• Membrane Journal
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• v.23 no.6
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• pp.460-468
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• 2013

This study reviewed optimum dosage rate of coagulant and ability to remove dissolved organic carbon without sedimentation in conventional water purification plant. It was confirmed that floc formated by pre-treatment process was broken by impeller of booster pump. Optimum dosage rate of coagulant was 4 mg/L (as PACl 17%) for floc formation through blend, coagulation and after passing through the pump when turbidity of raw water was less than 10 NTU. And average removal rate of dissolved organic carbon was 43% at that time. Maximum removal rate of dissolved organic carbon was 48%, even though coagulation rate was increased gradually until 8 mg/L (as PACl 17%). So removal rate of dissolved organic carbon is not much improved even if dosage rage of coagulant increase. TMP of PVDF (polyvinylidene flouride) pressurized MF process without pre-treatment operated at 0.54 bar and TMP of PVDF pressurized MF process with pre-treatment operated at 0.41 bar.

• Journal of Environmental Science International
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• v.7 no.6
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• pp.761-772
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• 1998

This study was performed to determine the optimum coagulant dosing amount for effective treatment of raw water. The removal rate of turbidity and the variations of water qualities according to various dosage of coagulants such as Alum, PAC and PACS were investigated. The optimum coagulant dosing amount to make the lowest turbidity of water were 35mg/ι t of Alum, 30mg/ι of PAC and 10mg/ι of PACS in case of 5 NTU of raw water turbidity, and 30mg/ι of Alum, 25mg/ι of PAC and 10mg/ι of PACS in case of 10 NTU of that, respectively. The removal rates of turbidity at 4 min. and 8 min. of settling time were 10 and 72% of Alum, 44 and 62% of PAC and 25 and 55% of PACS in case of 5 NTU, and 52 and 70% of Alum, 90 and 95% of PAC and 10 and 28% of PACS in case of 10 NTU, respectively. Judging from the settling capability of floc., the reaction time of floe. formation and removal efficiency of turbidity, PAC was evaluated as more effective coagulant than Alum and PACS. Also PAC was regarded as the most effective coagulant when the water supply was changed sharply and the fluctuation of the surface loading occured with wide and sharp in settling basin. pH and alkalinity of the water were decreased with increasing coagulants dosage. But pH and alkalinity were not decreased below 5.8 which is the standard for drinking water quality, and 10mg/ι which is the limit concentration of floc. breakage, respectively. Residual Al of the treated water was decreased with increasing coagulants dosage in case of 5 and 10NTU of raw water turbidity. $KMnO_4$ consumption of the water was decreased with increasing coagulants dosage. The reduction rate of $KMnO_4$ consumption at the optimum coagulants dosage were 39% of Alum. 18% of PAC and 11% of PACS in case of 5 NTU of raw water turbidity, and 42% of Alum, 27% of PAC and 36% of PACS in case of 10 NTU of that, respectively. Any relationship was not found between the removal rate of turbidity and KMnO$_4$ consumption. TOC of the water was a bit decreased with increasing coagulants dosage up to 30mg/ι but not changed above 30mg/ι of coagulants dosage. The degree of TOC reduction was increased in the order of Alum, PAC and PACS treatment. Zeta potential of the colloidal floe. at the optimum coagulants dosage was in the range of -20~-15mV in case of 5 NTU of raw water turbidity and 0~0.5mV in case of 10 NTU of that. respectively. Although the kinds and dosages of coagulants were different, zeta potential range were fixed under the conditions of the best coagulation efficiency.

• 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.

• 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 the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.369-376
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• 2015

Chemicals are injected in order to remove a variety of organic substances contained in the water purification plant influent. It can be determined with measuring sedimentation turbidity 4~7 hours later, whether the chemical dosage rate is proper or not, which make the real-time feedback control impossible. In addition, manual operation in accordance with the Jar-Test carried out in the laboratory and the operator's experience may cause the experimental and human error by the changes of organic characteristics and water quality. Especially at night ad weekend, the rate have been determined only by the operator judgment owing to environment engineer's absence. Therefore, the decision of optimal chemical dosage rate using proposed intelligent control algorithm is expected to result in real-time injection and cost reduction.

• Membrane and Water Treatment
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• v.13 no.1
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• pp.15-20
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• 2022

The continuous industrial growth increases the volume of pollutants discharged into the water, which induces Cyanobacteria in the receiving bodies. The removal of various cyanobacteria such as Microcystis, Anabaena, and Oscillatoria was explored to analyze their removal characteristics using different chemical and mineral coagulants. The chemical coagulants, including poly aluminium chloride (PACl), Alum, and mineral coagulants such as Loess and Illite, were tested to remove selected cyanobacteria. Results indicated that the removal rate increased with coagulant dosage regardless of the type of coagulant. The removal of selected cyanobacteria using chemical coagulant was found in the order: Microcystis > Anabaena > Oscillatoria. The PACl coagulant showed the most efficient removal rate for Microcystis, Anabaena, Oscillatoria. Removal rate of Microcystis conducted by PACl showed 92% at 100,000 cells/mL and 98.4% at 1,000,000 cells/mL whereas Illite showed lower 70% and Loess showed lower 50% in both 100,000 cells/mL and 1,000,000 cells/mL. The removal rate of Anabaena and Oscillatoria by PACl and Alum was higher 80%, while the other coagulants exhibited lower than 75% at 1,000,000 cells/mL. The removal rate of Oscillatoria by PACl was 80.1%, while the other coagulants exhibited lower than 70% at 1,000,000 cells/mL. Moreover, the mineral coagulants showed better removal efficiency at a higher concentration than low concentration during experiments. Therefore, removing cyanobacteria from water streams can be improved through coagulation by selecting a specific coagulant for a particular type of algae.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.3
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• pp.357-362
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• 2005

Poly-${\gamma}$-glutamic acid (${\gamma}-PGA$), which is extracted from fermented soybeans, is a high molecular weight, adhesive, and negatively charged(anionic) polymer. Recently, ${\gamma}-PGA$ has gained attention due to its potential as polymer. The objectives of this study were to examine the applicability of ${\gamma}-PGA$ as a coagulant and/or a coagulant aid, to evaluate the efficiency of ${\gamma}-PGA$ for the removal of Organic and Ammonium substance in wastewater treatment. The effect of coagulation was evaluated for the removal of SS and organic matter using poly aluminum chloride(PACI) as well as newly developed ${\gamma}-PGA$. The maximum COD removal rate of 63% and the SS of 78% were occurred at the dosage of 50mg/L ${\gamma}-PGA$ only. The most effective removal for particulate and organic matter was occured when both PACI and ${\gamma}-PGA$ were applied at the rate of 20:1(10mg/L PACI and 0.5mg/L ${\gamma}-PGA$). When mixed with PACI, only small portion of ${\gamma}-PGA$ was enough to improve removal efficiencies of organic and particulate matter in wastewater. This result showed the positive potential of ${\gamma}-PGA$ as a new coagulant materials for wastewater treatment.

• Journal of Environmental Science International
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• v.23 no.4
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• pp.715-722
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• 2014

Effects of coagulation types on flocculation were investigated by using a photometric dispersion analyzer (PDA) as an on-line monitoring technique in this study. Nakdong River water were used and alum and ferric chloride were used as coagulants. The aim of this study is to compare the coagulation characteristics of alum and ferric chloride by a photometric dispersion analyzer (PDA). Floc growing rates ($R_v$) in three different water temperatures ($4^{\circ}C$, $16^{\circ}C$ and $30^{\circ}C$) and coagulants doses (0.15 mM, 0.20 mM and 0.25 mM as Al, Fe) were measured. The floc growing rate ($R_v$) by alum was 1.8~2.8 times higher than that of ferric chloride during rapid mixing period, however, for 0.15 mM~0.25 mM coagulant doses the floc growing rate ($R_v$) by ferric chloride was 1.1~2.3 times higher than that of alum in the slow mixing period at $16^{\circ}C$ water temperature. Reasonable coagulant doses of alum and ferric chloride for turbidity removal were 0.1 mM (as Al) and 0.2 mM (as Fe), respectively, and the removal efficiency of those coagulant doses showed 94% for alum and 97% for ferric chloride. The appropriate coagulant dose of alum and ferric chloride for removing dissolved organic carbon (DOC) showed about 0.3 mM (as Al, Fe) and at this dosage, DOC removal efficiencies were 36% and 44%, and ferric chloride was superior to the alum for removal of the DOC in water.

• Journal of Environmental Health Sciences
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• v.19 no.2
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• pp.1-9
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• 1993

In public water supply systems, Alum and/or PAC being used as a coagulant. It is well known that their use increased frequently the concentration of residual aluminum in filtered water upon operating conditions. This study was conducted to find the optimum conditions that both the concentration of residual aluminum and turbidity are minimized by changing such factors as pH, temperature, alum dosage, mixing rate, alkalinity and hardness. The results can be summarized as follows: The pH values for the minimum concentration of residual aluminum and turbidity as a given experimental condition were found at pH 6 and pH 7 respectively, the apparent clarity was best at pH 8. The floc settling rate was the greatest at pH 6.5, but the turbidity was high at the same condition. The more alum dosage, the higher the concentration of residual aluminum. However the alum dosage less than 15 mg/l tend to decrease in turbidity. Restabilization and enmeshment occurred near 15 mg/l and 20 mg/l of alum dose respectively. With the increase of mixing rate (rapid and slow), the concentration of residual aluminum and turbidity are increased and the same trend was found in increment of mixing time. At low water temperature, the concentration of residual aluminum was decreased, but turbidity was increased. It was confirmed that alkalinity had an effect on the coagulation efficiency, but hardness did not.

• Journal of Korean Society of Water and Wastewater
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• v.7 no.2
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• pp.39-46
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• 1993

In this experimental study, it is concerned to develop a simple equation using jar-test results in order to predict the optimum dosage of coagulant, PAC(polyaluminum chloride). Considering the relationships with the reactions of coagulation and flocculation, the four independent variables (e.g. turbidity, temperature, pH and alkalinity) are selected out of many parameters and they are put into calculations to develop an equation by means of multi-regression method. As the result, the dosing rate of PAC is proportional to turbidity, pH and alkalinity, but in inverse to temperature. And the developed equation is as follow, $$D_c=\frac{3.2{\cdot}T^{0.37}{\cdot}A^{0.04}{\cdot}P^{0.5}}{t^{0.1}},\;(R^2=0.9443)$$ And also, comparing between the estimated value from the equation and the real dosing rate in the plant, Kwangam and Tdukdo, during 1988~1991, it is represented an agreement having a relative error of 16.4%, 17.8%, respectively.