• Journal of Korea Water Resources Association
• /
• v.54 no.spc1
• /
• pp.1083-1093
• /
• 2021

It is an essential to predict water usage for establishing an optimal supply operation plan and reducing power consumption. However, the water usage by consumer has a non-linear characteristics due to various factors such as user type, usage pattern, and weather condition. Therefore, in order to predict the water consumption, we proposed the methodology linking various techniques that can consider non-linear characteristics of water use and we called it as KWD framework. Say, K-means (K) cluster analysis was performed to classify similar patterns according to usage of each individual consumer; then Wavelet (W) transform was applied to derive main periodic pattern of the usage by removing noise components; also, Deep (D) learning algorithm was used for trying to do learning of non-linear characteristics of water usage. The performance of a proposed framework or model was analyzed by comparing with the ARMA model, which is a linear time series model. As a result, the proposed model showed the correlation of 92% and ARMA model showed about 39%. Therefore, we had known that the performance of the proposed model was better than a linear time series model and KWD framework could be used for other nonlinear time series which has similar pattern with water usage. Therefore, if the KWD framework is used, it will be possible to accurately predict water usage and establish an optimal supply plan every the various event.

• Journal of the Semiconductor & Display Technology
• /
• v.4 no.3 s.12
• /
• pp.29-33
• /
• 2005

As the integrated devices become more and more sophistcated, the diameter of wafers increased up to 300 mm and strict level of cleaning is necessary to remove the particulates on the surface of wafer. Therefore we need a new type of wet-station which can reduce DI water and chemical in the cleaning process. Moreover, it is important to control the temperature and the concentration of chemical in the wet-station. In the conventional chemical supply system, it is difficult not only to fit the mixing rate of chemicals in cleaning process, but also to fit the quantity and temperature. Thus, we propose a new chemicals supply system, which overcomes above problems by the analysis of fluid and thermal transfer on chemical supply system.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.25 no.11
• /
• pp.585-594
• /
• 2013

In this study, we developed a heat supply control algorithm that minimizes the heat loss in the heat distribution pipelines used for supplying heat energy to shared group housing. Controlling the temperature and flow rate of the hot water supplied to the heat exchanger for shared group housing enables us to develop a heat supply control technique that meets the heating load required by each household in a shared apartment building in accordance with changes in the outdoor air temperature, and that minimizes the heat loss occurring in the heat distribution pipeline. A one-year study in 2008 on a 1,473-household D-apartment building in Hwaseong, Gyeonggi-do, South Korea, compared the heat capacity used by each household, as well as the heat capacity supplied to the heat exchanger room of the apartment housing building, to calculate the amount of heat loss in the heat distribution pipeline. The results confirmed that 24.1% of the heat supplied was lost in the piping.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.3
• /
• pp.1488-1494
• /
• 2011

In this paper, we propose an algorithm using linear regression model that forecasts the demand of heated water in winter. To supply heated water to apartments, stores and office buildings, Korea District Heating Corp.(KDHC) operates boilers including electric power generators. In order to operate facilities generating heated water economically, it is essential to forecast daily demand of heated water with accuracy. Analysis of history data of Kangnam Branch of KDHC in 2006 and 2007 reveals that heated water supply on previous day as well as temperature are the most important factors to forecast the daily demand of heated water. When calculated by the proposed regression model, mean absolute percentage error for the demand of heated water in winter of the year 2006 through 2009 does not exceed 3.87%.

• Journal of Internet of Things and Convergence
• /
• v.10 no.2
• /
• pp.17-23
• /
• 2024

Losses in domestic water supply due to leaks are very large, such as fractures and defects in pipelines. Therefore, preventive measures to prevent water leakage are necessary. We propose the development of a leakage detection sensor utilizing vibration sensors and present an optimal leakage detection algorithm leveraging artificial intelligence. Vibrational sound data acquired from water pipelines undergo a preprocessing stage using FFT (Fast Fourier Transform), followed by leakage classification using an optimized tree-based boosting algorithm. Applying this method to approximately 260,000 experimental data points from various real-world scenarios resulted in a 97% accuracy, a 4% improvement over existing SVM(Support Vector Machine) methods. The processing speed also increased approximately 80 times, confirming its suitability for edge device applications.

• Journal of Korea Water Resources Association
• /
• v.56 no.4
• /
• pp.273-284
• /
• 2023

Water supply is continuously suffering from frequent droughts under climate change, and such extreme events are expected to become more frequent due to climate change. In this study, the decision scaling method was introduced to evaluate the drought vulnerability under future climate change in a wider range. As a result, the water supply reliability of the Boryeong Dam ranged from 95.80% to 98.13% to the condition of the aqueduct which was constructed at the Boryeong Dam. Furthermore, the Boryeong Dam was discovered to be vulnerable under climate change scenarios. Hence, genetic algorithm-based hedging rules were developed to evaluate the reduction effect of drought vulnerability. Moreover, three demand scenarios (high, standard, and low demand) were also considered to reflect the future socio-economic change in the Boryeong Dam. By analyzing quantitative reliability and the probability of extreme drought occurrence under 5% of the water storage rate, all hedging rules demonstrated that they were superior in preparing for extreme drought under low-demand scenarios.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.2
• /
• pp.297-305
• /
• 2014

Nowadays new water supply projects have been on the decline as the water-power constructions have saturated, which means that the existing power equipment have slowly aged and they require more efforts to maintain the system performance. An effective asset management method of power equipment has become a great necessity from both economical and technical aspects. To be balanced, the asset management should look into all three parts: management, engineering, and information. The purpose of this paper is to study a Risk-Based Maintenance (RBM) matrix method through the deterioration evaluation algorithm for an efficient reliability assessment of oil-immersed power transformers by considering both asset management and technical evaluation. Make use of this result, the equipment will be decided to be replace or repair otherwise on service.

• Journal of Korea Water Resources Association
• /
• v.55 no.spc1
• /
• pp.1187-1195
• /
• 2022

To run the algorithm for identifying the segments of a pipe network, the relative positional relation between nodes, pipes, and valves should be prepared as input information of a segment search algorithm. In order to more accurately identify the segments of real pipe network, pipe network GIS/CAD database that contains all isolation valves is more suitable than modeled pipe network information used for a hydraulic analysis program. In this study, we developed an algorithm that can establish the relative positional relations among node-pipe-valve suitable for pipe network segment search algorithms using GIS/CAD data of a real water supply network, and developed a MATLAB program that can implement it. The effectiveness of the developed MATLAB program was confirmed by applying it to a portion of a real municipal pipe network.

• Journal of Korea Water Resources Association
• /
• v.47 no.10
• /
• pp.921-934
• /
• 2014

The purpose of the study is to derive a long term reservoir operation method that is easy to understand and apply to practical use for dam operators. The zone based operation rule is a simple method to make operation decisions by criteria corresponding to storage zones. The reservoir storage levels dividing a reservoir, however, must be determined by some methods. We developed a reservoir operation model based on the zone based operation rule and the shuffled complex evolution algorithm (SCE-UA) was used to determine storage levels for zone division. The model was applied to Angat Dam in the Philippines that has trouble in water supply due to imbalance between supply and demand. We derived a zone based operation rule for Angat Dam and applied it to the reservoir simulation of Angat Dam using the historical inflow. The simulation results showed water supply deficit and power generation were improved by 34.5% and 21.2%, respectively, when compared with the historical records. The current study results may be used to derive a long term reservoir operation rule.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.317-321
• /
• 2022

In response to Incheon tap water accident in 2019, the Ministry of Environment has created the "Comprehensive Measures for Water Safety Management" to improve water operation management, provide systematic technical support, and respond to accidents. Accordingly, K-water is making a smart water supply management system for the entire process of tap water. In order to advance the response to water accidents, it is essential to secure the reliability of real-time water operation data such as flow rate, pressure, and water level, and to develop and apply a warning algorithm in advance using big data analysis techniques. In this paper, various statistical techniques are applied using water supply operation data (flow, pressure, water level, etc) to prepare the foundation for the selection of the optimal operating range and advancement of the monitoring and alarm system. In addition, the arrival time is analyzed through cross-correlation analysis of changes in raw water turbidity between the water intake and water treatment plants. The purpose of this paper is to study the model that predicts the raw water turbidity of a water treatment plant by applying raw water turbidity data considering the time delay according to the flow rate change.