• Journal of Institute of Control, Robotics and Systems
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• v.3 no.6
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• pp.644-651
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• 1997

In the water purification plant, chemicals are injected for quick purification of raw water. It is clear that the amount of chemicals intrinsically depends on water quality such as turbidity, temperature, pH and alkalinity. However, the process of chemical reaction to improve water quality (e.g., turbidity) by chemicals is not yet fully clarified nor quantified. The feedback signal in the process of coagulant dosage, which should be measured (through the sensor of the plant) to compute the appropriate amount of chemicals, is also not available. Most traditional methods focus on judging the conditions of purifying reaction and determine the amounts of chemicals through manual operation of field experts using Jar-test data. In this paper, a systematic control strategy is proposed to derive the optimum dosage of coagulant, PAC(Polymerized Aluminium Chloride), using Jar-test results. A neural network model is developed for coagulant dosing and purifying process by means of six input variables (turbidity, temperature, pH, alkalinity of raw water, PAC feed rate, turbidity in flocculation) and one output variable, while considering the relationships to the reaction of coagulation and flocculation. The model is utilized to derive the optimum coagulant dosage (in the sense of minimizing turbidity of water in flocculator). The ability of the proposed control scheme validated through the field test has proved to be of considerable practical value.

• Korean Journal of Food Science and Technology
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• v.27 no.3
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• pp.318-323
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• 1995

To improve wastewater treatment in a confectionery factory and to optimize chemical coagulation process, this study was performed. $COD_{Mn}$ and total solid of untreated wastewater were $200{\sim}820ppm\;and\;860{\sim}1350ppm$, respectively. Composition of total solid was sugar 40%, protein 10%, hexane-soluble 20%, and ash 30%. Turbidity at 650 nm and the amount of suspended solid (SS) showed correlation, thus turbidity could be used for the on-line measurement of SS. The most effective combination of coagulants for the removal of $COD_{Mn}$ and SS was that of $Al_2(SO_4)_3\;and\;Ca(OH)_2$. The optimal concentration of $Al_2(SO_4)_3\;and\;Ca(OH)_2$ was 480 ppm and 200 ppm, respectively. Optimal retention time of wastewater for $Al_2(SO_4)_3$ addition $Ca(OH)_2$ addition : flocculation was 2 : 2 : 10 min. Multiple treatment of $Al_2(SO_4)_3:Ca(OH)_2$ overcame coagulation inhibition by gelatin and detergent, and addition of microbial sludge reduced it.

• Journal of Korean Society on Water Environment
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• v.24 no.6
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• pp.682-689
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• 2008

The purpose of this study was to find out the variation between molecular size distribution (MSD) of natural organic matter (NOM) in raw waters after different water treatment processes like conventional process (coagulation, flocculation, filtration) followed by advanced oxidation process (ozonation, GAC adsorption). The MSD of NOM of Suji pilot plant were determined by Liquid Chromatography-Organic Carbon Detection (LC-OCD) which is a kine of high-performance size-exclusion chromatography (HPSEC) with nondispersive infrared (NDIR) detector and $UV_{254}$ detector. Five distinct fractions were generally separated from water samples with the Toyopearl HW-50S column, using 28 mmol phosphate buffer at pH 6.58 as an eluent. Large and intermediate humic fractions were the most dominant fractions in surface water. High molecular weight (HMW) matter was clearly easier to remove in coagulation and clarification than low molecular weight (LMW) matter. Water treatment processes removed the two largest fractions almost completely shifting the MSD towards smaller molecular size in DW. No more distinct variation of MSD was observed by ozone process after sand filtration but the SUVA value were obviously reduced during increase of the ozone doses. UVD results and HS-Diagram demonstrate that ozone induce not the variation of molecular size of humic substance but change the bond structure from aromatic rings or double bonds to single bond. Granular activated carbon (GAC) filtration removed 8~9% of organic compounds and showed better adsorption property for small MSD than large one.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.55 no.1
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• pp.10-16
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• 2022

Interest in effluent treatment is currently increasing and the use of polymetric coagulants is considered as a pretreatment of physical filtration prior to effluent discharge to increase solids recovery. A jar test evaluated effluent treatment efficiency of polymeric coagulants for semi-recirculating aquaculture systems. The particle coagulation efficiency and distribution were evaluated at different polymer dosages in freshwater and seawater effluents. The polymer was added at 0.005-0.08 mL/g of total suspended solids (TSS) in the effluents. TSS in the supernatant after coagulation decreased with increasing polymer dose in the freshwater, while showing no corresponding changes with dose in the seawater. However, in all treatments for both effluents, the removal efficiency was above 90%, regardless of the dose in the tested range. Both the De Brouckere Mean Diameter (DBMD) and volumetric median diameter (VMD) were all above 100 ㎛ in the freshwater effluent. In the seawater effluent, the particle size appeared to be larger than that in freshwater, ranging from 400-1,000 ㎛ for both DBMD and VMD. Considering that the typical pore size of physical filtration in aquaculture is between 60 and 200 ㎛, the use of polymers is expected to improve the practicality of physical filtration for efficient treatment.

• Journal of Korean Society of Environmental Engineers
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• v.35 no.3
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• pp.171-178
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• 2013

In this study, the sludge that occurs in the initial operation of coagulation system developed for the treatment of CSOs were returned to the flocculation reactor. The purposes of this study were to analyze the Characteristics of flocs that are generated through the recycling sludge and settling characteristics of sludge, and to evaluate the possibility that high concentrations of particulate matter in the initial inflow of CSOs could be used as an weighted coagulant additive. As a result, the concentration of treated CSOs pollutants at the beginning of the CSOs influent with a large amount of particulate matter over 20 ${\mu}m$ was low, after gradually increasing the concentrations of them. The flocs generated from the sludge return were similar in size compared to flocs generated through injection of micro sands, and settling velocity in case of return sludge injection was decreased from 55.1 cm/min to 21.5 cm/min. SVI value of the sludge accumulated at the bottom of the sedimentation tank was 72, and settled sludge volume decreased rapidly due to the consolidation of sludge to the time it takes to 10 minutes. these mean that sludge used for recycling has good settling characteristic. A condition of returned sludge which is 0.1% return of 0.3% extraction was formed in the balance of settlement and extraction. In this case, This condition was to be adequate to maintain the proper concentration such as 100~200 mg/L of TS and 50~100 mg/L of VS in the flocculation reactor. The usage of the return sludge containing particulate matters of CSOs as an weighted coagulant additive was able to secure a stable treated water quality despite the change of influent water quality dynamically. Furthermore, it can be expected to reduce the alum dosage along with the sludge production.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.317-320
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• 1997

In the water purification plant, chemicals are injected for quick purification of raw water. It is clear that the amount of chemicals intrinsically depends on the water quality such as turbidity, temperature, pH and alkalinity etc. However, the process of chemical reaction to improve water quality by the chemicals is not yet fully clarified nor quantified. The feedback signal in the process of coagulant dosage, which should be measured (through the sensor of the plant) to compute the appropriate amount of chemicals, is also not available. Most traditional methods focus on judging the conditions of purifying reaction and determine the amounts of chemicals through manual operation of field experts or jar-test results. This paper presents the method of deriving the optimum dosing rate of coagulant, PAC(Polymerized Aluminium Chloride) for coagulant dosing process in water purification system. A neural network model is developed for coagulant dosing and purifying process. The optimum coagulant dosing rate can be derived the neural network model. Conventionally, four input variables (turbidity, temperature, pH, alkalinity of raw water) are known to be related to the process, while considering the relationships to the reaction of coagulation and flocculation. Also, the turbidity in flocculator is regarded as a new input variable. And the genetic algorithm is utilized to identify the neural network structure. The ability of the proposed scheme validated through the field test is proved to be of considerable practical value.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.1
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• pp.78-91
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• 2005

Performance limiting factors (PLFs) derived from 161 drinking water treatment plants (DWTPs), assessed by International Technical Diagnosis & Assistance Center, were analyzed and evaluated in more detail in this study. In order to conduct study, 161 DWTPs were divided into five categories depending on their capacity, and into twelve groups according to processes and facilities. From the results of analysis, PLFs and their distribution ratio derived from each category were significantly different. Filtration was the most important performance limiting process in all DWTPs of five categories, and the PLFs in filtration were backwashing velocity, media configuration, bed depth, and formation of mud-ball. The PLFs in coagulation-flocculation process were found out to be coagulant dosage, mixing speed, mechanical problems, and others in the order of frequency of occurrence. Also, insufficient disinfection ability that is resulted from insufficient hydraulic detention time and improper chlorine dose and injection point, is the most significant among PLFs in a clear well. In the case of sedimentation, inappropriate baffle structure and excessive upward velocity were PLFs. In addition, the results showed that high turbid water and low alkalinity in a rainy season, ferric and manganese ions, and ammonia nitrogen have been contributed significantly on the performance of DWTPs.

• Journal of Korean Society of Water and Wastewater
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• v.26 no.6
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• pp.807-813
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• 2012

Flocculation and flotation are used as pretreatment steps prior to the reverse osmosis (RO) process. During seawater treatment, high temperature can change the water chemistry of seawater during the process of coagulation. It also affects bubble volume concentration (BVC) and bubble characteristics. Coagulants such as alum and ferric salts at $40^{\circ}C$ can also change flux rates in the seawater reverse osmosis (SWRO) process. In this study, the bubble characteristics in dissolved air flotation (DAF), used as a SWRO pretreatment process, were studied in synthetic seawater at $20^{\circ}C$ and $40^{\circ}C$. The flux of an RO membrane was monitored after dosing the synthetic seawater with coagulants at different temperatures. Results showed that BVC increases as the operating pressure increases and as the salt concentration decreases. The bubble size released at $40^{\circ}C$ is far smaller than that at $20^{\circ}C$The addition of a ferric salt is effective for turbidity removal in synthetic seawater at $20^{\circ}C$; it is more effective than alum. When synthetic seawater was dosed with a ferric salt, the RO membrane flux increased by 27 % at $40^{\circ}C$.

• Journal of Korean Society of Water and Wastewater
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• v.34 no.5
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• pp.357-371
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• 2020

Microplastics have become a rising issue in due to its detection in oceans, rivers, and tap water. Although a large number of studies have been conducted on the detection and quantification in various water bodies, the number of research conducted on the removal and treatment of microplastics are still comparatively low. In the current research, the inflow and removal of microplastics were investigated for various drinking water treatment plants around the world. Addition to the investigation of filed research, a survey was also conducted on the current research trend on microplastic removal for different treatment processes in the drinking water treatment plants. This includes the researches conducted on coagulation/flocculation, sedimentation, dissolved air flotation, sand filtration and disinfection processes. The survey indicated mechanisms of microplastic removal in each process followed by the removal characteristics under various conditions. Limitations of current researches were also mentioned, regarding the gap between the laboratory experimental conditions and field conditions of drinking water treatment plants. We hope that the current review will aid in the understanding of current research needs in the field of microplastic removal in drinking water treatment.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.282-285
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• 1996

In the water purification plant, the raw water is promptly purified by injecting chemicals. The amount of chemicals is directly related to water quality such as turbidity, temperature, pH and alkalinity. At present, however, the process of chemical reaction to the turbidity has not been clarified as yet. Since the process of coagulant dosage has no feedback signal, the amount of chemical can not be calculated from water quality data which were sensed from the plant. Accordingly, it has to be judged and determined by Jar-Test data which were made by skilled operators. In this paper, it is concerned to model and control the coagulant dosing process using jar-test results in order to predict optimum dosage of coagulant, PAC(Polymerized Aluminium Chloride). The considering relations to the reaction of coagulation and flocculation, the five independent variables(turbidity, temperature, pH, Alkalinity of the raw water, PAC feed rate) are selected out and they are put into calculation to develope a neural network model and a fuzzy model for coagulant dosing process in water purification system. These model are utilized to predict optimum coagulant dosage which can minimize the water turbidity in flocculator. The efficacy of the proposed control schemes was examined by the field test.