• Journal of Korean Society of Environmental Engineers
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• v.31 no.1
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• pp.15-20
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• 2009

The concentration of residual chlorine should be kept at over 0.1 mg/L in the circular water tank used in a water purification system. Generally, the concentration of residual chlorine depends on the structure and the volume of water tank, and also the water flow rate. To secure the diffusion time is important to the concentration of residual chlorine. For that reason, the baffles are installed in the circular water tank. In the present study, the variations of water and chlorine concentration were obtained with time using the numerical analysis. And also, the streamlines were shown according to the number of baffles. As a results, the vortex flow appeared between baffles, and the diffusion time of chlorine increased with the more number of baffles.

• Journal of Korea Water Resources Association
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• v.55 no.1
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• pp.59-70
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• 2022

Water distribution systems (WDSs) are a representative infrastructure injecting chlorine to disinfect the pathogenic microorganisms and supplying water from sources to consumers. Also, WDSs prescribe to maintain the usual standard (0.1-4.0 mg/L) of residual chlorine. However, the user's usage pattern, water age, network shape, and type affect the hydraulic features (i.e. nodal pressure, pipe velocity) and water quality features (i.e., the residual chlorine concentration). Therefore, this study developed an optimization approach for optimizing WDSs considering water quality-hydraulic factors using Multi-objective Harmony Search (MOHS). The design cost and the system resilience were applied as the design objective functions, and the nodal pressure and the concentration of residual chlorine are used as constraints. The derived optimal designs through this approach were analyzed according to network characteristics such as the network shapes and type. These optimal designs can meet the safety of economic and water quality aspects to increase user acceptance.

• Geomechanics and Engineering
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• v.36 no.2
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• pp.145-156
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• 2024

The mechanical properties of the concrete-frozen soil interface play a significant role in the stability and service performance of construction projects in cold regions. Current research mainly focuses on the precast concrete-frozen soil interface, with limited consideration for the more realistic cast-in-place concrete-frozen soil interface. The two construction methods result in completely different contact surface morphologies and exhibit significant differences in mechanical properties. Therefore, this study selects silty clay as the research object and conducts direct shear tests on the concrete-frozen soil interface under conditions of initial water content ranging from 12% to 24%, normal stress from 50 kPa to 300 kPa, and freezing temperature of -3℃. The results indicate that (1) both interface shear stress-displacement curves can be divided into three stages: rapid growth of shear stress, softening of shear stress after peak, and residual stability; (2) the peak strength of both interfaces increases initially and then decreases with an increase in water content, while residual strength is relatively less affected by water content; (3) peak strength and residual strength are linearly positively correlated with normal stress, and the strength of ice bonding is less affected by normal stress; (4) the mechanical properties of the cast-in-place concrete-frozen soil interface are significantly better than those of the precast concrete-frozen soil interface. However, when the water content is high, the former's mechanical performance deteriorates much more than the latter, leading to severe strength loss. Therefore, in practical engineering, cast-in-place concrete construction is preferred in cases of higher negative temperatures and lower water content, while precast concrete construction is considered in cases of lower negative temperatures and higher water content. This study provides reference for the construction of frozen soil-structure interface in cold regions and basic data support for improving the stability and service performance of cold region engineering.

• 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.

• Journal of Navigation and Port Research
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• v.37 no.2
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• pp.173-179
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• 2013

The interaction among wave, seabed and marine structure is an important issue in coastal engineering as well as geotechnical engineering. Understanding variations of stresses and pore water pressures generated in seabed induced by waves is important for civil engineers who have to design the foundation for various marine structures and verify the instability of seabed. In the matters on seabed instability, particularly, in the case of wave-induced liquefaction of seabed, it is turned out there are two different mechanisms through previous studies. These are caused by the transient or oscillatory nature and the residual or progressive nature of excess pore water pressure generated in seabed, respectively. In this study, it is analyzed dynamic characteristics of soils sampled in seabed around the port of Kochi, Japan, through the dynamic triaxial tests and the residual excess pore water pressure in the seabed induced by seepage force of wave. In addition, the calculated residual excess pore water pressures were compared with the field data observed in the port of Kochi.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.723-728
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• 2019

Citizens' distrust of water pollution is very high in tap water that we routinely drink. In addition, water pollution accidents of tap water are difficult to predict and the risk is high, so real-time monitoring and management are needed. Therefore, it is necessary to introduce real-time water quality monitoring using the Internet of things(IoT). Residual chlorine is more persistent and economical than other disinfectants and it is easy to check residual effect, so it is mainly used as a disinfection index in waterworks. It can be monitored in real time by using IoT technology in order to secure the safety of tap water. In this study, we developed smart device for real-time water quality monitoring using amperometry sensor and analyzed its performance.

• Proceedings of the Korean Society of Coastal and Ocean Engineers Conference
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• 1997.10a
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• pp.73-76
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• 1997

The purpose of this study is to find sedimentation patterns variation in Saemangeum coastal sea region. Water circulations are calculated diagnostically from the observed water temperature and salinity data and wind data and tidal residual current. Three dimensional movements of injected particles due In currents, turbulence and sinking velocity are tracked by the Euler-lagrange method. Calculated sedimentation patterns of riverine material are highly similar to the observed ones.

• Journal of the Korean Society of Safety
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• v.37 no.4
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• pp.113-119
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• 2022

Sudden intrusion of a large amount of surface water into a flood defensive tunnel or pipeline system can compress the residual air. The compressed air may explode along with water through the inlet or air vent, resulting in hydraulic capacity degradation or safety hazards. This study aims to investigate the behavior of compressed air body in pipelines according to the residual air condition with a series of laboratory experiments measuring pressure variation. It has been found that flow characteristics and residual air conditions have a dominant influence on the magnitude and periodicity of the pressure variation. A proper measure to effectively control the residual air is required for securing the design capacity of flood defensive pipeline systems, since the peak pressure is predominantly affected by residual air conditions.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1283-1293
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• 2022

The purpose of this study is to predict residual chlorine in order to maintain stable residual chlorine concentration in sedimentation basin by using artificial intelligence algorithms in water treatment process employing pre-chlorination. Available water quantity and quality data are collected and analyzed statistically to apply into mathematical multiple regression and artificial intelligence models including multi-layer perceptron neural network, random forest, long short term memory (LSTM) algorithms. Water temperature, turbidity, pH, conductivity, flow rate, alkalinity and pre-chlorination dosage data are used as the input parameters to develop prediction models. As results, it is presented that the random forest algorithm shows the most moderate prediction result among four cases, which are long short term memory, multi-layer perceptron, multiple regression including random forest. Especially, it is result that the multiple regression model can not represent the residual chlorine with the input parameters which varies independently with seasonal change, numerical scale and dimension difference between quantity and quality. For this reason, random forest model is more appropriate for predict water qualities than other algorithms, which is classified into decision tree type algorithm. Also, it is expected that real time prediction by artificial intelligence models can play role of the stable operation of residual chlorine in water treatment plant including pre-chlorination process.

• Proceedings of the KWS Conference
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• 2004.05a
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• pp.212-214
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• 2004

It is widely recognized that the residual stress of weldment affects steel construction and causes fracture initiation of welded structures. It is necessary to know since the power plants adopt a variety of welding processes distribution and magnitude of residual stresses. Therefore the purpose of present study is to investigate the validity of the indentation method to measure residual stresses of steel plates by residual stresses measured form the specimens of hot reheater pipes, cold reheater pipes and feed water lines used in power plants.