• 제목/요약/키워드: Water Network

검색결과 2,041건 처리시간 0.032초

The use of artificial neural networks in predicting ASR of concrete containing nano-silica

  • Tabatabaei, Ramin;Sanjaria, Hamid Reza;Shamsadini, Mohsen
    • Computers and Concrete
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    • 제13권6호
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    • pp.739-748
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    • 2014
  • In this article, by using experimental studies and artificial neural network has been tried to investigate the use of nano-silica as concrete admixture to reduce alkali-silica reaction. If there are reactive aggregates and alkali of cement with enough moisture in concrete, a gel will be formed. Then with high reactivity between alkali of cement and existence of silica in aggregates, this gel will expand by absorption of water, and causes expansive pressure and cracks be formed. At the time passes, this gel will reduce both durability and strength of the concrete. By reducing the size of silicate to nano, specific surface area of particles and number of atoms on the surface will be increased, which causes more pozzolanic activity of them. Nano-silica can react with calcium hydroxide ($Ca(OH)_2$) and produces C-S-H gel. In this study, accelerated mortar bar specimens according to ASTM C 1260 and ASTM C 1567, with different mix proportions were prepared using aggregates of Kerman, such as: none admixture and plasticizer, different proportions of nano-silica separately. By opening the moulds after 24 hour and curing in water at $80^{\circ}C$ for 24 hour, then curing in (1N NaOH) at $80^{\circ}C$ for 14 days, length expansion of mortar bars were measured and compared. It was noted that, the lowest length expansion of a specimens shows the best proportion of admixture based on alkali-silica reactivity. Then, prediction of alkali-silica reaction of concrete has been investigated by using artificial neural network. In this study the backpropagation network has been used and compared with different algorithms to train network. Finally, the best amount of nano silica for adding to mix proportion, also the best algorithm and number of neurons in hidden layer of artificial neural network have been offered.

수처리 계측제어설비 노드들 간의 무선 안전 전송을 위한 MS-WP 암호 프로세서에 관한 연구 (A Study on the MS-WP Cryptographic Processor for Wireless Security Transmission Network among Nodes of Water-Processing Measurement-Control-Equipment)

  • 이선근;유철;박종덕
    • 한국전자통신학회논문지
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    • 제6권3호
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    • pp.381-387
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    • 2011
  • 광범위한 지역의 센서들로부터 데이터를 획득, 제어, 감시 등을 수행하는 계측제어기는 중앙 제어실과 유기적 관계를 유지한다. 그러므로 계측제어기는 유선망보다 무선망이 효율적이다. 그러나 무선망을 이용하게 되면 외부로부터 안전성에 커다란 문제가 발생된다. 그러므로 본 논문은 계측제어기의 네트워크 효율성을 증대시키기 위하여 계측제어 무선망에 적합한 MS-WP 암호시스템을 제안하였다. 제안된 MS-WP 암호시스템을 칩 레벨로 구현하여 모의실험을 수행한 결과, AES 알고리즘에 비하여 130% 처리율 증가 및 시스템 효율이 2배 증가됨을 확인하였다. 제안된 MS-WP 암호시스템은 보안성을 증대시키며 저전력화가 가능하고 처리속도가 빨라 계측제어기에 적합할 것이라 사료된다.

TOPTSIS를 이용한 낙동강 지류에서의 수질측정망 평가 연구 (A Study on Evaluation of Water Quality Measurement Network in the Nakdong River Tributary Using TOPSIS)

  • 갈병석;박재범;김성민;심규현;신상민;최수연
    • 한국습지학회지
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    • 제24권1호
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    • pp.44-51
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    • 2022
  • 본 연구에서는 TOPSIS(Techniques for Order Performance by Similarity to Ieal Solution)을 이용하여 낙동강수계 34개 지천에서의 수질측정망 설치 지점에 대하여 평가하였다. 낙동강수계에서는 지난 2011년부터 195개 지천에서 수질 및 유량을 측정하고 있다. 특히, 34개 중점관리지점은 오염원이 많고 수질이 불량한 지역으로서 지속적인 수질이 관리가 필요하다. 관리가 필요한 지점 선정을 위해 평가항목은 10개 지표를 선정하였으며 선정된 지표를 표준화하고, 엔트로피 방법(Entropy Method)을 이용하여 가중치를 부여하였다. 가중치 산정결과, 인근 측정망 유무가 가장 크고 평균 수질과 산업단지 유무도 높은 가중치를 얻었다. 평가결과, 상위 지점은 인근 측정망이 없고 산업단지와 폐수처리시설이 있고 평균 수질이 타 지점보다 높은 지점이다. 평가된 자료는 향후 낙동강수계에서의 신규 수질측정망 설정 및 지속적인 지류에서의 수질 관리를 위해 필요한 연구 결과로 판단된다.

CNN기반 정규화 리사주 도형을 이용한 전자식 밸브 고장진단알고리즘 (Fault Diagnosis Algorithm of Electronic Valve using CNN-based Normalized Lissajous Curve)

  • 박성미;고재하;송성근;박성준;손남례
    • 한국산업융합학회 논문집
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    • 제23권5호
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    • pp.825-833
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    • 2020
  • Currently, the K-Water uses various valves that can be remotely controlled for optimal water management. Valve system fault can be classified into rotor defects, stator defects, bearing defects, and gear defects of induction motors. If the valve cannot be operated due to a gear fault, the water management operation can be greatly affected. For effective water management, there is an urgent need for preemptive repairs to determine whether gear is damaged through failure prediction diagnosis.. Recently, deep learning algorithms are being applied for valve failure diagnosis. However, the method currently applied has a disadvantage of attaching a vibration sensor to the valve. In this paper, propose a new algorithm to determine whether a fault exists using a convolutional neural network (CNN) based on the voltage and current information of the valve without additional sensor mounting. In particular, a normalized Lisasjous diagram was used to maximize the fault classification performance in the CNN-based diagnostic system.

초기파손율과 성장계수에 따른 상수관 개량모델의 민감도 분석 (Sensitivity Analysis of Pipeline Rehabilitation Model According to Initial Year Break Rate and Growth Rate Coefficient)

  • 정원식;김이태
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2005년도 학술발표회 논문집
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    • pp.1302-1306
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    • 2005
  • This study has Performed to develop rehabilitation model for determination of optimal rehabilitation time on the Cast Iron Pipes (CIP) with diameter less than 300 mm in water pipeline network and to analysis the sensitivity on the rehabilitation times of developed model. In the result from the application of the field, the renovation time was faster about 10 years than the replacement time. Especially, as the difference between rehabilitation and replacement time on E-CIP was about from 3 to 5 years, and it was thought that the replacement was effective on E-CIP. To sensitivity analysis, the discount rate of coefficient was fixed at 0.08, and the values of initial year break rate(N($t_o$) and growth rate coefficient(A) were adjusted in values of 0.0009, 0.0018, 0.0027, and 0.05, 0.10, 0.15 respectively. When the values of N($t_o$) and A was increased, the results from the time of rehabilitation and replacement was faster It was thought that N($t_o$), 0.018 was reliable values on the applied pipeline through the result of the study. In case of A, the values of A above 0.1 was thought to be Proper.

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네트워크 분석기법을 이용한 상수관망에서의 수질측정지점 선정기법 제안 (Determination of Water Quality Sensor Locations in Water Distribution Systems using Network Analysis)

  • 유도근;정건희;김중훈
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2009년도 학술발표회 초록집
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    • pp.250-254
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    • 2009
  • 상수관망의 기능은 정수처리 된 양질의 물을 수용가에게 안전하게 공급하는 것이며, 이를 위해 상수관내에는 수용가에 충분한 양의 물을 공급할 수 있는 적정 유량과 압력이 유지되어야하고 최소기준치 이상의 잔류염소농도 유지 등의 적절한 수질을 만족시켜야한다. 하지만 상수관망은 상수관 파괴에 따른 오염물질 유입이나 테러와 같은 인위적인 오염물 주입 등의 갑작스런 사고에 의한 수질오염에 언제나 노출되어 있다. 이러한 수질오염사고 발생 시 신속한 대처를 위해서는 상수관망의 모든 절점에 수질측정 센서를 설치하는 것이 바람직하겠지만, 이는 경제적 측면과 센서의 유지 관리측면에서는 이상적이지 않다. 또한 발생 가능한 모든 상황에 대한 시뮬레이션 기반의 수질모델링을 통하여 적절한 수질오염 측정지점을 선정할 수도 있겠지만, 이는 상당한 시간과 계산능력을 요한다. 따라서 본 연구에서는 네트워크 분석기법 (Network Analysis)인 Betweenness Centrality와 수리해석 모형인 EPANET을 이용하여 상수관망의 수질오염측정지점 선정기법을 제안하였다. Betweenness Centrality는 네트워크를 구성하는 한 절점과 다른 한 절점을 연결시키는 특정 절점의 매개정도로 중심성을 측정하는 기법이다. Betweenness Centrality는 상수관망의 특정절점에 수질오염 사고가 발생하였을 때 오염원의 이동 가능한 경로의 수에 따라 그 값이 달라지며, 결과값에 의하여 수질오염측정지점이 선정된다. 본 연구에 의한 결과는 상수관망이 복잡하여 시뮬레이션을 통한 분석이 어렵고 많은 시간과 계산능력이 요구 될 경우 대안기법으로 활용될 수 있을 것으로 판단된다.

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Predicting the Impact of Subsurface heterogeneous Hydraulic Conductivity on the Stochastic Behavior of Well Draw down in a Confined Aquifer Using Artificial Neural Networks

  • Abdin Alaa El-Din;Abdeen Mostafa A. M.
    • Journal of Mechanical Science and Technology
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    • 제19권8호
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    • pp.1582-1596
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    • 2005
  • Groundwater flow and behavior have to be investigated based on heterogeneous subsurface formation since the homogeneity assumption of this formation is not valid. Over the past twenty years, stochastic approach and Monte Carlo technique have been utilized very efficiently to understand the groundwater flow behavior. However, these techniques require lots of computational and numerical efforts according to the various researchers' comments. Therefore, utilizing new techniques with much less computational efforts such as Artificial Neural Network (ANN) in the prediction of the stochastic behavior for the groundwater based on heterogeneous subsurface formation is highly appreciated. The current paper introduces the ANN technique to investigate and predict the stochastic behavior of a well draw down in a confined aquifer based on subsurface heterogeneous hydraulic conductivity. Several ANN models are developed in this research to predict the unsteady two dimensional well draw down and its stochastic characteristics in a confined aquifer. The results of this study showed that ANN method with less computational efforts was very efficiently capable of simulating and predicting the stochastic behavior of the well draw down resulted from the continuous constant pumping in the middle of a confined aquifer with subsurface heterogeneous hydraulic conductivity.

지하수의 영향을 고려한 사면 해석 소프트웨어 개발 (Development of a Rock Slope Analysis Software Considering Ground Water Level)

  • 양형식;하태욱;김원범;최미진;이진행
    • 터널과지하공간
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    • 제15권3호
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    • pp.213-222
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    • 2005
  • 본 연구에서는 인공신경망을 이용하여 다양한 불연속면과 지하수 조건 하에 있는 연약 암반사면의 안정성을 예측하였다 입력 자료는 사면의 높이, 경사, 절리면 경사, 지하수위를 달리한 108가지 조건에 대한 UDEC 해석결과를 이용하였고, 이를 인공신경망에 학습시킨 후, 임의의 암반사면을 대상으로 검증을 실시하였다. 검증 결과 높은 상관성$(r^2-=0.97)$을 보여주는 정확한 안전율이 예측되었으며 학습되지 않은 자료에 대해서도 같은 정도의 정확도로 안전율을 산정 할 수 있었다.

Results Of Mathematical Modeling Of Organizational And Technological Solutions Of Effective Use Of Available Resource Of Modern Roofs

  • Arutiunian, Iryna;Mishuk, Katerina;Dankevych, Natalia;Yukhymenko, Artem;Anin, Victor;Poltavets, Maryna;Sharapova, Tetiana
    • International Journal of Computer Science & Network Security
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    • 제21권1호
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    • pp.49-54
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    • 2021
  • Relative to the outer surface of the mastic coating, the reliability of the available waterproofing resource is determined by the ability to stabilize the structural characteristics in difficult climatic conditions. Organic components of mastic as a result of solar radiation, elevated temperatures and their alternating change, atmospheric oxidants, especially in industrial areas, have a tendency to self-polymerization and loss of low molecular weight components. This is the gradual loss of deformability and the transition to brittleness with its tendency to crack as the reasons for the gradual transition from normal to emergency operating condition.The presented mechanism of functioning of the coating surface indicates the expediency of increasing its components, able to stabilize the structure and prevent changes in deformability.Durability, hydrophobicity, water displacement, water absorption are accepted as estimating indicators. The main dependences of the influence of the lost additional components of mastic on the operational properties of the formed coating characterize the ability to provide successful resistance to environmental influences and longer stability. As a result, mastic acquires additional service life.

Simulation Study for a UV Water Disinfection Unit Powered by a Photovoltaic System

  • Riahi, Said;Mami, Abdelkader;Minzu, Viorel
    • International Journal of Computer Science & Network Security
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    • 제22권1호
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    • pp.175-182
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    • 2022
  • This work presents a simulation model for a specific UV disinfection system (UVDS) powered by a Photovoltaic System. The global UVDS also includes the electronic converters, Electronic Ballast, UV Lamp and Motor Pump. The equations that model the physical components' behaviour are connected to obtain a dynamic global model. The latter is converted in a Simulink/Matlab model, which allows to carry out simulation series concerning the entire UVDS. The physical parameters: the irradiation G and the temperature T, are considered as inputs. series of measurements carried out in order to show how these parameters affect the current, the voltage of the PVs and especially the value of the current of the UV lamp, on the other hand a study on the behavior and the evolution of the parameters of the motor pump such as the armature current, motor torque, speed of rotation and the water flow. The purpose of all this is to realize how important are the two parameters concerning the lamp current and the water flow because they are two very important factors to keep an adequate water quality.