• 제목/요약/키워드: Water model

검색결과 13,750건 처리시간 0.035초

Water Demand Forecasting by Characteristics of City Using Principal Component and Cluster Analyses

  • Choi, Tae-Ho;Kwon, O-Eun;Koo, Ja-Yong
    • Environmental Engineering Research
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    • 제15권3호
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    • pp.135-140
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    • 2010
  • With the various urban characteristics of each city, the existing water demand prediction, which uses average liter per capita day, cannot be used to achieve an accurate prediction as it fails to consider several variables. Thus, this study considered social and industrial factors of 164 local cities, in addition to population and other directly influential factors, and used main substance and cluster analyses to develop a more efficient water demand prediction model that considers unique localities of each city. After clustering, a multiple regression model was developed that proved that the $R^2$ value of the inclusive multiple regression model was 0.59; whereas, those of Clusters A and B were 0.62 and 0.74, respectively. Thus, the multiple regression model was considered more reasonable and valid than the inclusive multiple regression model. In summary, the water demand prediction model using principal component and cluster analyses as the standards to classify localities has a better modification coefficient than that of the inclusive multiple regression model, which does not consider localities.

A CHARACTERISTICS-BASED IMPLICIT FINITE-DIFFERENCE SCHEME FOR THE ANALYSIS OF INSTABILITY IN WATER COOLED REACTORS

  • Dutta, Goutam;Doshi, Jagdeep B.
    • Nuclear Engineering and Technology
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    • 제40권6호
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    • pp.477-488
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    • 2008
  • The objective of the paper is to analyze the thermally induced density wave oscillations in water cooled boiling water reactors. A transient thermal hydraulic model is developed with a characteristics-based implicit finite-difference scheme to solve the nonlinear mass, momentum and energy conservation equations in a time-domain. A two-phase flow was simulated with a one-dimensional homogeneous equilibrium model. The model treats the boundary conditions naturally and takes into account the compressibility effect of the two-phase flow. The axial variation of the heat flux profile can also be handled with the model. Unlike the method of characteristics analysis, the present numerical model is computationally inexpensive in terms of time and works in a Eulerian coordinate system without the loss of accuracy. The model was validated against available benchmarks. The model was extended for the purpose of studying the flow-induced density wave oscillations in forced circulation and natural circulation boiling water reactors. Various parametric studies were undertaken to evaluate the model's performance under different operating conditions. Marginal stability boundaries were drawn for type-I and type-II instabilities in a dimensionless parameter space. The significance of adiabatic riser sections in different boiling reactors was analyzed in detail. The effect of the axial heat flux profile was also investigated for different boiling reactors.

불소를 이용한 상수관망 수리해석의 검증 및 보정 (Verification and Calribration of Hydraulic Analysis of Water Supply System Using Fluoride Tracer)

  • 주대성;박노석;박희경;오정우
    • 상하수도학회지
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    • 제12권2호
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    • pp.76-82
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    • 1998
  • It is necessary to calculate the accurate velocity from the hydraulic model for the reliable prediction of water quality changes in water supply system. To verify the hydraulic analysis of the water supply system, fluoride was used as a tracer to calculate the travel time from the injection point to the sampling points. Results from this field experiment indicate that fluoride can be a good conservative tracer while it showed a little longitudinal dispersion along the pipe lines. And the velocity from the model was verified by these travel times and calibrated by changing the ratio of the unaccountable water. When the ratio of the unaccountable water. When the ratio of the unaccountable water was 20%, the error between the estimation of hydraulic model and the real travel time was minimum.

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장기 용수 공급계획 수립을 위한 스프레드 쉬트 모델 (A Spread Sheet Model for a Long Range Water Supply Planning)

  • 김승권
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 1992년도 수공학연구발표회논문집
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    • pp.479-489
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    • 1992
  • A mathematical model for a long range water supply planning is develoted as a dynamic capacitated facility location problem, in which operation costs and two types of fixed costs are considered. The fixed costs are for water supply systems such as dams and reservoirs and for water conveyance systems of waterways or conduits from each water supply points. A Spreadsheet model is developed to support the efficiency of user interface and to implement a heuristic solution procedure. The proposed solution procedure utilizes SOLVER tool and it has been applied to a system with fictitious data but with reality and applicability in mind. As a result of the mathematical analysis, not only the most economic construction timings of surface water supply facilities and distribution systems but also the most economical water supply operating patterns are identified.

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실시간 수질 예측을 위한 신경망 모형의 적용 (Application of Neural Network Model to the Real-time Forecasting of Water Quality)

  • 조용진;연인성;이재관
    • 한국물환경학회지
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    • 제20권4호
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    • pp.321-326
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    • 2004
  • The objective of this study is to test the applicability of neural network models to forecast water quality at Naesa and Pyongchang river. Water quality data devided into rainy day and non-rainy day to find characteristics of them. The mean and maximum data of rainy day show higher than those of non-rainy day. And discharge correlate with TOC at Pyongchang river. Neural network model is trained to the correlation of discharge with water quality. As a result, it is convinced that the proposed neural network model can apply to the analysis of real time water quality monitoring.

EFDC-NIER 모델을 이용한 영산강 하구 물흐름 특성 분석 (Analysis of Hydraulic Characteristics of Yeongsan River and Estuary Using EFDC Model)

  • 신창민;김다래;송용식
    • 한국물환경학회지
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    • 제35권6호
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    • pp.580-588
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    • 2019
  • The flow of the middle and downstream of the Yeongsan River is stagnant by two weirs of Seungchon and Juksan and the estuary dam and maintained in freshwater. In this study, the Environmental Fluid Dynamics Code-National Institute of Environment Research(EFDC-NIER) model was applied to the Yeongsan River to simulate water flow, temperature, and salinity stratification. The EFDC-NIER model is an improved model which can simulate multi-functional weirs operation, multiple algal species, and the vertical movement mechanism of algal based on the EFDC model. The simulation results for the water level, water temperature, velocity, and salinity reproduced the observed values well. The mean absolute error(MAE) of the model calibration in the annual variations of the water level was 0.1-0.3 m, water temperature was 0.8-1.7 ℃, velocity was 4.5-7.1 cm/sec, and salinity was 1.5 psu, respectively. In the case of scenario simulation for the full opening of the estuary dam, the water level of the estuary dam was directly impacted by the tide so it was predicted to rise - 1.35 m to 0.2 m on average sea level. The velocity was also predicted to increase from 2.7 cm/sec to 50.8 cm/sec, and the flow rate to increase from 53 ㎥/sec to 5,322 ㎥/sec.

신경망 모형을 적용한 금강 공주지점의 수질예측 (Water Quality Forecasting at Gongju station in Geum River using Neural Network Model)

  • 안상진;연인성;한양수;이재경
    • 한국수자원학회논문집
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    • 제34권6호
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    • pp.701-711
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    • 2001
  • 수질 인자들은 다양하고 관계가 복잡하여 수질 변화를 예측하는데 많은 어려움이 있다. 따라서 입력과 출력이 비교적 용이하고 비선형 예측에 적합한 신경망 모형을 이용하여 금강유역 공주지점의 DO, BOD, TN에 대한 월수질 예측을 수행하고 ARIMA 모형과 비교하여 적용 가능성을 검토하였다. 사용된 신경망 모형은 학습을 위해 BP(Back Propagation) 알고리즘을 적용하였으며 학습을 향상시키기 위한 모멘트-적응학습율(Moment-Adaptive learming rate) 방법을 이용한 MANN 모형, 레번버그-마쿼트(Levenberg-Marquardt) 방법을 이 용한 LMNN 모형, 그리고 정성적인 판단인자를 첨가하여 정량적인 월 수질 자료와 분별, 학습하 도록 은닉층을 분리한 MNN 모형으로 구분하였다. 대체로 신경망 모형의 예측치가 실측치에 근사한 결과를 보였으며, 은닉층을 분리한 MNN 모형이 가장 우수한 결과를 보였다.

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인공신경망기법을 이용한 하천수질인자의 예측모델링 - BOD와 DO를 중심으로- (Predictive Modeling of River Water Quality Factors Using Artificial Neural Network Technique - Focusing on BOD and DO-)

  • 조현경
    • 한국환경과학회지
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    • 제9권6호
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    • pp.455-462
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    • 2000
  • This study aims at the development of the model for a forecasting of water quality in river basins using artificial neural network technique. Water quality by Artificial Neural Network Model forecasted and compared with observed values at the Sangju q and Dalsung stations in Nakdong river basin. For it, a multi-layer neural network was constructed to forecast river water quality. The neural network learns continuous-valued input and output data. Input data was selected as BOD, CO discharge and precipitation. As a result, it showed that method III of three methods was suitable more han other methods by statistical test(ME, MSE, Bias and VER). Therefore, it showed that Artificial Neural Network Model was suitable for forecasting river water quality.

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생태도시에서의 자원활용에 관한 연구 -하수 에너지 활용을 위한 보유열량 평가- (Study on Utilizing Resources in Ecopolis -Evaluation of the Potential Heat Capacity of Sewage For Utilizing as Sewage Energy-)

  • 정용현
    • 한국환경과학회지
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    • 제12권6호
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    • pp.583-591
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    • 2003
  • The research on potential energy was conducted to conserve the high-exergy energy like primary energy and utilize waste heat from sewage. From the Point of view in using the waste heat, the energy Potential of waste water from the model house was simulated. From the results, when the heated water was supplied to the model house side in order to put unused energy to Practice use, heated water had higher energy Potential than unheated water, which was due to the discharge of most of unused energy. The possessing heat capacity of sewage from heated water was increased to 40-70 percents in comparison with that from the unheated water. Therefore, it can be used as energy source for improving coefficient of performance of heat pumps. By adopting the multiple heat pump into a model house, It showed that the possessing heat capacity of sewage was reduced. It was also found that the heat was recovered as energy source fur multiple heat pump in a model house.

ARIMA 모형에 의한 하천수질 예측

  • 류병로;한양수
    • 한국환경과학회지
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    • 제7권4호
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    • pp.433-440
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    • 1998
  • This study was carried out to develop the stream water quality model for the intaking station of Kongju waterworks in the Keum River system. The monthly water quality(total nitrogen and total phosphorus) with periodicity and trend were forecasted by multiplicative ARIU models and then the applicability of the models was tested based on 7 years of the historical monthly water quality data at Kongju intaking strate. The parameter estimation was made with the monthly observed data. The last one year data was used to compare the forecasted water Quality by ARU model with the observed one. The models are ARIMA(2,0,0)$\times$(0,1,1)l2 for total nitrogen, ARIMA(0,1,1)x(0,1,1)l2 for total phosphorus. The forecasting results showed a good agreement with the observed data. It is implying the applicability of multiplicative ARIMA model for forecasting monthly water quality at the Kongju site.

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