• Journal of Korean Society of Water and Wastewater
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• v.27 no.5
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• pp.547-554
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• 2013

Chlorine has strong oxidizing power, also it is many advantages over other disinfectants such as the residual characteristic and economic feasibility. However, chlorine also has disadvantages such as creating disinfection by-products of chlorine as THMs. In particular, the most deadly disadvantage of chlorine is that it is extremely poisonous toxins about all alive lives. Disinfection with electrolysis water can be a very useful way Because you do not have to worry about chlorine's dangerous. In this study, we evaluated the potential as a disinfectant, across the evaluating disinfection effect and generating characteristic of by-products. The electrolyzed water could be obtained removal efficiencies of over 99.9 % the coliform by operating condition such as residence time, current density (voltage), the electrode gap. The residual chlorine be generated 10,000 mg/L in current density $1.0A/dm^2$ and residence time of 10 minutes. The residual chlorine concentration was possible to maintain a stable. The by-products generated by high concentration residual chlorine in the reactor such as trihalomethanes, haloaceticacid, chloralhydrate, haloacetonitrile were detected in less than a water quality standards. At the concentration of less than residual chlorine of 1 ppm, the chlorine disinfection by-products be generated most below the detection limit.

• Journal of Korean Society of Water and Wastewater
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• v.33 no.1
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• pp.17-29
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• 2019

This study developed prediction models of chlorine bulk decay coefficient by each condition of water quality, measuring chlorine bulk decay coefficients of the water and water quality by water purification processes. The second-reaction order of chlorine were selected as the optimal reaction order of research area because the decay of chlorine was best represented. Chlorine bulk decay coefficients of the water in conventional processes, advanced processes before rechlorination was respectively $5.9072(mg/L)^{-1}d^{-1}$ and $3.3974(mg/L)^{-1}d^{-1}$, and $1.2522(mg/L)^{-1}d^{-1}$ and $1.1998(mg/L)^{-1}d^{-1}$ after rechlorination. As a result, the reduction of organic material concentration during the retention time has greatly changed the chlorine bulk decay coefficient. All the coefficients of determination were higher than 0.8 in the developed models of the chlorine bulk decay coefficient, considering the drawn chlorine bulk decay coefficient and several parameters of water quality and statistically significant. Thus, it was judged that models that could express the actual values, properly were developed. In the meantime, the chlorine bulk decay coefficient was in proportion to the initial residual chlorine concentration and the concentration of rechlorination; however, it may greatly vary depending on rechlorination. Thus, it is judged that it is necessary to set a plan for the management of residual chlorine concentration after experimentally assessing this change, utilizing the methodology proposed in this study in the actual fields. The prediction models in this study would simulate the reduction of residual chlorine concentration according to the conditions of the operation of water purification plants and the introduction of rechlorination facilities, more reasonably considering water purification process and the time of chlorination. In addition, utilizing the prediction models, the reduction of residual chlorine concentration in the supply areas can be predicted, and it is judged that this can be utilized in setting plans for the management of residual chlorine concentration.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.2
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• pp.227-232
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• 2008

The masking effect of chlorine on algae-related taste and odor(T&O) compounds has long been an important issue for water suppliers. In this study, masking experiments with chlorine were performed on two kinds of treated water and one of raw water. After adding chlorine(0 to 0.8 mg/L) to water samples, odor intensity was evaluated by a newly developed sensory method(2-out-of-5 odor test) for three days along with the measurement of residual chlorine concentration. Even though the relationship between the residual chlorine concentration and odor reported by the sensory analysts was not always coincident, it was proved that residual chlorine more than a certain concentration could completely mask both added geosmin and naturally occurring T&O compounds. For the sand-filtered water spiked with 10 ng/L of geosmin, 0.12-0.18 mg/L of residual chlorine was necessary to achieve complete masking. In the case of GAC-filtered water, 10 ng/L of spiked geosmin was completely masked by 0.15-0.1 mg/L of residual chlorine. Combined ozone and GAC was not enough to treat raw water spiked with 300 ng/L of geosmin. In this experiment, sensory analysts were able to detect earthy or musty odors from the treated water. From a masking experiment with raw water taken from the Daechung Reservoir, it was found that fishy odor was more difficult to mask with chlorine than earthy odor. As the chlorine residual declined, the analysts began to notice the original odor and the fishy odor was noticed earlier than the earthy odor.

• Journal of Korean Society of Water and Wastewater
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• v.14 no.1
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• pp.108-116
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• 2000

Chlorine is widely used as a disinfectant in drinking-water systems throughout the world. Chlorine residual was used as an indicator for prediction of water quality in water distribution systems. The variation of chlorine residual in drinking water distribution systems of Suwon city was simulated using EPANET. EPANET is a computerized simulation model which predicts the dynamic hydraulic and water quality behavior within a water distribution system operating over an extended time period. Sampling and analysis were performed to calibrated the computer model in 1999 (Aug. Summer). Water quality variables used in simulations are temperature, roughness coefficient, pipe diameter, pipe length, water demand, velocity and so on. Extended water residence time affected water quality due to the extended reaction time in some areas. All area showed the higher concentration of chlorine residual than 0.2mg/l(standard). So it can be concluded that any area in Suwon city is not in biological regrowth problem. Rechlorination turned out to be an useful method for uniform concentration of free chlorine residual in distribution system. The cost of disinfectant could be saved remarkably by cutting down the initial chlorine concentration to the level which guarantees minimum concentration (0.2mg/l) throughout the distribution system.

• Journal of Korean Society of Water and Wastewater
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• v.34 no.5
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• pp.311-321
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• 2020

In this study, a model to optimize residual chlorine concentrations in a water supply system was developed using a multi-objective genetic algorithm. Moreover, to quantify the effects of optimized residual chlorine concentration management and to consider customer service requirements, this study developed indices to quantify the spatial and temporal distributions of residual chlorine concentration. Based on the results, the most economical operational method to manage booster chlorination was derived, which would supply water that satisfies the service level required by consumers, as well as the cost-effectiveness and operation requirements relevant to the service providers. A simulation model was then created based on an actual water supply system (i.e., the Multi-regional Water Supply W in Korea). Simulated optimizations were successful, evidencing that it is possible to meet the residual chlorine concentration demanded by consumers at a low cost.

• Journal of Korean Society of Water and Wastewater
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• v.20 no.1
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• pp.86-93
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• 2006

In the drinking water treatment, the aesthetic and color problem are caused by the manganese which is occurring and present in the surface, lake and ground water. The most common treatment processes for removing manganese are known for oxidation followed by filtration. In this study, the manganese sand process was used for removing manganese with river bank filtrate as a source. In the manganese sand process, the residual chlorine and pH are important factors on the continuous manganese oxidation. In addition, space velocity (SV) and alum dosage are play a role of manganese removal. Even though manganese removal increased with increasing chlorine concentration, the control of residual chlorine is actually difficult in this process As the results of tests, the residual chlorine concentration as well as manganese removal were effectively achieved at pH 7.5. The optimum attached manganese concentration on manganese sand was confirmed to 0.3mg/L by the experimental result of a typical sand converting to manganese sand.

• Corrosion Science and Technology
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• v.17 no.1
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• pp.12-19
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• 2018

Langelier Index (LI) is used as a tap water corrosiveness index. Residual chlorine in tap water induces corrosion inside water pipes. This study takes a deeper look into the effect of residual chlorine in water pipes. Comparison between tap waters of Y and K water treatment plant (WTP) shows that the LI index of K WTP is lower than that of Y. However, the corrosion rate of Y WTP is higher than that of K WTP. This means that the higher the concentration of residual chlorine in tap water, the higher the corrosion rate of pipe materials. When calcium hydroxide was added to tap water, the corrosiveness index was improved and thus the corrosion rate reduced. It is possible to increase the disinfection efficiency by increasing the duration of residual chlorine and suppressing the rust generation of water pipes and to supply minerals. A guideline for corrosion control with residual chlorine should be set up. The effects of residual chlorine should be included in the corrosiveness index of tap water.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.151-164
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• 2024

In water treatment plants supplying potable water, the management of chlorine concentration in water treatment processes involving pre-chlorination or intermediate chlorination requires process control. To address this, research has been conducted on water quality prediction techniques utilizing AI technology. This study developed an AI-based predictive model for automating the process control of chlorine disinfection, targeting the prediction of residual chlorine concentration downstream of sedimentation basins in water treatment processes. The AI-based model, which learns from past water quality observation data to predict future water quality, offers a simpler and more efficient approach compared to complex physicochemical and biological water quality models. The model was tested by predicting the residual chlorine concentration downstream of the sedimentation basins at Plant, using multiple regression models and AI-based models like Random Forest and LSTM, and the results were compared. For optimal prediction of residual chlorine concentration, the input-output structure of the AI model included the residual chlorine concentration upstream of the sedimentation basin, turbidity, pH, water temperature, electrical conductivity, inflow of raw water, alkalinity, NH₃, etc. as independent variables, and the desired residual chlorine concentration of the effluent from the sedimentation basin as the dependent variable. The independent variables were selected from observable data at the water treatment plant, which are influential on the residual chlorine concentration downstream of the sedimentation basin. The analysis showed that, for Plant, the model based on Random Forest had the lowest error compared to multiple regression models, neural network models, model trees, and other Random Forest models. The optimal predicted residual chlorine concentration downstream of the sedimentation basin presented in this study is expected to enable real-time control of chlorine dosing in previous treatment stages, thereby enhancing water treatment efficiency and reducing chemical costs.

• Corrosion Science and Technology
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• v.17 no.4
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• pp.176-182
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• 2018

Corrosion of the Cu alloy with 10wt% Ni in stagnant seawater with residual free chlorine was investigated. Despite that fact that Cu alloys are widely used for seawater applications due to their stubborn resistance to chloride attack, not much is known as to how the residual free chlorine in seawater affects corrosion of Cu and its alloys. In this work, immersion tests were conducted in the presence of different levels of chlorine for 90-10 Cu-Ni samples, one of the most frequently used Cu alloys for seawater application, mostly in shipbuilding. The results revealed no evidence for accelerated corrosion of the Cu-Ni alloy even in the presence of 5 ppm residual chlorine in seawater, signifying that the Cu-Ni alloy can be more tolerant to residual chlorine that has been commonly cited by the shipbuilding industry. However, comparison of polarization behavior of the alloy samples in the presence of different electrolytes with different concentrations of residual chlorine suggests that higher concentration of chlorine could increase the corrosion rate of the Cu-Ni alloy. Furthermore, it is suggested that microorganisms in the seawater could increase the corrosion rate of the Cu-Ni alloy by encouraging exfoliation of the corrosion product off the metal surface.

• Journal of Korean Society of Water and Wastewater
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• v.32 no.5
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• pp.411-419
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• 2018

The residual chlorine concentration is an essential factor to secure reliable water quality in the water distribution systems. The chlorine concentration decays along the pipeline system and the main processes of the reaction can be divided into the bulk decay and the wall decay mechanisms. Using EPANET 2.0, it is possible to predict the chlorine decay through bulk decay and wall decay based on the pipeline geometry and the hydraulic analysis of the water distribution system. In this study, we tried to verify the predictability of EPANET 2.0 using data collected from experimental practices. We performed chlorine concentration measurement according to various Reynolds numbers in a pilot-scale water distribution system. The chlorine concentration was predicted using both bulk decay model and wall decay model. As a result of the comparison between experimental data and simulated data, the performance of the limited $1^{st}$-order model was found to the best in the bulk decay model. The wall decay model simulated the initial decay well, but the overall chlorine decay cannot be properly predicted. Simulation also indicated that as the Reynolds number increased, the impact of the wall.