사이드 스트림 방식의 막 모듈을 대상으로 유입 유량을 수직으로 균등하게 분포시킬 수 있는 방안을 CFD로 설계한 결과, 내부 유입 수리구조에 유공 격벽 을 설치함으로써 모듈내로의 유입유량은 표준편차 기준으로 약 40% 정도 감소 됨을 확인하였다. 또한 CFD 결과를 검증하고 사이드 스트림 막 모듈의 편중된 오염의 원인을 조사하기 위해 수행된 입자영상유속 측정 결과로부터 유입구 반대편 유공에서 막 모듈 내부로 들어오는 수체의 유속이 상대적으로 커 수체의 모멘텀이 유입구 측벽에 강한 전단력을 발생하지만 유입구 반대 측벽에서는 사류가 형성됨을 확인하였다.

It has been widely accepted that the pressure management of water distribution systems using pressure reducing valves(PRVs) would be an effective method for controlling leakages. A pressure reducing valve (PRV) regulates outlet pressure regardless of fluctuating flow and varying inlet pressure, thereby reducing leakage and mitigating the stress on the water distribution system. However, the operation of a PRV is vulnerable to its mechanical condition and hydraulic operability. In this research, the effect of PRVs installed in water distribution system are evaluated in terms of hydraulic pressure reduction and mechanical performance by analyzing measured pressure data with statistical approach. A statistical approach using the moving average filter and frequency analysis based on fourier transform is presented to detect abnormally operated PRVs that have been densely installed in water distribution system. The result shows that the proposed approach can be a good performance evaluation method by simply measuring pressures for the PRVs.

This study have been conducted to analyze the feasibility of establishing Contamination Warning System(CWS) that is capable of monitoring early natural or intentional water quality accidents, and providing active and quick responses for domestic C_water supply system. In order to evaluate the water quality data set, pH, turbidity and free residual chlorine concentration data were collected and each statistical value(mean, variation, range) was calculated, then the seasonal variability of those were analyzed using the independent t-test. From the results of analyzing the distribution of outliers in the measurement data using a high-pass filter, it could be confirmed that a lot of lower outliers appeared due to data missing. In addition, linear filter model based on autoregressive model(AR(1) and AR(2)) was applied for the state estimation of each water quality data set. From the results of analyzing the variability of the autocorrelation coefficient structure according to the change of window size(6hours~48hours), at least the window size longer than 12hours should be necessary for estimating the state of water quality data satisfactorily.

The main objective of this research is to study feasibility for applying metal membrane to remove particles from air scouring membrane backwash water. Also, the research was conducted to investigate the influence of polyamine coagulation on floc growth in membrane backwash water as pretreatment for removal particles. From the results of experiments for evaluating the influence of polyamine coagulation on floc growth, it was investigated that particles in the rage of 2~50 μm grew up to 30~5,000 μm. In addition, all six metal membranes showed lower removal efficiency, which was 0.87~13.89%, in the case of no polyamine coagulant. On the other hand, in the case of injecting polyamine coagulant, those did extremely high efficiency in 56~92%. From the SEM(Scanning Electron Microscope) images of filtered wiremesh and metal foam membrane, sieve effects were predominant for liquid solid separation in wiremesh and adsorption and diffusion capture effects were predominant in metal foam membrane.

The probability distribution of wind speeds is a mathematical function describing the range and relative frequency of wind speeds at a particular location . In other word , the behavior of wind velocity at a given site can be specified as a probability distribution function. The accuracy of design wind estimation depends on the choice of an appropriate probability distribution model (PDM) and parameter estimation techniques. Generally, parameters for PDMs are estimated with the method of moments(MOM), probability weighted moments(PWM), and maximum likelihood (ML). In this work , we tried to estimate the parameters of PDMs for wind speed data using a recently developed meta-heuristic approach known as a harmony search (HS) that is a phenomenon-mimicking algorithm. The performance of the HS is compared to the genetic algorithm (GA) and conventional method (i.e.,ML) via simulation and case study.