• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.149-158
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• 2002

For the purpose of preciously describing real time traffic pattern in urban road network, dynamic network loading(DNL) models able to simulate traffic behavior are required. A number of different methods are available, including macroscopic, microscopic dynamic network models, as well as analytical model. Equivalency minimization problem and Variation inequality problem are the analytical models, which include explicit mathematical travel cost function for describing traffic behaviors on the network. While microscopic simulation models move vehicles according to behavioral car-following and cell-transmission. However, DNL models embedding such travel time function have some limitations ; analytical model has lacking of describing traffic characteristics such as relations between flow and speed, between speed and density Microscopic simulation models are the most detailed and realistic, but they are difficult to calibrate and may not be the most practical tools for large-scale networks. To cope with such problems, this paper develops a new DNL model appropriate for dynamic traffic assignment(DTA), The model is combined with vertical queue model representing vehicles as vertical queues at the end of links. In order to compare and to assess the model, we use a contrived example network. From the numerical results, we found that the DNL model presented in the paper were able to describe traffic characteristics with reasonable amount of computing time. The model also showed good relationship between travel time and traffic flow and expressed the feature of backward turn at near capacity.

• KNOM Review
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• v.22 no.2
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• pp.1-11
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• 2019

The paradigm of science and technology and R&D system changes from the existing form of independent research to community research which transmits and stores large-capacity data generated from observation and experiment to the research site through a high-speed network. Network-dependent advanced research is improves form of collaboration, sharing, globalization. For this purpose, not only the integration of science and IT technology, but also the optimized network infrastructure and technology for real-time sharing of the enormous data is necessary. This paper explains the direction of change through the case of KREONET's network-dependent advanced research and analyzes the technology and network resources supported in each research field. Through this, we propose a network optimization model for each advanced research field with the main data flow and satisfy the network required performance by advanced applications on KREONET.

• Applied Science and Convergence Technology
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• v.25 no.4
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• pp.67-72
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• 2016

This article describes an electrical network analysis (ENA) method to calculate the pressure distribution of a vacuum system in a molecular flow regime. The vacuum system was modeled using electrical components. For an accurate analysis, a complexly combined pipe model, excluding entrance conductance, was employed and the pressure distribution was simulated using ENA. A vacuum system comprising three vacuum pumps was used for simplicity. In addition, the ENA results were compared with results from finite element analysis (FEA) and experimental measurements. The pressure distribution profiles estimated from ENA, performed using the LTSpice IV software, were in agreement with FEA and experimental results.

• The KSFM Journal of Fluid Machinery
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• v.11 no.2
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• pp.46-54
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• 2008

This study presents a numerical optimization to optimize an axial flow fan blade to increase the efficiency. The radial basis neural network is used as an optimization method with the numerical analysis by Reynolds-averaged Navier-Stokes equations using SST model as turbulence closure. Four design variables related to airfoil maximum camber, maximum camber location, leading edge radius and trailing edge radius, respectively, are selected, and efficiency is considered as objective function which is to be maximized. Thirty designs are evaluated to get the objective function values of each design used to train the neural network. Optimum shape shows the efficiency increased by 1.0%.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.12 s.243
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• pp.1291-1298
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• 2005

Since the interior shape of a pressure regulator is complex and the change of fluid resistance at each operation condition is rapid and big, the pressure regulator can become the major factor that causes big loss in pipelines. So the suitable pressure regulator modeling by each operation condition is important to obtain reliable results especially in small scale pipeline network analysis. And in order to prevent the condensation and freezing problems, it is needed to confirm both whether temperature recovery is achieved after passing by the pressure regulator's narrow neck and how much amount of low temperature area that can cause condensate accumulation is distributed by various PCV models at every inlet-outlet pressure ratio. In this research, the numerical model resembling P company pressure regulator that is used widely for high pressure range in commercial, is adopted as the base model of CFD analysis to investigate pressure regulator's flow characteristics at each pressure ratio. Additionally it is also introduced to examine pressure regulator's critical flow characteristics and possibility of condensation or freezing at each pressure ratio. Furthermore, the comparison between the results of CFD analysis and the results of analytic solution obtained by compressible fluid-dynamics theory is attempted to validate the results of CFD modeling in this study and to estimate the accuracy of theoretical approach at each pressure ratio too.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.12 s.243
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• pp.1299-1306
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• 2005

The suitable pressure regulator modeling at each opening ratio and pressure ratio is very important to obtain reliable results, especially in small scale pipeline network analysis such as a pressure regulator system. And it is needed to confirm both whether temperature recovery is achieved after passing by the pressure regulator's narrow neck and how much amount of low temperature area that can cause condensate accumulation is distributed by various PCV models and driving conditions. In this research, the numerical model resembling P company pressure regulator that is used widely for high pressure range in commercial, is adopted as the base model of CFD analysis to investigate pressure regulator's flow characteristics at each pressure ratio and opening ratio. And it is also introduced to examine pressure regulator's critical flow characteristics and possibility of condensation or freezing at each pressure ratio and opening ratio. Additionally, the comparison between the results of CFD analysis and the results of analytic solution obtained by compressible fluid-dynamics theory is attempted to validate the results of CFD modeling in this study and to estimate the accuracy of theoretical approach at each pressure ratio and opening ratio too.

• ETRI Journal
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• v.42 no.2
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• pp.186-195
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• 2020

Software-defined networking (SDN) acts as a centralized management unit, especially in a network with devices that operate under the transport layer of the OSI model. However, when a network with layer 7 middleboxes (MBs) is considered, current SDNs exhibit limitations. As such, to achieve a real-centralized management unit, a new architecture is required that decouples the data and control planes of all network devices. In this report, we propose such a complementary architecture to the current SDN in which SDN-enabled MBs are included along with contemporary SDN-enabled switches. The management unit of this architecture improves network performance and reduces routing cost by considering the status of the MBs during flow forwarding. This unit consists of the following two parts: an SDN controller (SDNC) and a middlebox controller (MBC). The latter selects the best MBs for each flow and the former determines the best path according to its routing algorithm and provides information via the MBC. The results show that the proposed architecture improved performance because the utilization of all network devices including MBs is manageable.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.113-116
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• 2021

As artificial intelligence technologies, including deep learning, develop, these technologies are being introduced to code similarity analysis. In the traditional analysis method of calculating the graph edit distance (GED) after converting the source code into a control flow graph (CFG), there are studies that calculate the GED through a trained graph neural network (GNN) with the converted CFG, Methods for analyzing code similarity through CNN by imaging CFG are also being studied. In this paper, to determine which approach will be effective and efficient in researching code similarity analysis methods using artificial intelligence in the future, code similarity is measured through funcGNN, which measures code similarity using GNN, and Siamese Network, which is an image similarity analysis model. The accuracy was compared and analyzed. As a result of the analysis, the error rate (0.0458) of the Siamese network was bigger than that of the funcGNN (0.0362).

• Tunnel and Underground Space
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• v.11 no.2
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• pp.156-166
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• 2001

A stochastic continuum(SC) modeling technique was developed to simulate the groundwater flow pathway in fractured rocks. This model was developed to overcome the disadvantageous points of discrete fracture network(DFN) modes which has the limitation of fracture numbers. Besides, SC model is able to perform probabilistic analysis and to simulate the conductive groundwater pathway as discrete fracture network model. The SC model was formulated based on the discrete fracture network(DFN) model. The spatial distribution of permeability in the stochastic continuum model was defined by the probability distribution and variogram functions defined from the permeabilities of subdivided smaller blocks of the DFN model. The analysis of groundwater travel time was performed to show the consistency between DFN and SC models by the numerical experiment. It was found that the stochastic continuum modes was an appropriate way to provide the probability density distribution of groundwater velocity which is required for the probabilistic safety assessment of a radioactive waste disposal facility.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.907-913
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• 1999

For an automated transportation system like PRT(Personal Rapid Transit) system or IVHS, an efficient vehicle-merging algorithm is required for smooth operation of the network. For management of merging, collision avoidance between vehicles, ride comfort, and the effect on traffic should be considered. This paper proposes an unmanned vehicle-merging algorithm that consists of two procedures. First, a longitudinal control algorithm is designed to keep a safe headway between vehicles in a single lane. Secondly, 'vacant slot and ghost vehicle' concept is introduced and a decision algorithm is designed to determine the sequence of vehicles entering a converging section considering energy consumption, ride comfort, and total traffic flow. The sequencing algorithm is based on fuzzy rules and the membership functions are determined first by an intuitive method and then trained by a learning method using a neural network. The vehicle-merging algorithm is shown to be effective through simulations based on a PRT model.