• 한국수자원학회논문집
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• 제54권9호
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• pp.643-656
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• 2021

최근 국내 상수도 관리 기술은 고도로 발달하고 있으며, 이 과정에서 상수관망 내 용수공급 현황을 파악하고 예측하기 위한 컴퓨터 수리·수질 해석 모형은 핵심적인 역할을 수행하고 있다. 그러나 대규모 네트워크의 경우 컴퓨터 해석모형의 부담을 가중하고, 특히 짧은 계산시간 간격과 긴 모의 시간이 요구되는 수질해석의 경우, 막대한 계산시간이 소요되어 다양한 수질모의 및 분석이 어려운 경우가 발생한다. 본 연구에서는 대규모 상수관망시스템의 수질해석의 계산효율을 개선하기 위해 상수도 공급계통을 2단계로 계층화한 후, 계층화된 네트워크를 대상으로 수질모의를 수행하는 계층적 수질모의 기법을 제안하였다. 제안된 모의기법은 국내 대규모 상수도 네트워크에 적용하였으며, 다양한 염소투입농도 시나리오에 따른 잔류염소농도의 시공간적 분포를 모의하고 분석한 결과를 제시하였다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.146-146
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• 2021

A contamination event occurring in water distribution networks (WDNs) needs to be handled with the appropriate mitigation strategy to protect public health safety and ensure water supply service continuation. Typically the mitigation phase consists of contaminant sensing, public warning, network inspection, and recovery. After the contaminant source has been detected and treated, contaminants still exist in the network, and the contaminated water should be flushed out. The recovery period is critical to remove any lingering contaminant in a rapid and non-detrimental manner. The contaminant flushing can be done in several ways. Conventionally, the opening of hydrants is applied to drain the contaminant out of the system. Relying on advanced information and communication technology (ICT) on WDN management, warning and information can be distributed fast through electronic media. Water utilities can inform their customers to participate in the contaminant flushing by opening and closing their house faucets to drain the contaminated water. The household draining strategy consists of determining sectors and timeslots of the WDN users based on hydraulic simulation. The number of sectors should be controlled to maintain sufficient pressure for faucet draining. The draining timeslot is determined through hydraulic simulation to identify the draining time required for each sector. The effectiveness of the strategy is evaluated using three measurements, such as Wasted Water (WW), Flushing Duration (FD), and Pipe Erosion (PE). The optimal draining strategy (i.e., group and timeslot allocation) in the WDN can be determined by minimizing the measures.

• 한국수자원학회논문집
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• 제48권10호
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• pp.845-855
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• 2015

대규모 상수관망 시스템의 운영비용 절감을 위한 펌프장 운영 최적화 연구가 최근 활발히 진행되고 있다. 이러한 상수관망 시스템 운영 최적화에 대한 연구를 수행하기 위해서는 짧게는 24시간, 길게는 1주일 이상의 시간모의가 필수적이며, 최적화 알고리즘과의 연계를 통한 시뮬레이션이 요구된다. 대규모 상수관망의 경우 관로 및 절점의 수가 수 천 혹은 수 만개에 달해 수리해석 및 최적화에 많은 시간이 소요되며 실시간 운영을 목적으로 하는 경우 모형의 적용에 한계가 발생한다. 이처럼 모의시간에 대한 문제를 해결하기 위해서는 해당 상수관망 시스템의 수리 거동, 수질 해석 결과를 변화시키지 않는 범위에서 관망을 간소화 할 필요가 있다. 본 연구에서는 국내에서 실제로 운영되고 있는 송, 배수 시스템의 일부를 대상으로 시스템 간소화, 즉 골격화(Skeletonization) 연구를 진행하였으며, 모두 네 가지의 골격화 기법을 비교, 평가하였다. 본 연구에서 제안된 골격화 기법을 통해 대규모 상수관망의 해석에 소요되는 시간을 단축함으로써, 실제 상수관망의 실시간 운영 모듈 개발에 도움이 될 것으로 기대한다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.114-114
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• 2020

Water contamination in a water distribution network (WDN) is harmful since it directly induces the consumer's health problem and suspends water service in a wide area. Actions need to be taken rapidly to countermeasure a contamination event. A contaminant source ident ification (CSI) is an important initial step to mitigate the harmful event. Here, a CSI approach focused on determining the contaminant intrusion possible location and time (PLoT) is introduced. One of the methods to discover the PLoT is an inverse calculation to connect all the paths leading to the report specification of a sensor. A filtering procedure is then applied to narrow down the PLoT using the results from individual sensors. First, we spatially reduce the suspect intrusion points by locating the highly suspicious nodes that have similar intrusion time. Then, we narrow the possible intrusion time by matching the suspicious intrusion time to the reported information. Finally, a likelihood-score is estimated for each suspect. Another important aspect that needs to be considered in CSI is that there are inherent uncertainties, such as the variations in user demand and inaccuracy of sensor data. The uncertainties can lead to overlooking the real intrusion point and time. To reflect the uncertainties in the CSI process, the Monte-Carlo Simulation (MCS) is conducted to explore the ranges of PLoT. By analyzing all the accumulated scores through the random sets, a spread of contaminant intrusion PLoT can then be identified in the network.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2004년도 학술발표회
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• pp.521-526
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• 2004

It is necessary to analyze the unsteady flow in the pipe network for the better operation and controls, but there are some problems in actual pipe network simulation, such as collecting a large amount of information in the field, operating highly upgraded computer system, and keeping a big storage device to run analysis program. The skeletonization method is used to cope with the problems in this paper. It is expected to reduce computation time, researcher's efforts, and costs for the analyzing the pipe network. The impact of individual pipe elements to the behavior of the water distribution system can be accounted in the process of skeletonization. However it is also important to study continuously about how to apply the skeletonization method for each of different cases, because inadequate uses may bring simulation to a false result. This paper introduces basic theories and skeletonizing examples in the actual pipe network in Dae-gu city.

• 상하수도학회지
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• 제20권6호
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• pp.799-811
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• 2006

As an alternative measure to replace reactive stance with proactive one, a risk based management scheme has been commonly applied to enhance public satisfaction on water service by providing a higher creditable solution to handle a rehabilitation problem of pipe having high potential risk of leaks. This study intended to examine the feasibility of a simulation model to predict a recurrence probability of pipe leaks. As a branch of the data mining technique, probabilistic neural network (PNN) algorithm was applied to infer the extent of leaking recurrence probability of water network. PNN model could classify the leaking level of each unit segment of the pipe network. Pipe material, diameter, C value, road width, pressure, installation age as input variable and 5 classes by pipe leaking probability as output variable were built in PNN model. The study results indicated that it is important to pay higher attention to the pipe segment with the leak record. By increase the hydraulic pipe pressure to meet the required water demand from each node, simulation results indicated that about 6.9% of total number of pipe would additionally be classified into higher class of recurrence risk than present as the reference year. Consequently, it was convinced that the application of PNN model incorporated with a data base management system of pipe network to manage municipal water distribution network could make a promise to enhance the management efficiency by providing the essential knowledge for decision making rehabilitation of network.

• 한국수자원학회논문집
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• 제57권8호
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• pp.561-569
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• 2024

본 연구에서는 상수도관망의 시간에 따른 누적피해도를 정량적으로 산정하기 위해 추계학적 방법으로 상수도관망의 누적피해도 산정모형을 개발하였으며 이를 실제 도시에 적용하여 사용연수 증가에 따른 상수도관망의 누적피해도 변화를 분석하였다. 상수도관망 전체 피해율을 분석하기 위해 개별 관로의 누적피해도 평가모형을 수립하였고 누적피해도에 직접적인 영향을 미치는 노후지수는 MCS (Monte Carlo Simulation)을 사용하여 분석하였으며 부식으로 인한 두께변화 예측을 위해 Romanoff의 실측데이터를 사용하였다. 또한 단위관망(중블럭, 소블럭)별 상수도관망의 피해도를 분석하기 위한 누적피해도 모형을 수립하고 이를 통해 최대 50년 동안의 단위관망의 누적피해도를 예측할 수 있었다. 분석결과, 대상 지역인 청주시 내덕 1동 상수도관망의 경우 사용연수가 20년, 30년, 50년으로 증가함에 따라 누적피해도가 7%, 43%, 79%로 증가하는 것을 확인할 수 있었다.

• 한국수자원학회논문집
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• 제36권1호
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• pp.105-115
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• 2003

본 연구에서는 상수관망의 신뢰도해석을 위해 수리적 신뢰도와 기계적 신뢰도를 통합적으로 해석할 수 있는 통합신뢰도 해석모형을 개발하였다. 수리적 신뢰도는 불화실성을 가진 변수들에 대하여 적절한 변동계수를 가진 확률 분포형을 적용시켜 임의변수로 고려하였고 기계적 신뢰도는 관망의 각 구성물에 대해 순차적 고장을 발생시켜 각 고장에 대한 영항을 해석하여 신뢰도를 산정하였다. 덕 연구모형을 실제관망에 대한 적용결과 본 모형은 실제관망에 대한 불확실한 요소를 고려한 신뢰도를 잘 모의하고 있었다. 앞으로 신뢰성있는 상수관망 설계 및 기존 관망의 신뢰도 판정에 본 모형이 적용된다면 기계적 및 수리적으로 객관성이 있는 신뢰도를 가진 상수관망의 건설 및 유지관리가 될 수 있다고 판단된다.

• 상하수도학회지
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• 제19권3호
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• pp.279-287
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• 2005

In this study, I suggest an effective operation of waterwork facilities in large cities and a scientific method for utilizing water in water distribution systems. To achieve this goal, my simulation were carried out on data from Kwangju City using Pipenet '98, a pipe-network program. From this simulation, I examine the possibilities of application the system in large cities, comparing data measured at 33 hydraulic pressure monitoring places from waterwork enterprises. The result is coincident with that of waterwork enterprises, with about a 12.5% average error rate and $0.32kg/cm^2$ average deviation. The method and program I use here can be helpful in cities where there is a need to extend the waterwork facilities, or where there is a need to suspend the water supply, and/or there is an accident. The simulation shows how to expand waterwork facilities effectively, how to prevent accidents, and how to estimate the hydraulic pressure even in the areas without monitoring places.

• Smart Structures and Systems
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• 제26권2호
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• pp.175-184
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• 2020

Conventional Monte Carlo simulation-based methods for seismic risk assessment of water networks often require excessive computational time costs due to the hydraulic analysis. In this study, an Artificial Neural Network-based surrogate model was proposed to efficiently evaluate the flow-based system reliability of water distribution networks. The surrogate model was constructed with appropriate training parameters through trial-and-error procedures. Furthermore, a deep neural network with hidden layers and neurons was composed for the high-dimensional network. For network training, the input of the neural network was defined as the damage states of the k-dimensional network facilities, and the output was defined as the network system performance. To generate training data, random sampling was performed between earthquake magnitudes of 5.0 and 7.5, and hydraulic analyses were conducted to evaluate network performance. For a hydraulic simulation, EPANET-based MATLAB code was developed, and a pressure-driven analysis approach was adopted to represent an unsteady-state network. To demonstrate the constructed surrogate model, the actual water distribution network of A-city, South Korea, was adopted, and the network map was reconstructed from the geographic information system data. The surrogate model was able to predict network performance within a 3% relative error at trained epicenters in drastically reduced time. In addition, the accuracy of the surrogate model was estimated to within 3% relative error (5% for network performance lower than 0.2) at different epicenters to verify the robustness of the epicenter location. Therefore, it is concluded that ANN-based surrogate model can be utilized as an alternative model for efficient seismic risk assessment to within 5% of relative error.