• Journal of Mechanical Science and Technology
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• v.20 no.10
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• pp.1576-1589
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• 2006

Most of surface water ways in Egypt suffer from the infestation of aquatic weeds especially submerged ones which cause lots of problems for the open channels and the water structures such as increasing water losses, obstructing the water flow, and reducing the efficiency of the water structures. Accurate simulation of the water flow behavior in such channels is very essential for water distribution decision makers. Artificial Neural Network (ANN) has been widely utilized in the past ten years in civil engineering applications for the simulation and prediction of the different physical phenomena and has proven its capabilities in the different fields. The present study aims towards introducing the use of ANN technique to model and predict the impact of the existence of submerged aquatic weeds on the hydraulic performance of open channels. Specifically the current paper investigates utilizing the ANN technique in developing a simulation and prediction model for the flow behavior in an open channel experiment that simulates the existence of submerged weeds as branched flexible elements. This experiment was considered as an example for implementing the same methodology and technique in a real open channel system. The results of current manuscript showed that ANN technique was very successful in simulating the flow behavior of the pre-mentioned open channel experiment with the existence of the submerged weeds. In addition, the developed ANN models were capable of predicting the open channel flow behavior in all the submerged weeds' cases that were considered in the ANN development process.

• Water for future
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• v.25 no.1
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• pp.101-110
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• 1992

In this paper for simulating spatially and temporally varied moving storm in a watershed a distributed model was developed. The model is conducted by two major flow simulations which overland flow simulation and channel network flow simulation. Two dimensional continuity equation and momentum equation of kinematic approximation are used in the overland flow simulation. On the other hand, in the channel networks simulation two types of governing equations which are one dimensional continuity and momentum equations between two adjacent sections in a channel, and continuity and energy equations at a channel junction are applied. The finite element formulations were used in the overland flow simulation and the implicit finite difference formulations were used in the channel network simulation. The finite element formulations for the overland flow are analyzed by the Gauss elimination method and the finite difference formulations for the channel network flow are analyzed by the double sweep method having advantages of computational speed and reduced computer storages. Several recurrent coefficient equations for channel network simulation are suggested in the paper.

• Journal of Korean Society on Water Environment
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• v.24 no.1
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• pp.91-98
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• 2008

This work was performed to develop a model possible to predict the influent flow and influent components, which are one of main disturbances causing process problems at the operation of municipal wastewater treatment plant. In this study, artificial neural network (ANN) was used in order to develop a model that was able to predict the influent flow, $COD_{Mn}$, SS, TN 1 day-ahead, 2day-ahead and 3 day ahead. Multi-layer feed-forward back-propagation network was chosen as neural network type, and tanh-sigmoid function was used as activation function to transport signal at the neural network. And Levenberg-Marquart (LM) algorithm was used as learning algorithm to train neural network. Among 420 data sets except missing data, which were collected between 2005 and 2006 at field plant, 210 data sets were used for training, and other 210 data sets were used for validation. As result of it, ANN model for predicting the influent flow and components 1-3day ahead could be developed successfully. It is expected that this developed model can be practically used as follows: Detecting the fault related to effluent concentration that can be happened in the future by combining with other models to predict process performance in advance, and minimization of the process fault through the establishment of various control strategies based on the detection result.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.10a
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• pp.231-234
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• 2005

The high temperature deformation behavior of AZ 31 Mg alloy was investigated by designing a back propagation neural network that uses a gradient descent-learning algorithm. A neural network modeling is an intelligent technique that can solve non-linear and complex problems by learning from the samples. Therefore, some experimental data have been firstly obtained from continuous compression tests performed on a thermo-mechanical simulator over a range of temperatures $(250-500^{\circ}C)$ with strain rates of $0.0001-100s^{-1}$ and true strains of 0.1 to 0.6. The inputs for neural network model are strain, strain rate, and temperature and the output is flow stress. It was found that the trained model could well predict the flow stress for some experimental data that have not been used in the training. Workability of a material can be evaluated by means of power dissipation map with respect to strain, strain rate and temperature. Power dissipation map was constructed using the flow stress predicted from the neural network model at finer Intervals of strain, strain rates and subsequently processing maps were developed for hot working processes for AZ 31 Mg alloy. The safe domains of hot working of AZ 31 Mg alloy were identified and validated through microstructural investigations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.9 no.4
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• pp.103-112
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• 1989

A numerical model for Steady state groundwater flow has been established to understand the groundwater flow phenomena near a radioactive waste repository. The integrated finite difference method based on a network composed of nodes and members was applied to investigate groundwater flow in homogeneous, heterogeneous and layered media. Its numerical solution was in good agreement with analytic solution. Physical phenomena associated in the groundwater flow depending on both hydraulic characteristics and effects of fractured zone were also investigated. A method by which feasible groundwater flow paths can be identified was developed. This method used the composite network for the geologic media near a repository and the direction of computed groudwater velocity. Groundwater velocity and travel time were predicted for the possible pathway form a repository to a biosphere.

• Tunnel and Underground Space
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• v.6 no.1
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• pp.30-38
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• 1996

A two dimensional analysis program for groundwater flow in fractured network was developed to analyze the influence of discontinuity characteristics on groundwater flow. This program involves the generation of discontinuities and also connectivity analysis. The discontinuities were generated by the probabilistic density function(P.D.F.) reflecting the characteristics of discontinuities. And the fracture network model was completed through the connectivity analysis. This program also involves the analysis of groundwater flow through the discontinuity network. The result of numerical experiment shows that the equivalent hydraulic conductivity increased and became closer to isotropic as the density and trace length increased. And hydraulic head decreased along the fracture zone because of much water-flow. The grouting increased the groundwater head around cavern. An analysis of groundwater flow through discontinuity network was performed around underground oil storage cavern which is now under construction. The probabilistic density functions(P.D.F) were obtained from the investigation of the discontinuity trace map. When the anisotropic hydraulic conductivity is used, the flow rate into the cavern was below the acceptable value to maintain the hydraulic containment. But when the isotropic hydraulic conductivity is used, the flow rate was above the acceptable value.

• Proceedings of the KOR-KST Conference
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• 2002.02a
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• pp.97-139
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• 2002

The aim of the present study is to find a good quality user equilibrium assignments under time varying condition. For this purpose, this study introduces a dynamic network loading method that can maintain correct flow propagation as well as flow conservation, and it develops a novel solution algorithm that does not need evaluation of the objective function by modifying the Schittenhelm (1990)'s algorithm. This novel algorithm turns out to be efficient and convenient compared to the conventional Frank-Wolfe (1956) algorithm because the former finds solutions based on routes rather than links so that it can maintain correct flow propagation intrinsically in the time-varying network conditions. The application of dynamic user equilibrium (DUE) assignment model with this novel solution algorithm to test networks including medium-sized one shows that the present DUE assignment model gives rise to high quality discrete time solutions when we adopt the deterministic queuing model for a link performance function, and we associate flows and costs in a proper way.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.4
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• pp.111-122
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• 1999

In this paper, we consider a queueing network model. where the population constraint within each subnetwork is controlled by a semaphore queue. The total number of customers that may be present in the subnetwork can not exceed a given value. Each node has a constant service time and the arrival process to the queueing network is an arbitrary distribution. A major characteristics of this model is that the lower layer flow is halted by the state of higher layer. We present some properties that the inter-change of nodes does not make any difference to customer's waiting time in the queueing network under a certain condition. The queueing network can be transformed into a simplified queueing network. A dramatic simplification of the queueing network is shown. It is interesting to see how the simplification developed for sliding window flow control, can be applied to multi-layered queueing network.

• Journal of Korea Water Resources Association
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• v.40 no.4
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• pp.325-334
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• 2007

In this study, a long-term unsteady simulation model has been developed using rigid water column theory which is more accurate than Extended-period model and more efficient comparing with water-hammer simulation model. The developed model is applied to 24-hours unsteady simulation considering daily water-demand and water-hammer analysis caused by closing a valve. For the case of 24-hours daily simulation, the pressure of each node decreases as the water demand increase, and when the water demand decrease, the pressure increases. During the simulation, the amplitudes of flow and pressure variation are different in each node and the pattern of flow variation as well as water demand is quite different than that of KYPIPE2. Such discrepancy necessitates the development of unsteady flow analysis model in water distribution network system. When the model is applied to water-hammer analysis, the pressure and flow variation occurred simultaneously through the entire network system by neglecting the compressibility of water. Although water-hammer model shows the lag of travel time due to fluid elasticity, in the aspect of pressure and flow fluctuation, the trend of overall variation and quantity of the result are similar to that of water-hammer model. This model is expected for the analysis of gradual long-term unsteady flow variations providing computational accuracy and efficiency as well as identifying pollutant dispersion, pressure control, leakage reduction corresponding to flow-demand pattern, and management of long-term pipeline net work systems related with flowrate and pressure variation in pipeline network systems

• Journal of Power System Engineering
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• v.9 no.4
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• pp.24-30
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• 2005

For a reciprocating compressor of household refrigerators, a direct analogy between the pipe flow network and the electric circuit network has been utilized to set up a mathematical model for oil supply system. Individual lubrication elements of the oil supply system, such as propeller- installed oil cap, oil galleries, radial oil feeding holes, spiral oil grooves, and various sliding surfaces have been analogized by equivalent electric elements, and these have been combined together to form an electric circuit corresponding to the whole oil supply system. By solving the closed network equations of the model, oil flow rates at various lubrication elements could be obtained. Total amount of the oil flow rate drawn into the shaft has been measured and compared reasonably well with the prediction of the numerical simulation.