• Journal of Korean Society of Water and Wastewater
• /
• v.31 no.1
• /
• pp.73-81
• /
• 2017

The UV/chlorine process is a UV-based advanced oxidation process for removing various organic pollutants in water. The process is becoming increasingly popular because of its effectiveness in practice. It is important to the safe and efficient operation of a UV/chlorine process that the optimal operating conditions for both target removal objective and saving energy are determined. Treatment efficiency of target compounds in UV/chlorine process was mainly affected by pH and scavenging factor. In this study, kinetic based mathematical model considering water characteristics and electrical energy dose calculations model was developed to predict of treatment efficiency and optimal operating conditions. The model equation was validated for the UV/chlorine process at the laboratory scale and in pilot tests at water treatment plants.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2002.05a
• /
• pp.21-25
• /
• 2002

Activated sludge processes are widely used in biological wastewater treatment processes. The main motivation of this research is to develop an intelligent control strategy for activated sludge process (ASP). ASP is a complex and nonlinear dynamic system because of the characteristic of wastewater, the change in influent rate, weather conditions, and so on. The mathematical model of ASP also includes uncertainties which are ignored or not considered by process engineer or controller designer. The ASP model based on Matlab/Simulink is designed in this paper. The performance of the model is tested by IWA (International Water Association) and COST (European Cooperation in the filed of Scientific and Technical Research) data that include steady-state results during 14 days. In this paper, fuzzy logic control approach is applied to control the DO (dissolved oxygen) concentration. The fuzzy logic controller that includes two inputs and one output can adjust air flowrate. Also, this paper introduces the remote monitoring and control system that is applied for the CSTR (Continuously Stirred Tank Reactor) wastewater treatment system. The CSTR plant has a local control and the remote monitoring system which is contained communication parts which consist of LAN (Local Area Network) network and CDMA (Code Division Multiple Access) wireless module. Remote control and monitoring systems are constructed in the laboratory.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.2333-2335
• /
• 2000

The main motivation of this research is to develop an intelligent control strategy for Activated Sludge Process(ASP). ASP is a complex and nonlinear dynamic system because of the characteristic of a wastewater, the change of an influent flow rate, weather conditions, and etc. The mathematical model of ASP also includes uncertainties which are ignored or not considered by process engineer or controller designer. The ASP is generally controlled by a PID controller that consists of fixed proportional, integral, and derivative gain values. The PID gains can be adjusted by the expert in the ASP. The ASP model based on Matlab$^{(R)}$5.3/Simulink$^{(R)}$3.0 is developed in this paper. Various control methods are applied to the ASP model and the control results are disscussed. Three control methods are designed and tested: conventional PID controller, fuzzy logic control approach to modify setpoints, and fuzzy-PID control method.

• Journal of Korean Society of Water and Wastewater
• /
• v.21 no.5
• /
• pp.601-607
• /
• 2007

In order to maintain constant residual chlorine in sedimentation basin, It is necessary to develop real time prediction model of residual chlorine considering water treatment plant data such as water qualities, weather, and plant operation conditions. Based on the operation data acquired from K water treatment plant, prediction models of residual chlorine in sediment basin were accomplished. The input parameters applied in the models were water temperature, turbidity, pH, conductivity, flow rate, alkalinity and pre-chlorination dosage. The multiple regression models were established with linear and non-linear model with 5,448 data set. The corelation coefficient (R) for the linear and non-linear model were 0.39 and 0.374, respectively. It shows low correlation coefficient, that is, these multiple regression models can not represent the residual chlorine with the input parameters which varies independently with time changes related to weather condition. Artificial neural network models are applied with three different conditions. Input parameters are consisted of water quality data observed in water treatment process based on the structure of auto-regressive model type, considering a time lag. The artificial neural network models have better ability to predict residual chlorine at sediment basin than conventional linear and nonlinear multi-regression models. The determination coefficients of each model in verification process were shown as 0.742, 0.754, and 0.869, respectively. Consequently, comparing the results of each model, neural network can simulate the residual chlorine in sedimentation basin better than mathematical regression models in terms of prediction performance. This results are expected to contribute into automation control of water treatment processes.

• Advances in environmental research
• /
• v.3 no.2
• /
• pp.173-183
• /
• 2014

A comprehensive mathematical model was developed for this study to estimate on-site and off-site GHG emissions from wastewater treatment plants (WWTPs). The model was applied to three different hybrid WWTPs (S-WWTP, J-WWTP, and T-WWTP) including anaerobic, anoxic, and aerobic process, located in Seoul City, South Korea. Overall on-site and off-site GHG emissions from S-WWTP, J-WWTP, and T-WWTP were $305,253kgCO_2e/d$, $282,682kgCO_2e/d$, and $117,942kgCO_2e/d$, respectively. WWTP treating higher amounts of wastewater produced more on-site and off-site GHG emissions. On average, the percentage contribution of on-site and off-site emissions was 3.03% and 96.97%. The highest amount of on-site GHG emissions was generated from anoxic process and the primary on-site GHG was nitrous oxide ($N_2O$). Off-site GHG emissions related to electricity consumption for unit operation was much higher than that related to production of chemicals for on-site usage. Recovery and reuse of biogas significantly reduced the total GHG emissions from WWTPs. The results obtained from this study can provide basic knowledge to understand the source and amount of GHG emissions from WWTPs and strategies to establish lower GHG emitting WWTPs.

• Journal of Korean Society of Water and Wastewater
• /
• v.27 no.6
• /
• pp.815-826
• /
• 2013

Using a developed mathematical model and calibrated kinetic constants, numerical experiments for a aerobic digestion of wastewater sludge by SBR aerobic digestion process combined with ultrasonication (USSBR) were performed in this study. It simulated well the phenomena of the decomposition of particulate organics and the release of organic nitrogen and transformation. To achieve 40 % of particulate organics removal, USSBR process requires only 6 days of SRT and 14 W/L of ultrasonic power whereas SBR aerobic digestion process requires 12 days of SRT. Based on the model simulation results, an empirical equation was presented here. This equation will be used to predict digestion efficiency for the given variables of SRT and ultrasonic power dose. USSBR aerobic digestion process can reduce the nitrogen concentration. The optimal operation strategy for the simultaneous removal of solids and soluble nitrogen in this process is estimated to 7 days of SRT with 14 W/L of ultrasonic power dose while anoxic period was 6 hours out of 24 hours of cycle time. In this condition, 40 % of particulate organics as well as 36 % of total nitrogen will be removed and the soluble nitrogen concentration of the centrate will be lower less then 40 mg/L.

• Korean Chemical Engineering Research
• /
• v.54 no.3
• /
• pp.340-349
• /
• 2016

Electro oxidation system was designed in this study for the reduction of COD (Chemical Oxygen Demand) from high-strength wastewater, produced during refinery turnaround period. First, BDD (Boron Doped Diamond) electrode was synthesized and electro oxidation system of actual industrial wastewater was developed by adopting the synthesized BDD electrode. The experiments were carried out under various operating conditions under certain range of current density, pH, electrolyte concentration and reaction time. Secondly, reaction kinetics were identified based on the experimental results, and the kinetics were embedded into a genetic mathematical model of the electro oxidation system. Lastly, design and operating parameters of the process were optimized to maximize the efficiency of the pretreatment system. The coefficient of determination ($R^2$) of the model was found to be 0.982, and it proved high accuracy of the model compared with experimental results.

• Membrane Journal
• /
• v.19 no.1
• /
• pp.72-82
• /
• 2009

A mathematical model was written for simulating the removal of phenol from wastewater in enzyme-loaded membrane reactor (EMR). The numerical simulation program was developed so as to predict the degradation of phenol through an EMR. Numerical model proves to be effective in searching for optimal operating conditions and creating an optimal microenvironment for the biocatalyst in order to optimize productivity. In this study, several dimensionless parameters such as Thiele Modulus (${\phi}^2$, dimensionless Michaelis-Menten constant ($\xi$), Peclet number (Pe) were introduced to simplify their effects on system efficiency. In particular, the study of phenol conversion at different feed compositions shows that low phenol concentrations and high Thiele Modulus values lead to higher reactant degradation.

• Journal of Korean Society of Water and Wastewater
• /
• v.26 no.6
• /
• pp.897-905
• /
• 2012

Based on the activated sludge model, a simple aerobic digestion model which represents the aerobic sludge digestion by sequencing batch reactor(SBR) equipped with ultrasonicator was composed and performed in this study. The results are as follows. Aerobic digestion efficiency can be increased by adopting ultrasonic pretreatment. For the 5 days of SRT, 24 % of particulate component is predicted to be removed by ultrasonic pretreatment and aerobic digestion. This is 7 %p higher than that of conventional aerobic digestion. A Hybrid SBR aerobic digestion combined with ultrasonication shows higher digestion efficiency than aerobic digestion and ultrasonic pretreatment system. In case of this hybrid system, the digestion efficiency was predicted up to 49 % when the ultrasonication was performed every 2 hours, repeatedly. However, excessive treatment like every hours of ultrasonication in an aerobic digestion process results in adverse effect on TCOD removal because biomass disintegrated completely and the solubilized COD can not be used for the biomass synthesis again.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.1 no.1
• /
• pp.56-61
• /
• 2001

Activated sludge processes are broadly used in the biological wastewater treatment processes. The activated sludge processes are complex systems because of the many factors such as the variation of influent flowrate and ingredients, the complexity of biological reactions, and the various operation conditions. The main motivation o this research is to develop an intelligent control strategy for activated sludge process (ASP). ASP is a complex and nonlinear dynamic system owing to the characteristic of wastewater, the change in influent flowrate, weather conditions, and so on. The mathematical model of ASP also includes the uncertainty which is a ignored or unconsidered factor from process designers. The ASP model based on Matlabⓡ/Simulinkⓡ is developed in this paper. And the model performance is examined by IWA (International Water Association) and COST (European Cooperation in the filed of Scientific and Technical Research) data. The model tests derive steady-state results of 14 days. In this paper, fuzzy logic control approach is applied to handle DO concentrations. The fuzzy logic controller includes two inputs and one output to adjust air flowrate. The objective function for the optimization, in the implemented evolutionary strategy, is formed with focusing on improving the effluent quality and reducing the operating cost.