• 수도
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• v.23 no.6 s.81
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• pp.36-46
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• 1996

급수 수요량의 단기예측은 상수도 시스템의 유지관리 계획 수립의 중요한 구성 요소이며, 대상지역의 특성을 민감하게 반영하고 있으므로, 급수수요의 지역 특성과 관련된 수요 구조의 파악이 무엇보다 중요한 과제라 할 수 있다. 따라서 본 논문에서는 상수도 시스템의 합리적 배수 제어 획을 실시하기 위한 기초적 정보인 급수량 변동 구조에 대해 통계적인 분석을 실시하였다. 특히 일단위의 급수량에 초점을 두어 급수량의 시계열 특성과 급수량 영향 요인 분석을 통하여 대상 지역의 정상 시계열장과 급수량에 영향을 미치는 요인을 분석하였다. 또한 급수량의 계절별 단기 수요 예측 모델을 제안하기 위하여 통계적 예측 수법으로 평가 받고 있는 MARIMA (Multiple Auto Regressive Integrated Moving Average) 모델을 급수량 단기 수요 예측에 적용하여 계절별 급수 수요량을 예측하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.471-471
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• 2021

비상급수시설은 상수도 공급이 중단될 경우에 국민들에게 최소한의 음용수와 생활용수를 안정적으로 공급하기 위한 시설이다. 2018년 기준으로 상수도 보급을 통한 국내 1인 1일 급수량은 평균 348리터로 나타났지만, 국내 민방위 비상급수시설의 급수소요량은 성인 기준 1명당 25리터를 기준으로 하고 있다. 이것은 식수 9리터와 생활용수 16리터를 포함한 값이다. 그러나 왜 식수 기준을 9리터로 했는지, 생활용수 16리터로 쓸 수 있는 물 사용의 범위가 어디까지인지에 대한 구체적인 내용은 명확하지 않은 실태이다. 본 연구는 국내 민방위 비상급수시설의 급수소요량 기준을 검토하기 위한 것으로 UN, WHO, 유럽, 미국 등의 비상급수와 관련되 음용수 및 생활용수 기준을 수집하고 이를 비교 검토하였다. 그 결과 국내 민방위 비상급수시설의 급수소요량 기준이 선진국보다 적게 산정되어 있음을 알 수 있었으며, 포로수용소의 지속가능 급수지원 기준량보다도 낮은 것을 알 수 있었다. 본 연구에서는 문헌조사를 토대로 음용수, 요리, 세면, 세탁 등을 포함하여 지속가능한 적정 급수소요량 기준을 최소 50리터 이상으로 제안하였다. 한국의 경제력과 국민들의 복지를 고려할 때, 향후 민방위 비상급수시설의 급수소요량 기준을 현재보다 상향 조정하는 것이 타당함을 알 수 있었다.

• Journal of the Korean Institute of Rural Architecture
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• v.4 no.1
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• pp.19-28
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• 2002

농촌지역 공동주택의 건립에는 도시의 기반시설이 취약하므로 이에 충족하는 사전조치가 따라야 한다. 도시기반 시설 중에서도 건축의 기본설비인 상수도(급수)설비는 없어서는 안될 기본설비시설이라 할 수 있다. 본 연구에서 조사 분석한 것을 보면 급수사용량에 있어서 하절기인 7, 8월에 급수사용량이 최대치를 나타나고 있으나 일부지역에서는 계절에 관계없이 이사철에 최대급수량이 발생하는 것으로 분석되었다. 따라서 최대사용량을 조사, 분석한 결과 하절기와 이사철에 급수사용량이 많음을 알 수 있다. 농촌 공동주택에 있어서 급수사용량을 충분히 확보하기 위해서는 지하수 개발을 최대 급수량 이상의 수원을 확보해야 함을 전제로 하고 있다. 급수사용량 이상의 정수설비도 수반되어야 한다.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2622-2624
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• 2005

화력발전소 보일러의 급수량은 유출되는 증기량에 맞추어 자동 조절된다. 유출 증기량이 변하는 상황에서도 이에 상응하는 급수량은 실시간으로 조절되어야 한다. 증기량과 급수량에 차이가 있으면 보일러의 보유 수량과 드럼의 수위가 변하게 되므로, '드림수위를 일정하게 유지하는 것'이 급수량제어의 목표라고 할 수 있다. 본 논문은 실제 운용되고 있는 설비를 대상으로 고찰한 내용이며, 급수펌프 구동력으로는 중기터빈을 사용한다. 증기터빈과 급수펌프는 같은 축으로 연결되어있으며, 급수량 조절은 급수펌프의 회전속도를 제어함으로써 이루어진다. 터빈에 사응되는 증기는, 고압과 저압 2종류이며, 저압 증기가 부족한 경우에 고압증기를 사용하는 구성으로 되어있다. 증기 밸브의 유량 특성에는 비선형성을 많이 포함하고 있었다. 이 외에도 급수펌프가 갖는 비선형성을 분석하였으며, 이 특성들을 모두 종합한 '증기터빈 속도제어기 튜닝 곡선'을 제시하였다

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.821-832
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• 1998

This study investigates the prediction of daily water supply, which is a necessary for the efficient management of water distribution system. Fuzzy neuron, 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 adaptive learning method by which a membership function and fuzzy rules were adapted for daily water supply prediction. This study was investigated methods for predicting water supply based on data about the amount of water supplied to the city of Kwangju. 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 supplied (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 18.35% 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.

• Journal of Korea Water Resources Association
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• v.30 no.1
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• pp.45-54
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• 1997

The correct estimation of the daily or hourly urban water demand is required for the efficient management and operation of the water supply facilities. The prediction of water supply demand are regression model and time series method, the optimum ARIMA (Auto Regressive Integrated Moving Average) model was sought for the daily urban water demand estimation in this paper. The data used for this study were obtained from the city of Kwangju Korea. The raw data used in this study were rearranged 15, 30, 60, 90 days for the purpose of analysis. The statistical analysis was applied to the data to obtain the ARIMA model. As a result, the parameters determining the ARIMA model was obtained. The accuracy of the model was 2% of water supply. The developed model was found to be useful for the practical operation and management of the water supply facilities.

• Water for future
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• v.28 no.6
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• pp.147-158
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• 1995

The purpose of this study is to establish a method of estimating the daily urban water demand using statistical model. This method will be used for the development of the efficient management and operation of the water supply facilities. The data used were the daily urban water use, the population, the year lapse and the weather conditions such as temperature, precipitation, relative humidity, etc. Kwangju city was selected for the case study area. The raw data used in this study were rearranged either by month or by season for the purpose of analysis, and the statistical analysis was applied to the data to obtain the regression model. As a result, the multiple linear regression model was developed to estimate the daily urban water use based on the seather condition. The regression constant and the model coefficients were determined for each month of a year. The accuracy of the model was within 3% of average error and within 10% of maximum error. The developed model was found to be useful to the practical operation and management of the water supply facilities.

• Water for future
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• v.27 no.4
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• pp.135-143
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• 1994

The purpose of this study was to improve the understanding of the characteristics of the daily urban water use. The city of Kwangju in Korea was selected as a study area. The population of Kwangju in the end of 1993 was more than one million and two hundred thousand peoples. The average of daily water use in 1993 was about three hundred and fifty thousand tons a day. The variation of the urban water demand trend with time for a day was studied. One day was devided into 12 divisions with a 2hour increment. The water use demand for the given time interval of a day was observed. The water use index was defind in percentage that indicates the ratio of the amount of water use for a time interval to the amount of water use for a day. The water use index was found to be useful to manage and to operate the water supply systems. In addition to this, the probability distribution of the water use demand for each time interval was tested using the K-S(Komogorov-Smirnov) method. The normal distribution type was found to be appropriate as the probability distribution type for the variation of water demand for the given time interval of a day.

• Journal of Korea Water Resources Association
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• v.31 no.2
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• pp.155-165
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• 1998

As an improvement on qualities of lives and a change in the habitual ways people eat require more water to be used for daily lives, the amount of wastewater generated from our usual lives is also expected to be in higher rate of consumption. The unit loading factor of sewage flow-rate based upon the number of people living in the apartment complexes has to be found for the design of the sewage or wastewater treatment facilities. These data are definitely thought to be useful for the plans to operate the sewage treatment facilities and for those to establish the plans toward a management of water qualities. Thus this study has shown that the data regarding the water supplies and the number of apartment residents within the 123 districts of KNHC(Korea National Housing Corporation) were collected and analyzed. One district in Seoul and the other local district were chosen an the experimental sites for th hourly, daily, weekly and seasonal measurements of the influent sewage flow-rate. The unit loading factor of influent sewage flow-rate were determined through the comparison of total sewage amount in combination with the number of people residing in two apartment complexes with supplying amount of water.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1560-1566
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• 2017

Recently, accumulation of data on pig farm is enabled through the wide spread of smart pig farm equipped with Internet-of-Things based sensors, and various machine learning algorithms are applied on the data in order to improve the productivity of pig farm. Herein, multiple machine learning schemes are used to predict the water usage in pig farm which is known to be one of the most important element in pig farm management. Especially, regression algorithms, which are linear regression, regression tree and AdaBoost regression, and classification algorithms which are logistic classification, decision tree and support vector machine, are applied to derive a prediction scheme which forecast the water usage based on the temperature and humidity of pig farm. Through performance evaluation, we find that the water usage can be predicted with high accuracy. The proposed scheme can be used to detect the malfunction of water system which prevents the death of pigs and reduces the loss of pig farm.