Pilot-scale coagulation and sedimentation processes were operated to investigate the T-P (Total phosphorus) removal efficiency. A multiple regression model was also derived to predict the water quality improvement effect with river water characteristics. The inflow rates for the pilot-scale facility were 157-576 m³/day, and the coagulant doses were in the range of 13.7-58.5 mg/L (average 38.9 mg/L) for PAC (Poly alum chloride) and 16.5-62.1 mg/L (average 36.0 mg/L) for alum. The results found that the influent BOD (Biochemical oxygen demand) and T-P concentrations were 4.9 mg/L and 0.115 mg/L, and the removal efficiencies were 52.7% and 59.4%, respectively. T-P removal efficiencies on wet weather days were higher by 10% than dry weather days because influent solids influenced T-P's coagulation process. The pH of river water was 6.9-7.8, and the average pH was 7.3. Although the pH variation was not significant, the trend showed that the treatment efficiency of T-P and PO₄-P removal increased. Thus, the pH range considered in this study seems to be appropriate for the coagulation process, which is essential for phosphorous removal. The T-P removal efficiencies were 19.6-93.3% (average 59.2%) for PAC and 16.4-98.5%(average 55.9%) for alum; thus, both coagulants showed similar results. Furthermore, the average coagulant doses were similar at 42.4 mg/L for PAC and 41.3 mg/L for alum. When the T-P concentration of the effluent was compared by the [Al]/[P] ratio, the phosphorus concentration of the treated water decreased with an increasing [Al]/[P] ratio, and the lowest T-P concentration range appeared at the [Al]/[P] ratio of 10-30. A seasonal multiple regression analysis equations were derived from the relationships between 10 independent and dependent variables (T-P concentration of effluent). This study could help lake water quality maintenance, reduce eutrophication, and improve direction settings for urban planning, especially plans related to developing waterfront cities.

As the frequency of seismic disasters in Korea has increased rapidly since 2016, interest in systematic maintenance and crisis response technologies for structures has been increasing. A data-based leading management system of Lifeline facilities is important for rapid disaster response. In particular, the water supply network, one of the major Lifeline facilities, must be operated by a systematic maintenance and emergency response system for stable water supply. As one of the methods for this, the importance of the structural health monitoring(SHM) technology has emerged as the recent continuous development of sensor and signal processing technology. Among the various types of SHM, because all machines generate vibration, research and application on the efficiency of a vibration-based SHM are expanding. This paper reviews a vibration-based pipeline SHM system for seismic disaster response of water supply pipelines including types of vibration sensors, the current status of vibration signal processing technology and domestic major research on structural pipeline health monitoring, additionally with application plan for existing pipeline operation system.

Water treatment process simulator is the tool for predicting sequential changes of water quality in a train of unit processes. This predicts the changes through governing equations that represent physicochemical performance of each unit processes with an initial and boundary conditions. Since there is no operational data for the design of a water treatment facility, there is no choice but to predict the performance of the facility by assuming initial and boundary conditions in virtual reality. Therefore, a simulator that can be applied in the design stage of a water treatment facility has no choice but to be built as a numerical analysis model of a deductive technique. In this study, we had conducted basic research on governing equations, inter-process data-flow, and simulator algorithms for the development of simulators. Lastly, this study will contribute to design engineering tool development research in the future by establishing the water treatment theory so that it can be programmed in a virtual world and suggesting a method for digital transformation of the water treatment process.