• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1295-1303
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• 2022

As the role of water distribution networks (WDNs) becomes more important, identifying abnormal events (e.g., pipe burst) rapidly and accurately is required. Since existing approaches such as field equipment-based detection methods have several limitations, model-based methods (e.g., machine learning based detection model) that identify abnormal events using hydraulic simulation models have been developed. However, no previous work has examined the impact of data uncertainties on the results. Thus, this study compares the effects of measurement error-induced pressure data uncertainty in WDNs. An artificial neural network (ANN) is used to predict nodal pressures and measurement errors are generated by using cumulative density function inverse sampling method that follows Gaussian distribution. Total of nine conditions (3 input datasets × 3 output datasets) are considered in the ANN model to investigate the impact of measurement error size on the prediction results. The results have shown that higher data uncertainty decreased ANN model's prediction accuracy. Also, the measurement error of output data had more impact on the model performance than input data that for a same measurement error size on the input and output data, the prediction accuracy was 72.25% and 38.61%, respectively. Thus, to increase ANN models prediction performance, reducing the magnitude of measurement errors of the output pressure node is considered to be more important than input node.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.232-238
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• 2013

This paper study the position estimation of MBK system according to the non-linear filter for non-Gaussian noise in underwater sensor networks. In the filter to estimate location, recently, the extended Kalman filter (EKF) and particle filter are getting attention. EKF is widely used due to the best algorithm in the Gaussian noise environment, but has many restrictions on the usage in non-Gaussian noise environment such as in underwater. In this paper, we propose the improved One-Dimension Particle Filter (ODPF) using the distribution re-interpretation techniques based on the maximum likelihood. Through the simulation, we compared and analyzed the proposed particle filter with the EKF in non-Gaussian underwater sensor networks. In the case of both the sufficient statistical sample and the sufficient calculation capacity, we confirm that the ODPF's result shows more accurate localization than EKF's result.

• International Journal of Knowledge Content Development & Technology
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• v.10 no.4
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• pp.29-46
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• 2020

The paper describes the quantitative and qualitative dimensions of artificial neural networks (ANN) in India in the global context. The study is based on research publications data (8260) as covered in the Scopus database during 1999-2018. ANN research in India registered 24.52% growth, averaged 11.95 citations per paper, and contributed 9.77% share to the global ANN research. ANN research is skewed as the top 10 countries account for 75.15% of global output. India ranks as the third most productive country in the world. The distribution of research by type of ANN networks reveals that Feed Forward Neural Network type accounted for the highest share (10.18% share), followed by Adaptive Weight Neural Network (5.38% share), Feed Backward Neural Network (2.54% share), etc. ANN research applications across subjects were the largest in medical science and environmental science (11.82% and 10.84% share respectively), followed by materials science, energy, chemical engineering and water resources (from 6.36% to 9.12%), etc. The Indian Institute of Technology, Kharagpur and the Indian Institute of Technology, Roorkee lead the country as the most productive organizations (with 289 and 264 papers). Besides, the Indian Institute of Technology, Kanpur (33.04 and 2.76) and Indian Institute of Technology, Madras (24.26 and 2.03) lead the country as the most impactful organizations in terms of citation per paper and relative citation index. P. Samui and T.N. Singh have been the most productive authors and G.P.S.Raghava (86.21 and 7.21) and K.P. Sudheer (84.88 and 7.1) have been the most impactful authors. Neurocomputing, International Journal of Applied Engineering Research and Applied Soft Computing topped the list of most productive journals.

• The Journal of the Acoustical Society of Korea
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• v.17 no.1E
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• pp.54-65
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• 1998

This study attempts to test the classifying performance of a neural network and thereby examine its applicability to the signals distorted in a shallow water environment. Linear frequency modulated(LFM) signals are simulated by using an acoustic model and also measured through sea experiment. The network is constructed to have three layers and trained on both data sets. To get normalized power spectra as feature vectors, the study considers the three transforms : shot-time Fourier transform (STFT), wavelet transform (WT) and pseudo Wigner-Ville distribution (PWVD). After trained on the simulated signals over water depth, the network gives over 95% performance with the signal to noise ratio (SNR) being up to-10 dB. Among the transforms, the PWVD presents the best performance particularly in a highly noisy condition. The network performs worse with the summer sound speed profile than with the winter profile. It is also expected to present much different performance by the variation of bottom property. When the network is trained on the measured signals, it gives a little better results than that trained on the simulated data. In conclusion, the simulated signals are successfully applied to training a network, and the trained network performs well in classifying the signals distorted by a surrounding environment and corrupted by noise.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.108-108
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• 2018

상수관의 노후화 혹은 공사 중 작업자의 실수, 또는 자연재해 등에 의해 상수관망 내 파손 관이 발생할 경우 파손된 관의 보수 및 교체 작업을 위해서는 파손 관과 인접한 밸브를 차폐하게 된다. 이로 인하여 관망의 일부 지역에 물 공급이 차단되는 단수구역이 발생하게 되며, 단수구역은 밸브를 닫음으로 인해 파손 관과 함께 격리되는 직접고립지역(segment)과 직접고립지역을 차폐함으로써 의도치 않게 수원으로부터 물 공급이 차단되는 간접고립지역(unintended isolation)으로 구분할 수 있다. 간접고립지역은 차폐된 직접고립지역으로 인해 수원으로부터의 유일한 용수공급 노선이 차단되어 발생한다. 관 파손에 의한 단수 피해를 현실적으로 모의하기 위해서는 밸브위치에 따른 단수구역을 정확히 산정할 필요가 있다. 단수구역은 파손관의 위치뿐만 아니라 차단 밸브의 개수 및 위치에 따라 달라진다. 따라서, 관 파손에 의한 단수피해를 최소화하기 위해서는 각 관로의 파손확률과 절점의 중요도를 고려하여, 적절한 밸브의 위치를 선정해야 한다. 본 연구에서는 관 파손에 따른 단수상황을 모의하여 파손 관에 의한 직, 간접 단수구역을 탐색한 후, 단수용량을 파악하고 이를 최소화하기 위한 밸브의 적정 위치를 최적화 알고리즘을 이용하여 결정하는 방안을 제시하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.401-401
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• 2019

상수관망시스템은 정수처리 된 용수를 수요처에 공급하는 사회기반시설물이며, 주로 지하에 매설되는 시설물의 특성상 관로에 누수가 발생하였을 경우, 정확한 발생지점을 파악하기가 어렵다. 특히, 지진에 의해 시스템 내 다중지점에 누수가 발생할 경우, 장기간 경제적 손실과 사용자의 불편이 예상되므로 신속히 누수지점을 파악한 후, 피해 관로의 적절한 교체 혹은 보수가 이루어져야 한다. 본 연구에서는 지진으로 인해 상수관망에 발생한 다중 누수관로의 정확한 탐지를 위해 다양한 누수탐지 기법을 제안하고 모의결과를 비교, 분석하였다. 가상의 다중 누수 시나리오를 모의한 후, 시스템 내 설치된 수압계와 유량계의 누수발생 전, 후 모니터링 값을 이용하여 1) 최적화 알고리즘을 이용한 Calibration 기법, 2) 수리해석을 통한 누수지점 역추적 기법, 3) 인공신경망을 이용한 Pattern 학습법 등을 적용하였다. 동일한 다중 누수 시나리오를 각 누수탐지 기법에 적용함으로써 누수지점 산정 결과에 대한 정확도를 비교, 분석하였다. 본 연구는 최근 국내에서 발생빈도가 높아지고 있는 지진재해 발생에 대비하여 상수관망시스템의 지진피해 복구 연구를 위해 활용될 수 있을 것으로 기대한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.90-90
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• 2020

상수관망시스템은 관할 지역 내 생활 및 공업용수를 공급하기 위한 사회기반시설물로써, 비상시에도 사용자의 용수 수요를 충족하기 위한 안정적인 성능이 요구된다. 이러한 상수관망시스템의 용수공급능력은 비상시 용수공급가능량, 공급수압 등 여러 가지 수리해석 결과를 통해 판단할 수 있다. 그러나, 시스템의 설계 및 운영 과정에서 다양한 성능들을 시간·공간적으로 모두 고려하는 것은 매우 복잡한 과정을 거치므로, 복합적인 용수공급 성능을 집약적으로 평가하기 위한 신뢰도 지수들이 개발되었다. 여기서 신뢰도 지수들은 각각의 이론적 접근방법에 따라 시스템의 특정 성능에 다소 편중된 평가 결과를 갖는 것으로 알려져 있으며, 따라서 상수관망시스템의 설계 및 운영 시, 목적과 특성에 맞는 적합한 신뢰도 지수를 선정하고, 적용하기 위한 분석이 필요하다. 본 연구에서는 상수관망시스템의 구조적 특성 및 핵심 성능에 따른 신뢰도 지수별 적용성을 평가하기 위해, 다양한 형태의 네트워크에서 몇 가지 공급부하 시나리오를 바탕으로 수리해석 결과와 신뢰도 지수 간의 상관성을 분석하였다. 또한, 다기준 분석기법을 통해 종합적인 시스템 핵심 성능에 대한 신뢰도 지수의 상관성을 분석함으로써, 시스템 전반에 대한 신뢰도 지수별 적용성을 함께 평가하였다. 본 연구 결과는 향후 상수관망시스템의 설계 또는 기존 시스템의 보강 및 운영계획 수립 등을 위한 연구에서 폭넓게 활용할 수 있을 것으로 기대된다.

• Journal of Korea Water Resources Association
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• v.50 no.12
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• pp.803-813
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• 2017

Recently, various studies have been conducted to optimize the pump operation scheduling and/or the pump/tank size minimizing the system cost of water distribution network. Prior to that, it is important to understand the sensitivity of pump/tank size on the system cost and overall water quality. Here, we have performed the sensitivity analysis to investigate the effect of pump/tank size on the economic cost (construction and operation) and water quality (water age). The analysis was applied on a real, large-scale water transmission network currently operating in South Korea. The results revealed that the pump/tank size has a strong influence on system construction/operation costs. Especially, the tank size has a significant effect on the system-wide water quality. In the case of applied networks, the operating cost decreases as the capacity of the facility increases, but the design cost increases. Using a sensitivity analysis, a suitable range of pump/tank size could be suggested to minimize costs and stabilize the water quality at the same time prior to a system design.

• Journal of Korean Society of Water and Wastewater
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• v.33 no.5
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• pp.353-366
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• 2019

This research proposes an optimal flushing operation technique in an effort to prevent secondary water pollutions and accidents in aged pipes, and to improve the cleaning effect of unidirectional flushing. Water flow directions were analyzed using EPANET 2.0, while flushing and air scouring experiments in forward and reverse directions were performed in the field. In 42 experiments, average residual chlorine concentration and turbidity were improved after cleaning compared to before cleaning. It was found that even when the same cleaning method was used, further improvement of cleaning effect was possible by applying air injection and reverse direction cleaning techniques. By means of one-way ANOVA(Analysis of variance), it was also possible to statistically verify the need of actively utilizing air injection and reverse direction cleaning. Based on correlation between turbidity and TSS, the total amount of suspended solids removal was estimated for 874 flushing operations and 194 air scouring operations. The result showed that air scouring used more discharge water than flushing by an average of $4.9m^3$ yet with larger amounts of suspended solids removal by an average of 145.9 g. The result of analysis on turbidity values from 887 flushing operations showed low cleaning effect of unidirectional flushing for the pipes with diameters over 300 mm. In addition, the turbidity values measured during cleaning showed an increasing tendency as pipe age increased. The methodology and results of this research are expected to contribute to the efficient maintenance and improvement of water quality in water distribution networks. Follow-up research involving the measurement of water quality at regular time intervals during cleaning would allow a more accurate comparison of discharge water quality characteristics and cleaning effects between different cleaning methods. To this end, it is considered necessary to develop a standardized manual that can be used in the field and to provide relevant trainings.

• Journal of Korea Water Resources Association
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• v.51 no.11
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• pp.989-998
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• 2018

Connectivity between water source and demand node can be served as a critical system performance indicator of the degree of water distribution network (WDN)' failure severity under abnormal conditions. Graph theory-based approaches have been widely applied to quantify the connectivity due to WDN's graph-like topological feature. However, most previous studies used undirected-unweighted graph theory which is not proper to WDN. In this study, the directed-weighted graph theory was applied for WDN connectivity analyses. We also proposed novel connectivity indicators, Source-to-Node Shortest Pathway (SNSP) and SNSP-Degree (SNSP-D) which is an inverse of the SNSP value, that does not require complicate hydraulic simulation of a WDN of interest. The proposed SNSP-D index was demonstrated in total 42 networks in J City, South Korea in which Pearson Correlation Coefficient (PCC) between the proposed SNSP-D and four other system performance indicators was computed: three resilience indexes and an energy efficiency metric. It was confirmed that a system representative value of the SNSP-D has strong correlation with all resilience and energy efficiency indexes (PCC = 0.87 on average). Especially, PCC was higher than 0.93 with modified resilience index (MRI) and energy efficiency indicator. In addition, a multiple linear regression analysis was performed to identify the system hydraulic characteristic factors that affect the correlation between SNSP-D and other system performance indicators. The proposed SNSP is expected to be served as a useful surrogate measure of resilience and/or energy efficiency indexes in practice.