• 제목/요약/키워드: Artificial reservoir

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Simulation of Reservoir Sediment Deposition in Low-head Dams using Artificial Neural Networks

  • Idrees, Muhammad Bilal;Sattar, Muhammad Nouman;Lee, Jin-Young;Kim, Tae-Woong
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2019년도 학술발표회
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    • pp.159-159
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    • 2019
  • In this study, the simulation of sediment deposition at Sangju weir reservoir, South Korea, was carried out using artificial neural networks. The ANNs have typically been used in water resources engineering problems for their robustness and high degree of accuracy. Three basic variables namely turbid water inflow, outflow, and water stage have been used as input variables. It was found that ANNs were able to establish valid relationship between input variables and target variable of sedimentation. The R value was 0.9806, 0.9091, and 0.8758 for training, validation, and testing phase respectively. Comparative analysis was also performed to find optimum structure of ANN for sediment deposition prediction. 3-14-1 network architecture using BR algorithm outperformed all other combinations. It was concluded that ANN possess mapping capabilities for complex, non-linear phenomenon of reservoir sedimentation.

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Performance of adding waste glass and sewage sludge to reservoir-sediment aggregates

  • Chiou, Ing-Jia;Chen, Chin-Ho;Lin, Chia-Ling
    • Computers and Concrete
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    • 제13권1호
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    • pp.83-96
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    • 2014
  • Accumulated annual reservoir sedimentation in Taiwan was 14.6 million m3 in 2010, seriously endangering reservoir safety and the water supply. In addition, the sintering temperature of reservoir-sediment aggregates (RSAs) is very high, and very energy consuming consequently. Therefore, to explore the effects of admixtures on sintering behavior and performance of the aggregates, two different admixtures are blended, waste-glass and municipal sewage sludge, into reservoir sediment to make artificial aggregates. Experimental results show that the lightweight characteristics of waste-glass/reservoir-sediment aggregates (WGRSAs) are more significant than those of sewage sludge/reservoir-sediment aggregates (SSRSAs). Moreover, as sintering temperature increases, the specific gravity of WGRSAs drops more apparently. The optimum sintering temperature of pure reservoir-sediment aggregates (PRSAs), SSRSAs, and WGRSAs was $1150^{\circ}C$, $1100^{\circ}C$, and $1050^{\circ}C$, respectively. The PRSAs are normal weight with better strength; the WGRSAs are lightweight and energy-saving; and the SSRSAs are lightweight with normal strength.

Properties of artificial lightweight aggregates made from waste sludge

  • Chiou, I.J.;Chen, C.H.
    • Computers and Concrete
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    • 제8권6호
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    • pp.617-629
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    • 2011
  • In this investigation, reservoir sediment and municipal sewage sludge were sintered to form the artificial lightweight aggregates. The sintered aggregates were compared with the commercialized lightweight aggregates to in terms of potential alkali-silica reactivity and chemical stability based on analyses of their physical and chemical properties, leaching of heavy metal, alkali-silica reactivity, crystal phase species and microstructure. Experimental results demonstrated that the degree of sintering of an aggregate affected the chemical resistance more strongly than did its chemical composition. According to ASTM C289-94, all potential alkali-silica reactivity of artificial lightweight aggregates were in the harmless zone, while the potential reactivity of artificial lightweight aggregates made from reservoir sediment and municipal sewage sludge were much lower than those of traditional lightweight aggregates.

저토심 옥상녹화 시스템에서 돌나물(Sedum sarmentosum)의 생육에 대한 인공배지 종류, 토심, 그리고 배수 형태의 효과 (Effects of Artificial Substrate Type, Soil Depth, and Drainage Type on the Growth of Sedum sarmentosum Grown in a Shallow Green Rooftop System)

  • 허근영;김인혜;강호철
    • 한국조경학회지
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    • 제31권2호
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    • pp.102-112
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    • 2003
  • This study was carried out to research and develop a shallow green rooftop system which would require low maintenance and therefore could be used for existing rooftops. To achieve these goals, the conceptual model was induced by past studies and the experimental systems were deduced from the conceptual model. On the growth of Sedum sarmentosum grown in these rooftop systems, the effects of artificial substrate type, soil depth, and drainage type were investigated from 3 April to 11 October 2002. Artificial substrates were an alone type and a blending type. The alone type was an artificial substrate formulated by blending crushed porous glass with bark(v/v, 6:4). The blending type was formulated by blending the alone type with loam(v/v, 1:1). Soil depths were 5cm, loom, and 15cm. Drainage types were a reservoir-drainage type and a drainage type. The reservoir-drainage type could keep water and drain excessive water at the same time. The drainage type could drain excessive water but could not keep water. Covering area, total fresh and dry weight, visual quality, and water content per 1g dry matter were measured. All the variables were analyzed by correlation analysis and factor analysis. The results of the study are summarized as follows. The growth increment was higher in the blending type than in the alone type, the highest in loom soil depth and higher in the reservoir-drainage type than in the drainage type. The growth quality was higher in the blending type than in the alone type, the highest in l0cm soil depth, and higher in the drainage type than in the reservoir-drainage type. In consideration of the permissible load on the existing rooftops and the effects of the treatments on the growth increment and quality, the system should adopt the blending type in artificial substrate types, 5~10cm in soil depths, and the drainage type in drainage types. This system will be well-suited to the growth of Sedum sarmentosum, and when the artificial substrate was in field capacity, the weight will be 75~115kg/$m^2$.

저수지 수질관리를 위한 인공폭기 장치의 최적운전방안 (Strategic Operation of the Artificial Aeration System for Water Quality Management of the Reservoir)

  • 임경호;정상만;한영성;박영오
    • 한국물환경학회지
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    • 제18권3호
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    • pp.261-270
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    • 2002
  • The artificial aeration in the middle and the small scale reservoirs is widely used to destroy the stratified layer and algal boom. This study has been conducted at the Youncho reservoir located in Keoje island since Jan. 2000 to suggest the most suitable control strategy of the artificial aeration and reduce the side effect. The main results obtained from this research are as follows. The starting time of aeration for destratification was adjusted from the end of March to the beginning of April when the natural stratification is started. In order to prevent an anoxic condition the artificial mixing should be started by the middle of April when the DO in hypolimnion is dropped to less than $5mg/{\ell}$. The decrease DO, caused by the increase in water temperature, spreads rapidly from hypolimnion to themocline. Thermal stratification disappeared after the onset of artificial aeration within 7 days in the Yuncho reservoir. The air diffusers decrease water temperature in the layer of epilimnion and thermocline, but rise it in hypolimnion. The continuous operation of air diffuser prevent the stratification and anoxic condition in hypolimnion despite of the rising of water temperature and algal abundance. The algal abundance is not observed in effective zone by aeration. The turbidity rising problem induced from the aeration is avoided by keeping an air diffuser about 1.5m high from the bottom of lake. During the summer season, ceasing the aeration should be decided carefully. And also, it is necessary to operate the system it considering weather and temperature, and depending on the number and the position of aerators.

Ecological Studies on Togyo Reservoir in Chulwon, Korea. 8. The Epilithic Algal Community after the Experimental Acidification on the Artificial Substrata (Tiles) at Mesocosm

  • Lee, Kyung;Yoon, Sook-Kyung;Ki, Jang-Seu;Han, Myung-Soo
    • ALGAE
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    • 제19권2호
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    • pp.115-122
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    • 2004
  • The epilithic algal communities on the artificial substrata (unglazed ceramic tiles) were investigated from 5th July to 24th July 1999 with two or three days intervals for elucidating the effects of the experimental acidification. They were harvested inside the mesocosm with and without the acid treatment on Togyo reservoir within the Civilian Passage Restriction Line near Demilitarized Zone (DMZ) in Korea. After the colonization of epilithic algal community, their standing crops revealed different patterns outside and inside the mesocosm. However the time lapse of 5 days was observed on the inside with acid treatment. The dominant species were different: Achnanthes minutissima was outside but Coenochloris polycocca was inside and inside with acid treatment. The differences in floral composition were also found. Achnanthes minutissima which has been the most important species in the colonization by the epilithic algal community of the mesocosm was less important at the lower pH. Coenochloris polycocca is a species well adapted to low pH.

임계치 모형과 인공신경망 모형을 이용한 실시간 저수지 수위자료의 이상치 탐지 (Outlier Detection of Real-Time Reservoir Water Level Data Using Threshold Model and Artificial Neural Network Model)

  • 김마가;최진용;방재홍;이재주
    • 한국농공학회논문집
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    • 제61권1호
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    • pp.107-120
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    • 2019
  • Reservoir water level data identify the current water storage of the reservoir, and they are utilized as primary data for management and research of agricultural water. For the reservoir storage management, Korea Rural Community Corporation (KRC) installed water level stations at around 1,600 agricultural reservoirs and has been collecting the water level data every 10 minutes. However, various kinds of outliers due to noise and erroneous problems are frequently appearing because of environmental and physical causes. Therefore, it is necessary to detect outlier and improve the quality of reservoir water level data to utilize the water level data in purpose. This study was conducted to detect and classify outlier and normal data using two different models including the threshold model and the artificial neural network (ANN) model. The results were compared to evaluate the performance of the models. The threshold model identifies the outlier by setting the upper/lower bound of water level data and variation data and by setting bandwidth of water level data as a threshold of regarding erroneous water level. The ANN model was trained with prepared training dataset as normal data (T) and outlier (F), and the ANN model operated for identifying the outlier. The models are evaluated with reference data which were collected reservoir water level data in daily by KRC. The outlier detection performance of the threshold model was better than the ANN model, but ANN model showed better detection performance for not classifying normal data as outlier.

횡성호 식물플랑크톤에 대한 간헐식 폭기의 영향과 선택취수 (Effect on Phytoplankton by Hydraulic-Gun-Aerators and Selective Withdrawal in Hoengseung Reservoir)

  • 최일환;김학철
    • 환경영향평가
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    • 제16권1호
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    • pp.15-26
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    • 2007
  • Surface water is the main drinking water source in Korea. Algal bloom caused by phytoplankton in reservoir is common event in every summer season. To prevent or control the algal blooms, artificial circulation system has been adopted in many reservoirs, including Hoengseung reservoir. Total 7 hydraulic-gun-aerators were installed around the intake tower in Hoengseung reservoir since 2000. This study is to elucidate the effects of hydraulic-gun-aerators on phytoplankton bloom, pH, DO, temperature and evaluate the selective withdrawal and vertical distribution of phytoplankton by means of submersible fluorescence probe, which features high correlation with a standard ISO method (r=0.90, P<0.0001) for chlorophyll-a quantification.

축적 컴퓨팅을 위한 멤리스터 소자의 최적화 (Optimization of Memristor Devices for Reservoir Computing)

  • 박경우;심현진;오호빈;이종환
    • 반도체디스플레이기술학회지
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    • 제23권1호
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    • pp.1-6
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    • 2024
  • Recently, artificial neural networks have been playing a crucial role and advancing across various fields. Artificial neural networks are typically categorized into feedforward neural networks and recurrent neural networks. However, feedforward neural networks are primarily used for processing static spatial patterns such as image recognition and object detection. They are not suitable for handling temporal signals. Recurrent neural networks, on the other hand, face the challenges of complex training procedures and requiring significant computational power. In this paper, we propose memristors suitable for an advanced form of recurrent neural networks called reservoir computing systems, utilizing a mask processor. Using the characteristic equations of Ti/TiOx/TaOy/Pt, Pt/TiOx/Pt, and Ag/ZnO-NW/Pt memristors, we generated current-voltage curves to verify their memristive behavior through the confirmation of hysteresis. Subsequently, we trained and inferred reservoir computing systems using these memristors with the NIST TI-46 database. Among these systems, the accuracy of the reservoir computing system based on Ti/TiOx/TaOy/Pt memristors reached 99%, confirming the Ti/TiOx/TaOy/Pt memristor structure's suitability for inferring speech recognition tasks.

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Water Quality in Artificial Reservoirs and Its Relations to Dominant Reservoir Fishes

  • Hwang, Yoon;Han, Jeong-Ho;An, Kwang-Guk
    • 생태와환경
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    • 제42권4호
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    • pp.441-451
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    • 2009
  • The major objectives of this study were to evaluate trophic state of reservoirs using major water quality variables and its relations in terms of trophic guilds and tolerance guilds with dominant lentic fishes. For this study, we selected 6 artificial reservoirs such as Namyang Reservoir ($N_yR$), Youngsan Reservoir ($Y_sR$), Daechung Reservoir ($D_cR$), Chungju Reservoir ($Cj_R$), Chungpyung Reservoir ($C_pR$), and Paldang Reservoir ($P_dR$), and collected fish during 2000~2007 along with data analysis of water quality monitored by the ministry of environment, Korea. Biological oxygen demand (BOD) and chemical oxygen demand (COD), indicators of organic matter pollution, varied depending on types of the reservoirs and the spatial patterns in terms of trophic gradients were similar to patterns of nutrients, Secchi depth and chlorophyll-a. Analysis of trophic state index (TSI) showed that reservoirs of $D_cR$ and $C_jR$ were mesotrophy and other 4 reservoirs were eutrophic state. The relations of trophic relations showedthat TSI (Chl-a) had a positive linear function [TSI (CHL)=0.407 TSI (TP)+28.2, n=138, p<0.05] with TSI (TP) but had a weak relation with TSI (TN). Also, TSI (TP) were negatively correlated ($R^2=0.703$, p<0.05) with TSI (SD), whereas TSI (TN) was not significant (p>0.05) relations with TSI (SD). Tolerance guilds of lentic fishes, based on three types of the reservoirs, reflected the exactly water quality in the TN, TP, BOD, and COD, and similar trends were shown in the fish feeding/trophic guilds.