition, simulations for membrane maintenance were conducted based on the variation in membrane resistance, which reflects the fouling state of the membrane. These revealed that the rearrangement of membranes is not significantly effective without cleaning the fouled membrane. Instead, a partial replacement of membranes can be an effective maintenance scheme to increase the recovery rate. Accordingly, the results of the study presented here can be used to save operation and maintenance (O&M) costs in SWRO plants through the optimized management of fouled membranes.

The development and exploitation of sustainable and environment-friendly energy resources are required in order to resolve global energy shortages. Recently, salinity gradient power (SGP) has been considered a feasible candidate, with high potential to become a substitute for the current use of fossil fuels due to benefits such as less periodicity, abundance and no emission of carbon dioxide. In this paper, one SGP, pressure-retarded osmosis (PRO) system, was reviewed in terms of its mechanism, limitations and available applications. In the PRO system, water permeates through a semipermeable membrane from the feed solution to the draw solution, and energy is generated by depressurizing the permeated flow through a hydro turbine. Models for understanding its mechanism and for improving of its performance were reviewed. In addition, applications of sea water reverse osmosis (SWRO), wastewater treatment (WWT) and PRO hybrid process were introduced in order to develop new water-energy nexus processes...

The forward osmosis process is considered a promising desalination method due to its low energy requirement compared to other methods. In this study, modelling and simulations for a plate-and-frame and a modified spiral-wound module are carried out for the FO process. The mathematical models consist of mass balance, a permeate flux model, and concentration polarization equations. The plate-and-frame model is formulated with consideration of flow directions, and the modified spiral-wound model is formulated with consideration of its geometric characteristics. These two sets of model equations are numerically and iteratively integrated since they are implicit and highly non-linear. The simulation for both modules was conducted by varying 4 types of operating conditions: volumetric flow rate of the feed and the draw solution, the concentration of the draw solution, flow direction, and the membrane orientation. The results for various conditions are also compared. In future research, the developed model could be applied for designing FO modules and finding optimal operating conditions.

The spread of antibiotics resistance among bacteria is a threat to human health. Since South Korea uses approximately 1.5 times more antibiotics than do other OECD countries, this is likely to impact the numbers and types of antibiotic-resistant bacteria found in the environment. In this study we examined feces from domesticated animals and humans for the diversity and abundance of antibiotic-resistant Escherichia coli. Abundant antibiotic-resistant E. coli were isolated from all the tested animals and humans and were examined by horizontal, fluorophore-enhanced, rep-PCR (HFERP) DNA fingerprint analysis. A total of 793 unique, non-clonal, E. coli isolates were obtained from the 513 human and animal hosts examined. Antibiotic resistance analysis, done using 14 antibiotics, indicated that 72.3% of the isolates (573 of 793) were found resistant to more than one antibiotic. The E. coli isolated from swine were resistant to the greatest number of antibiotics. Tetracycline resistant E. coli were routinely isolated from all animal hosts (36 to 77% per host), except for dairy cattle (9.3%). Twenty nine E. coli isolates from all hosts, except for duck, were resistant to more than 10 antibiotics. Gene transfer and southern hybridization studies revealed that resistance to 13 of the antibiotics was self-transmissible, and likely mediated by plasmids and integrons. Since genetically diverse and numerically abundant antibiotic-resistant E. coli were consistently recovered from chicken, swine and other domesticated animals in South Korea, our results suggest that the use of sub-therapeutic levels of antibiotics for disease prophylaxis and growth promotion should be curtailed.

Seawater reverse osmosis (SWRO) desalination is considered one of the most promising technologies for supplying freshwater to the regions suffering from water scarcity. Although a considerable amount of research has been conducted in attempts to improve SWRO desalination technology, reducing the cost of producing freshwater is still required. In Korea, this effort is already been being carried out by the Seawater Engineering & Architecture of High Efficiency Reverse Osmosis (SeaHERO) project. Core Technology 2 (CT2), one of the most important sub-projects out of four CTs under SeaHERO, pursues two main goals: optimization of processes for low energy consumption/high efficiency and localization of core parts/equipments of the SWRO plant. Four unit technologies (UTs) are then incorporated into CT2 and each UT has its own technical target; UT1 focuses on the development of SWRO desalination system integration and optimization technology in terms of energy saving; UT2 and 3 work to develop high performance RO...

In the present study, the feasibility of a tri-hybrid desalination system for the production of electricity, energy for heating and cooling and water was studied. The tri-hybrid desalination system is a combination of a cogeneration and a desalination system. The system is composed of a generator driven by a gas engine, a gas boiler, a turbo-refrigerator, an absorption refrigerator for cogeneration, and an RO and an MED for the desalination system. The excess heat was calculated based on the electrical, heating and cooling load data and assumed that would be used for the production of water. The quantitative analysis of the product water and the energy consumption rate was compared on a month-by-month basis, and the feasibility of the tri-hybrid desalination system is explained.

A seawater reverse osmosis (SWRO) desalination process has become an alternative technology to solve water shortage problem in the world. Although SWRO is an advanced and useful technology for humanity, there is still unsettled cost effective issue. Therefore, the estimation of operation and maintenance (O&M) costs should be significantly considered before a new construction of SWRO desalination plant. The objective of this feasibility study is to estimate total annual profits (TAP) according to O&M for a new construction of SWRO desalination plant at 9 candidate sites along the shoreline in Korea. The cost estimation model was developed and validated with Fujairah SWRO plant operation data in 2005. As a result, TAPs for the 9 candidate sites were estimated and compared with that of Fujairah SWRO plant. The result reflects that the cost estimation model in this study is able to propose a reasonable range of TAP for a new construction project of SWRO desalination plant in Korea.

Recovery and salt rejection rate, which are directly related to the membrane properties and operating conditions (i.e., feed flow rate, pressure, temperature, and TDS concentration), are two main indicators for evaluating the performance of a reverse osmosis (RO) membrane process. A simple and rapid test with minimum data is inevitably requested to diagnose membrane performance at a certain operating conditions, because experiments at all operating conditions are inefficient and consumable work in the view of cost as well as man-hour. In this study, permeate flow rate and TDS concentration of three kinds of commercial RO membranes were carefully examined under various operating conditions [i.e., feed pressure (45–65 kgf/cm2) and temperature (5–30°C)]. Based on the experimental data, membrane resistance models including temperature and pressure correction factors were developed for the rapid diagnosis of SWRO membrane performances. As a result, the models developed in this study have good agreements betwee...

Desalination offers one of the reasonable alternatives as a solution to water scarcity. Among the desalination technologies, seawater reverse osmosis (SWRO) process becomes increasingly attractive for freshwater supply with comparatively low energy consumption and cost-effective operation. In this study, a benchmark of operating Fujairah SWRO desalination plant in the United Arab Emirates is applied to assess the relative performance of a new and large plant construction in other sites. A process model was developed to simulate the performance of SWRO desalination process and to estimate its operating cost. The developed model was validated using one-year SWRO operation data obtained from Fujairah SWRO desalination plant. Temperature and salinity data were collected from World Ocean Atlas 2005, and then applied to the model to estimate the operating cost under the site-specific conditions of 9 different countries. The results of this study present that the performance of the SWRO desalination process was significantly influenced by feed water concentration (i.e., mainly salinity) and temperature, and that the total operating cost is significantly dependent of the local electricity costs. As a conclusion, World Ocean Atlas data and the benchmark provide a method of comparing the performance of various SWRO desalination systems among different countries. Furthermore the methodology is applicable to simulate the process model with site-specific water quality data and to estimate the operating cost before a new construction of SWRO desalination plant at a target area elsewhere.

At the time being there are several technological designs of membrane-based seawater reverse osmosis (SWRO) pretreatment systems on the desalination market. The abundance of different membrane materials and configurations (pressurized/submerged/inside-out/outside-in etc.) combined with site specific conditions make the unbiased assessment of their general performance a difficult task. In this paper we suggest a data mining method based on the principal component analysis (PCA) to serve as a more systematically logical regression tool on currently available literature data. PCA is a multivariate statistical method that uses a linear transformation for dimension reduction and pattern recognition. The results show how this method can be used effectively in the case of SWRO membrane based pretreatment for both literature data reconciliation and reconstruction, as well as for future data prediction.

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.

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.

The Yeongsan (YS) Reservoir is an estuarine reservoir which provides surrounding areas with public goods, such as water supply for agricultural and industrial areas and flood control. Beneficial uses of the YS Reservoir, however, are recently threatened by enriched non-point and point source inputs. A series of multivariate statistical approaches including principal component analysis (PCA) were applied to extract significant characteristics contained in a large suite of water quality data (18 variables monthly recorded for 5 years); thereby to provide the important phenomenal information for establishing effective water resource management plans for the YS Reservoir. The PCA results identified the most important five principal components (PCs), explaining 71% of total variance of the original data set. The five PCs were interpreted as hydro-meteorological effect, nitrogen loading, phosphorus loading, primary production of phytoplankton, and fecal indicator bacteria (FIB) loading. Furthermore, hydro-meteorological effect and nitrogen loading could be characterized by a yearly periodicity whereas FIB loading showed an increasing trend with respect to time. The study results presented here might be useful to establish preliminary strategies for abating water quality degradation in the YS Reservoir.

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.

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.

Whenever measurements of fecal pollution in coastal bathing waters reach levels that might pose a significant health risk, warning signs are posted on public beaches in California. Analysis of historical shoreline monitoring data from Huntington Beach, southern California, reveals that protocols used to decide whether to post a sign are prone to error. Errors in public notification (referred to here as posting errors) originate from the variable character of pollutant concentrations in the ocean, the relatively infrequent sampling schedule adopted by most monitoring programs (daily to weekly), and the intrinsic error associated with binary advisories in which the public is either warned or not. In this paper, we derive a probabilistic framework for estimating posting error rates, which at Huntington Beach range from 0 to 41%, and show that relatively high sample-to-sample correlations (0.4) are required to significantly reduce binary advisory posting errors. Public mis-notification of coastal water quality can be reduced by utilizing probabilistic approaches for predicting current coastal water quality, and adopting analog, instead of binary, warning systems.