• 한국정보통신학회논문지
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• 제11권6호
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• pp.1207-1213
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• 2007

기존의 수도설비의 밸브실과 유량계의 관리는 기계적이고 숙련자의 경험적인 방식으로 이루어져 왔다. 그러나 USN 기반의 실시간 수도설비 모니터링 시스템을 활용한 시설물 관리는 안전성과 정확성을 제공함으로서 양질의 수자원을 관리하는데 기술적인 발전을 가져올 수 있다. 따라서 본 연구는 USN(Ubiquitous Sensor Network)과 CDMA(Code Division Multiple Access) 망을 이용한 수도 시설물의 안전 관리 시스템에 관하여 연구하였다. 수도 설비 중에서 밸브실과 유량계실을 대상으로 유량계, 압력센서, 진동센서, Co센서, 온 습도센서들의 RFID(Radio-frequency identification) 센서로 구성된 USN을 구성하고, USN으로부터 실시간으로 수도 시설물 정보 및 수(水)처리 측정 정보를 수집하여, CDMA망을 통해 원거리 관제 시스템에 전송한다. USN 기술을 이용하여 수도설비를 관리함으로서 현장에서의 편리성, 안전성, 정확성을 높여 더욱 효율적이고 안정적으로 깨끗한 수돗물을 공급하는데 기여할 수 있다.

• 대한토목학회논문집
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• 제26권3B호
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• pp.291-300
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• 2006

본 연구에서는 통계를 이용한 경안천유역의 최적 수질 측정망 구성이 제안된다. 분석을 위해서 필요한 수질 데이터는 QUAL2E 모형을 이용하여 모의하였으며, 경안천 유역의 2000년도 3월부터 11월까지의 월 평균자료를 이용하였다. QUAL2E 모형을 구축하는데 필요한 수리 매개변수는HEC-RAS모형을 이용하여 추정하였다. 수질매개변수의 경우 월평균 실측자료를 바탕으로 1차 신뢰성 분석(FORA)를 이용하여 민감도 분석을 실시하여 수질항목별로 민감하지 않은 매개변수를 제외한 후 보정이 이루어진다. QUAL2E 모형의 모의 결과를 바탕으로 크리깅 기법과 Branch and Boundary Method를 이용하여 평수량 일때와 갈수량 일때로 구분하여 관측지점의 개수와 위치가 결정된다. 또한 선정된 지점을 기준으로 proportional sampling method(비례표본추출법)를 이용하여 각각의 지점별 측정 빈도가 제시된다.

• 한국관개배수논문집
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• 제19권1호
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• pp.19-29
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• 2012

The data of the agricultural water quality survey network was analyzed between from 1990 to 2010 in order to propose effective plans for water quality management by analyzing the characteristics of agricultural lakes and the change of water quality. The result of the analysis shows that there is a correlation between water quality and items that can be a function of water depth such as dam height, dam length, dam height/dam length ratio and active storage/surface area of lake ratio. This means that, Korean agricultural lakes, there is a correlation between water quality and water depth. Water quality of the lakes that have lower than 5m of active storage/surface area of lake ratio (effective water depth) especially tends to get worse rapidly. The Chl-a and COD concentration of Korean agricultural lakes have a tendency to increase between June and September. Therefore, we recommend first taking a water quality improvement project for the lakes preformed watershed management project, and taking a preventive short-term water quality improvement project for the unperformed lakes before June among lakes that have lower than 5m of effective water depth.

• 한국농공학회지
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• 제39권2호
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• pp.9-18
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• 1997

Abstract This paper presents a heuristic method for optimal design of water distribution system with multiple sources and potential links. In multiple source pipe network, supply rate at each source node affects the total cost of the system because supply rates are not uniquely determined. The Linear Minimum Cost Flow (LMCF) model may be used to a large scale pipe network with multiple sources to determine supply rate at each source node. In this study the heuristic method based on the LMCF is suggested to determine supply rate at each source node and then to optimize the given layout. The heuristic method in turn perturbs links in the longest path of the network to obtain the supply rates which make the optimal design of the pipe network. Once the best tree network is obtained, the frequency count of reconnecting links by considering link failure is in turn applied to form loop to enhance the reliability of the best tree network. A sample pipe network is employed to test the proposed method. The results show that the proposed method can yield a lower cost design than the LMCF alone and that the proposed method can be efficiently used to design irrigation systems or rural water distribution systems.

• 산업기술연구
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• 제41권1호
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• pp.1-6
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• 2021

Fly ash and silica fume belong to industry by-products that can be used to produce concrete. This study shows the model of a neural network to evaluate the strength development of blended concrete containing fly ash and silica fume. The neural network model has four input parameters, such as fly ash replacement content, silica fume replacement content, water/binder ratio, and ages. Strength is the output variable of neural network. Based on the backpropagation algorithm, the values of elements in the hidden layer of neural network are determined. The number of neurons in the hidden layer is confirmed based on trial calculations. We find (1) neural network can give a reasonable evaluation of the strength development of composite concrete. Neural network can reflect the improvement of strength due to silica fume additions and can consider the reductions of strength as water/binder increases. (2) When the number of neurons in the hidden layer is five, the prediction results show more accuracy than four neurons in the hidden layer. Moreover, five neurons in the hidden layer can reproduce the strength crossover between fly ash concrete and plain concrete. Summarily, the neural network-based model is valuable for design sustainable composite concrete containing silica fume and fly ash.

• 상하수도학회지
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• 제20권1호
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• pp.35-43
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• 2006

Concerns related to protecting, identifying, and isolating of subsystems of a water distribution network have led to the realization of the increased importance of valves in the system. The most important purpose of valves in water distribution systems is to isolate a subsystem due to breakage, maintenance activities, or contamination. A subsystem called segment is isolated by the closure of adjacent valves. Minimizing the pipe failure impact, an efficient algorithm is required to identify adjacent valves quickly. In this paper, an algorithm to identify adjacent valves to be closed to isolate a subsystem from the remainder of a network when a pipe failure is presented. The algorithm is operated on a matrix called the valve location matrix containing the information of valve locations. An application to an existing water distribution system demonstrates the developed algorithm efficiently locates the adjacent valves for the isolation of a broken pipe.

• 상하수도학회지
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• 제12권4호
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• pp.43-52
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• 1998

The purpose of this study is to establish a method of estimating the daily urban water demend using Backpropagation algorithm is part of ANN(Artificial Neural Network). This method will be used for the development of the efficient management and operations of the water supply facilities. The data used were the daily urban water demend, the population and weather conditions such as treperarture, precipitation, relative humidity, etc. Kwangju city was selected for the case study area. We adjusted the weights of ANN that are iterated the training data patterns. We normalized the non-stationary time series data [-1,+1] to fast converge, and choose the input patterns by statistical methods. We separated the training and checking patterns form input date patterns. The performance of ANN is compared with multiple-regression method. We discussed the representation ability the model building process and the applicability of ANN approach for the daily water demand. ANN provided the reasonable results for time series forecasting.

• 상하수도학회지
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• 제14권3호
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• pp.281-290
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• 2000

This study investigates the prediction of daily water supply, which is a necessary for the efficient management of water distribution system. ANFIS, namely artificial intelligence, is a neural network into which fuzzy information is inputted and then processed. In this study, daily water supply was predicted through an application of network-based fuzzy inference system(ANFIS) for daily water supply prediction. This study was investigated methods for predicting water supply based on data about the amount of water which supplied in Kwangju city. For variables choice, four analyses of input data were conducted: correlation analysis, autocorrelation analysis, partial autocorrelation analysis, and cross-correlation analysis. Input variables were (a) the amount of water supply, (b) the mean temperature, and (c) the population of the area supplied with water. Variables were combined in an integrated model. Data of the amount of daily water supply only was modelled and its validity was verified in the case that the meteorological office of weather forecast is not always reliable. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 18.46% and the average error was lower than 2.36%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.

• 상하수도학회지
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• 제28권6호
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• pp.699-711
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• 2014

This study was carried out to analyze water suspension in the water supply system through fault tree analysis. And quantitative factors was evaluated to minimize water suspension. Consequently the aim of this study is to build optimal planning by analyzing scenarios for water suspension. Accordingly the fault tree model makes it possible to estimate risks for water suspension, current risks is $92.23m^3/day$. The result of scenario analysis by pipe replacement, risks for water suspension was reduced $7.02m^3/day$ when replacing WD4 pipe. As a result of scenario analysis by water district connections, the amount of risk reduction is maximized when it is connecting to network pipe of D Zone. Therefore, connecting to network pipe for D Zone would be optimal to reduce risk for water suspension.

• 상하수도학회지
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• 제29권3호
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• pp.415-425
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• 2015

Aging water pipe networks hinder efficient management of important water service indices such as revenue water and leakage ratio due to pipe breakage and malfunctioning of pipe appurtenance. In order to control leakage in water pipe networks, various methods such as the minimum night flow analysis and sound waves method have been used. However, the accuracy and efficiency of detecting water leak by these methods need to be improved due to the increase of water consumption at night. In this study the Principal Component Analysis (PCA) technique was applied to the night water flow data of 426 days collected from a water distribution system in the interval of one hour. Based on the PCA technique, computational algorithms were developed to narrow the time windows for efficient execution of leak detection job. The algorithms were programmed on computer using the MATLAB. The presented techniques are expected to contribute to the efficient management of water pipe networks by providing more effective time windows for the detection of the anomaly of pipe network such as leak or abnormal demand.