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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.

Land use and cover is one of the important factors that influence water flow within a watershed. Alteration of land use through time affects hydrological processes as well as the water budget in the watershed. In analyzing these processes that occur within basins and watershed, Soil and Water Assess...

Despite a growing awareness of the problems associated with cyanobacterial blooms in rivers, and particularly in regulated rivers, the drivers of bloom formation and abundance in rivers are not well understood. We developed a Bayesian hierarchical model to assess the relative importance of predictors of summer cyanobacteria abundance, and to test whether the relative importance of each predictor varies by site, using monitoring data from 16 sites in the four major rivers of South Korea. The results suggested that temperature and residence time, but not nutrient levels, are important predictors of summer cyanobacteria abundance in rivers. Although the two predictors were of similar significance across the sites, the residence time was marginally better in accounting for the variation in cyanobacteria abundance. The model with spatial hierarchy demonstrated that temperature played a consistently significant role at all sites, and showed no effect from site-specific factors. In contrast, the importance of residence time varied significantly from site to site. This variation was shown to depend on the trophic state, indicated by the chlorophyll-a and total phosphorus levels. Our results also suggested that the magnitude of weir inflow is a key factor determining the cyanobacteria abundance under baseline conditions.

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.

Pressure-retarded osmosis (PRO) is viewed as a highly promising renewable energy process that generates energy without carbon emissions in the age of the climate change regime. While many experimental studies have contributed to the quest for an efficiency that would make the PRO process commercially viable, computational modeling and simulation studies have played crucial roles in investigating the efficiency of PRO, particularly the concept of hybridizing the PRO process with reverse osmosis (RO). It is crucial for researchers to understand the implications of the simulation and modeling works in order to promote the further development of PRO. To that end, the authors collected many relevant papers and reorganized their important methodologies and results. This review, first of all, presents the mathematical derivation of the fundamental modeling theories regarding PRO including water flux and concentration polarization equations. After that, those theories and thermodynamic theories are then applied to depict the limitations of a stand-alone PRO process and the effectiveness of an RO-PRO hybridized process. Lastly, the review diagnoses the challenges facing PRO-basis processes which are insufficiently resolved by conventional engineering approaches and, in response, presents alternative modeling and simulation approaches as well as novel technologies.

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.

Bacteria are a primary contaminant in natural surface water. The instream concentration of fecal coliform, a potential indicator of pathogens, is influenced by meteorological conditions and land-use characteristics. However, the relationships between these conditions and fecal coliforms are not fully understood. Furthermore, the sources of large variability in fecal coliform counts, e.g., temporal or spatial sources, remain unexplained, especially at large scales. This study proposes the use of Bayesian overdispersed Poisson models, whereby the combined effects of temperature, rainfall, and land-use characteristics on fecal coliform concentration are quantified with predictive uncertainty, and the sources of variability in fecal coliform concentration are assessed. The models were developed using 8-year weekly observations of fecal coliforms obtained from the Wachusett Reservoir watershed in Massachusetts, USA. The results highlight the importance of interactions among meteorological and land-use characteristics in controlling the instream fecal coliform concentration; the increase in fecal coliform concentration with temperature increase was more drastic when rainfall occurred. Also, the responses of fecal coliforms to temperature increases were more pronounced in forest-dominated than in urban-dominated areas. In contrast, the fecal coliform concentration increased more rapidly with rainfall increases in urban-dominated than in forest-dominated areas. The models also demonstrate that among the sources of variability, the monthly component made the most significant contribution to the variability in fecal coliform concentrations. Our results suggest that seasonally dependent processes, including surface runoff, are critical factors that regulate fecal coliform concentration in streams.

© 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.

Providing high-resolution monitoring data is essential in promoting decision-making activities for surface water quality protection such as scientific modeling and data analysis. In this study, statistical models using multiple linear regression (MLR) were developed to estimate Chlorophyll-a (Chl-a) and total suspended solid (TSS) concentrations in a mesotrophic reservoir, the Yeongam Reservoir in Korea, from satellite observations. Two types of satellite data that covered different spectral regions, for wavelengths in 412–865 nm (for the Geostationary Ocean Color Imager) and those in 405–14,385 nm (for the Moderate Resolution Imaging Spectroradiometer), were used as inputs for statistical models, after bias correction. The MLR models for Chl-a and TSS were initially constructed and evaluated with 39 image data-sets obtained during 2011–2014. Subsequently, they compared with their corresponding algorithms that were developed under different environmental settings as well as the CE-QUAL-W2 model, a...

Fecal coliforms are indicators of pathogens and thereby, understanding of their fate and transport in surface waters is important to protect drinking water sources and public health. We compiled fecal coliform observations from four different sites in the USA and Korea and found a seasonal variability with a significant connection to temperature levels. In all observations, fecal coliform concentrations were relatively higher in summer and lower during the winter season. This could be explained by the seasonal dominance of growth or die-off of bacteria in soil and in-stream. Existing hydrologic models, however, have limitations in simulating the seasonal variability of fecal coliform. Soil and in-stream bacterial modules of the Soil and Water Assessment Tool (SWAT) model are oversimplified in that they exclude simulations of alternating bacterial growth. This study develops a new bacteria subroutine for the SWAT in an attempt to improve its prediction accuracy. We introduced critical temperatures as a parameter to simulate the onset of bacterial growth/die-off and to reproduce the seasonal variability of bacteria. The module developed in this study will improve modeling for environmental management schemes.

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.

Reverse osmosis (RO) desalination of 35,000 ppm seawater consisting of sodium and chlorine ions with water was simulated using molecular dynamics. In this study, RO simulations were performed at different pressures using carbon nanotube (CNT) membranes having varying pore diameters (8–14 A). Results showed that a CNT membrane allowed high water fluxes because of the presence of a low energy barrier for water–carbon interactions, with continuous and ordered water chains observed inside the CNTs. The investigations into the ion rejection capability of CNT membranes revealed that (6, 6) CNTs could provide high rejection rates (>95%). The rejection of ions was mainly due to the presence of a high energy barrier caused by removing the hydrating water molecules necessary for ions to pass through the narrow CNT pore. The desalination performance of (6, 6) CNT membranes and conventional polymeric membranes was then compared. It was found that CNT membranes have a higher normalized flux and comparable ion ...

The pressure retarded osmosis (PRO) process has been considered as an alternative and renewable technology to generate electricity from mixing two solutions of different salinities. However, improving the osmotic performance of semi-permeable membrane is still a major challenge in the PRO system. Therefore, thin-film nanocomposite (TFN) membrane was synthesized by using carbon nanotubes (CNT)-embedded-polyethersulfone (PES) supporting layer and polyamide active layer in this study. The prepared membranes were further employed in the PRO process to harvest energy from saline water. The water flux increase of the TFN membrane was promoted by CNT-induced porosity and the hydrophilicity of the support layer as well as by the chemical etching of the active layer. The water flux and maximum power density of the developed TFN membrane was found to be 87% (averaged from 2 bar to 10 bar) and 110% greater than for bare thin-film composite (TFC) membranes, respectively. Furthermore, the TFN membrane preparation could easily be scaled up using conventional fabrication methods with less than 2% additional material cost. Therefore, this finding could contribute to the commercialization of sustainable energy generation by utilizing the tremendous potential of fresh- and salt-water mixing.

Statistical models play an important role in elucidating the dynamic behaviors of surface water quality, given limited data on a large scale. In this study, we examine alternative approaches to develop regression models that predict fecal coliform (FC) concentrations in a river using different methods for selecting important variables provided by a self-organizing map (SOM). The raw data used as input to the SOM included 11 water quality, 6 meteorological, and 7 land use parameters that were monitored along the Yeongsan River in Korea on various time scales (from daily to half a decade) during 1996–2008. In both test and validation data sets, (multiple) regressions using backward elimination were compared against regression models via forced entry, which included a set of ranked variables simultaneously based on four indices in the SOM (i.e. structuring index, relative importance, cluster description, and Spearman’s rank correlation). Results showed that the SOM effectively illustrated the complex...

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...

Summary To control algal blooms, the stressor–response relationships between water quality metrics, environmental variables, and algal growth need to be better understood and modeled. Machine-learning methods have been suggested as means to express the stressor–response relationships that are found when applying mechanistic water quality models. The objective of this work was to evaluate the efficiency of regression trees in the development of a stressor–response model for chlorophyll-a (Chl-a) concentrations, using the results from site-specific mechanistic water quality modeling. The 2-dimensional hydrodynamic and water quality model (CE-QUAL-W2) model was applied to simulate water quality using four-year observational data and additional scenarios of air temperature increases for the Yeongsan Reservoir in South Korea. Regression tree modeling was applied to the results of these simulations. Given the well-expressed seasonality in the simulated Chl-a dynamics, separate regression trees were developed for months from May to September. The regression trees provided a reasonably accurate representation of the stressor–response dependence generated by the CE-QUAL-W2 model. Different stressors were then selected as split variables for different months, and, in most cases, splits by the same stressor variable yielded the same correlation sign between the variable and the Chl-a concentration. Compared to physical variables, nutrient content appeared to better predict Chl-a responses. The highest Chl-a temperature sensitivities were found for May and June. Regression tree splits based on ammonium concentration resulted in a consistent trend of greater sensitivity in the groups of samples with higher ammonium concentrations. Regression tree models provided a transparent visual representation of the stressor–response relationships for Chl-a and its sensitivity. Overall, the representation of relationships using classification and regression tools can be considered a useful approach to assess the state of aquatic ecosystems and effectively determine significant stressor variables.

When stormwater runoff flows into a constructed wetland, the water level changes inside, and the volume of the wetland changes accordingly. In this study, the relationship between pollutant removal and water depth flowrate changes was analyzed with velocity phase analysis, using the concepts of horizontal velocity and vertical velocity. A constructed wetland located in an agricultural area was used for the velocity phase analysis. Analysis results revealed that all four ponds and Phases I and III accounted for over 90% of the pollutant load. In particular, Phase III, where vertical and horizontal velocities were reduced, was responsible for approximately twice the load on average. The reason for the highest load in Phase III was due to the inflow of contaminants into the constructed wetland through the first flush effect occurred at the time when the flow rate decreased due to the difference in runoff strength. Therefore, it is necessary to maximize Phases I and III in the velocity phase when designing multi-stage wetlands to make the flow of water more natural. Furthermore, considering pollutant load levels, a design review is needed to expand the size of downstream wetlands, so that they can optimize water quality management functions.

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.

The cycle of occurrence of extreme weather event is getting shorter. To cope with this situation, various carbon abatement policies are being established, and related technologies are being studied. Naturally, no-carbon growth through sustainable energy generation is getting popular. One of such sustainable energy generating technologies is Pressure-retarded osmosis (PRO), which is a membrane-based energy generating process worked by salinity gradient. The very first PRO pilot plant was built by Statkraft in Norway. The pilot plant project checked the feasibility of the PRO plant, which we thought was theoretically possible, and acquired many meaningful results. However, it was found that a stand-alone PRO process is premature yet to be commercialized due to the economic constraints and environmental constraints of status quo. Consecutive to the challenge of Statkraft, various projects regarding PRO process have been conducted. Such projects specifically focused on solving the problems of economic and environmental constraints in PRO process by considering seawater and river composition, and geographical characteristics. To do so, the characteristics of a membrane process have been mainly considered to minimize the undesirable phenomena such as internal concentration polarization. In the same context, the pretreatment step of PRO process has been emphasized in PRO process, to get rid of the unwanted components of raw water. On the other hand, to raise the efficiency of energy generation, hybridization strategy also has been attempted. By hybridizing PRO process with Seawater Reverse Osmosis (SWRO), the energy generation efficiency of PRO process is enhanced excellently. In addition, geographical information system, a concept that includes osmotic power potential, seawater cycle, and physiochemical variables, can play an important role in selecting a process site. Although we have still a long way to go for the optimization of PRO process, PRO field can be a promising field, which can realize the truly eco-friendly and sustainable energy generation, if a long-term development is entailed.

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.

Pressure retarded osmosis (PRO) is a promising membrane-based process for producing clean and renewable energy. Since the major driving force is the salinity gradient between the feed and draw solutions, PRO can operate without a large environmental footprint. However, the performance of PRO can be severely limited by fouling, with organic fouling commonly deemed the main factor influencing PRO performance, since even a small amount of organic foulants can cause a significant flux decline. In spite of its importance, however, few studies have focused on PRO fouling. Therefore, the objectives of this study were to investigate the effect of hydraulic pressure as an influencing factor and to adjust the feed solution pH in order to alleviate fouling in the PRO process. Alginate was chosen as the model foulant due to its common existence in feed water. Based on our results, a higher hydraulic pressure caused an increase in the reverse solute flux, such that organic fouling became aggravated. In additio...

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 paper describes the effects of weir construction on water quality in the Yeongsan (YS) River. In general, weirs affect aquatic environments of rivers and streams by interrupting natural water flow. To identify changes in water quality before and after weir construction, analysis of variance and autocorrelation tests were conducted on data from four monitoring stations. Seasonal variations in suspended solids (SS), biochemical oxygen demand (BOD5), chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP), and pH were analyzed using data from six years of monitoring. No significant changes in mean BOD5 or COD followed the construction of weirs. However, mean TN and TP were changed significantly during and after construction. Moreover, SS and pH changed significantly during construction, and TN and TP concentrations were slightly improved after weir construction. However, continuous monitoring and analysis of water quality changes in each weir are required to prevent environmenta...

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.

A hybrid forward osmosis (FO)/crystallization/reverse osmosis (RO) process for seawater desalination was proposed, and the theoretical analysis of the process was conducted. When the FO unit is considered as the main desalination unit, the crystallization and RO units can be regarded as a draw solute recovery process. First, in the FO process, fresh water is extracted from seawater and permeates into draw solution. This diluted draw solution is cooled down in the crystallization process and the draw solute is precipitated up to the saturation at low temperature. As a result, the feed stream of the RO process has lower concentration, and consequently, total energy consumption is expected to be reduced. In order to apply the proposed process in practice, the selection of suitable draw solute should be carefully determined. In the present work, five substances were suggested as draw solutes in the proposed system: ammonium oxalate, ammonium aluminum sulfate, sodium periodate, sodium phosphate and sodium sulfate. Based on properties of the substances, total energy consumption was analyzed for each draw solute. The total energy was calculated by the sum of cooling energy in crystallization process and pumping energy in RO process. Through the hybridization of these three unit processes, the energy requirement for fresh water production can be reduced to 2.15 kW h/m3. Thus, it is concluded that the proposed process can be highly competitive.

In this study, unlike the previous researches, the pretreatment equipment composed of a 40- μm disk filter and a hollow fiber ultra-filtration (UF) membrane was constructed. The performances of the pretreatment facilities were analyzed on the basis of 5-week-long continuous experiments using sea water. The results confirmed that the newly constructed pretreatment equipment could be used for the pretreatment of sea water reverse osmosis as evidenced by silt density index15 values below two for a long period and measured turbidities of about 0.4 NTU. The membrane fouling could be removed by using chemical enhanced backwash. Trans-membrane pressure and the permeability could be returned to the initial conditions. It reveals that UF membrane performances of the pretreatment were dependent on the sea water conditions and operating conditions.

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 thorough investigation of membranes as well as their transport and material properties is a key to understanding the governing principles and unresolved issues of membrane processes. Through molecular dynamics (MD) simulations, static and dynamic properties of membrane separation systems may be investigated on a molecular level. By reviewing over 70 articles, this paper aims to highlight the usefulness of applying molecular dynamics in membranes (MDM) in order to broaden our knowledge of membrane-based water treatment processes. Here, the theoretical foundations of classical MD are described together with the results that are obtainable from MDM simulations. By compiling results from published works, we emphasize the ability of MD to determine membrane transport and material properties from simulations. The authors conclude by suggesting the further use of MDM for prospective research areas pertaining to membrane-based water treatment processes.

Shale gas has the potential to significantly change the way of the world`s energy use. However, there are increasing concerns on environmental problems, particularly with respect to water use and wastewater treatment. This paper highlights issues related to shale gas water management and technologies currently used to address them. It also presents perspectives of emerging technologies for the treatment of shale gas wastewater, including forward osmosis (FO) and membrane distillation (MD).

Nonpoint source (NPS) pollution is widely recognized as a major source affecting the water quality deterioration in rivers, lakes, and marine environments. Many studies about the relations between NPS pollutants and solid matters from drainage area have been carried out in the area of stormwater management. This study collected stormwater and soil samples from a drainage area in Korea; the particle size distributions (PSDs) were then analyzed during four storm events. The results indicate that the PSDs of fine and medium silt in the stormwater are related to the soil component of the drainage area. In addition, solid matter was strongly related to NPS pollutant discharges such as total nitrogen and total phosphorus during stormwater runoff. Therefore, to design an NPS management facility, the PSD from the drainage area should be considered. It is expected that this study can be applied to the designs of settling ponds used to remove particles from stormwater runoff.

Nonpoint source pollutions discharged with stormwater runoff during rainfall events degrade public waterbodies. Because combined sewer overflows (CSOs) especially affect public waterbodies, necessary measures must be taken for CSOs. Therefore, this study treated CSOs using the ultra-rapid coagulation (URC) process. More than 50% of the study site was comprised of an industrial area, followed by forest, farmland and residential areas at 21.3, 2.6, and 23.5%, respectively. The 30,000 ton capacity URC process was used to treat CSOs generated from the catchment. Monitoring was conducted over 8 rainfall events, and the samples were analyzed for pollutant parameters such as total suspended solids (TSS), biochemical oxygen demand (BOD), chemical oxygen demand (CODcr), total nitrogen (TN), total phosphorus (TP), and heavy metals. At the beginning of the rainfall, the first flash effect was observed, but was not observed 20 min later. The concentration of TSS and BOD increased as the rainfall intensity be...

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.