• 한국전산유체공학회:학술대회논문집
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• 2000.10a
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• pp.101-108
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• 2000

Pipe network analysis is analyze all of it about pressure and volume flow rate through that are pipeline, junction, regulator and valve etc. In this study is compare TVD with MOC method for analysis of unsteady compressible flow in pipelines. Then, we calculated unsteady compressible flow for pipe network that periodic volume flow rate conditions.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4751-4758
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• 2022

Two-phase flow may almost exist in every branch of the energy industry. For the corresponding engineering design, it is very essential and crucial to monitor flow patterns and their transitions accurately. With the high-speed development and success of deep learning based on convolutional neural network (CNN), the study of flow pattern identification recently almost focused on this methodology. Additionally, the photographing technique has attractive implementation features as well, since it is normally considerably less expensive than other techniques. The development of such a two-phase flow pattern online monitoring system is the objective of this work, which seldom studied before. The ongoing preliminary engineering design (including hardware and software) of the system are introduced. The flow pattern identification method based on CNNs and transfer learning was discussed in detail. Several potential CNN candidates such as ALexNet, VggNet16 and ResNets were introduced and compared with each other based on a flow pattern dataset. According to the results, ResNet50 is the most promising CNN network for the system owing to its high precision, fast classification and strong robustness. This work can be a reference for the online monitoring system design in the energy system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.1
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• pp.88-93
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• 2020

Recently, SDN technology is applied to real communication business, users are getting bigger, and as the amount of data flowing in the network increases, interest in network data flow management is increasing. During this process, it must be ensured that the confidentiality, integrity, availability, and traceability of the data on the network being transmitted. In addition, it is necessary to develop an environment for observing the flow of data in real time on a network required in various fields and visually confirming the control. In this paper, first, Mininet is applied to construct a network topology and various environment attributes. Second, we added OpenDayLight in Mininet environment to develop a simulation environment to visually check and control network traffic flow in network topology.

• Journal of the Korean Geotechnical Society
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• v.15 no.5
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• pp.229-240
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• 1999

The groundwater flow and grout flow in individual rock joint and jointed rock mass are studied using various methods of analysis such as (i) the finite difference method, (ii) channel network analysis and (iii) joint network analysis. The flow behaviour is investigated in two distinguishable scales of observation: one for a rough joint of a laboratory scale having variable aperture, and the other for field- scale rock masses having three sets of intermittent joints. In the former case, the aperture-dependent channel flow is identified for both water and grout flows. The comparison of the flow rate in a rough joint is made between the finite difference analysis and existing analytical solution. In the latter case, the effects of increasing number of joints on the groundwater inflow into a circular opening of various diameters are analyzed using both the joint network method and Goodman's analytic solution. Comparisons are made between the two methods. The boundary effects in the joint network method are discussed. The inhomogeneity of joint network and its impacts on the groundwater inflow are also discussed.

• Transactions of Materials Processing
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• v.27 no.4
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• pp.227-235
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• 2018

The flow stresses have been identified prior to a numerical simulation for predicting a deformation of materials using the experimental or analytical analysis. Recently, the flow stress models considering the temperature effect have been developed to reduce the number of experiments. Artificial neural network can provide a simple procedure for solving a problem from the analytical models. The objective of this paper is the prediction of flow stress on the fiber metal laminate using the artificial neural network. First, the training data were obtained by conducting the uniaxial tensile tests at the various temperature conditions. After, the artificial neural network has been trained by Levenberg-Marquardt method. The numerical results of the trained model were compared with the analytical models predicted at the previous study. It is noted that the artificial neural network can predict flow stress effectively as compared with the previously-proposed analytical models.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.11
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• pp.243-251
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• 2021

The goal of this study is to examine the characteristics of Chinese visitors visiting Thailand, determine the rules, and give a reference for Thai tourism authorities and businesses when developing marketing strategies for the Chinese market. This paper constructs the tourism flow network and takes Bangkok as the major research target. The statistical characteristics of the network are studied using the SNA method, based on the trip notes of Thailand on www.mafengwo.cn, a prominent travel website in China as the data source. The results show that: Shanghai, Beijing, and Tianjin occupy important positions in the network; The flow direction of Chinese tourists to Thailand mainly tends to Bangkok, Chiang Mai, Pattaya, and Phuket Island; Grand Palace have strong tourism flow aggregation, diffusion, and control over other nodes in the whole network structure; Tom Yu Kuang has the greatest degree centrality in all Thai cuisine. The findings of the study can help relevant management departments create tourist policies and modify market strategies by developing the regular characteristics of China's tourism flow to Thailand in the theoretical field.

• Journal of applied mathematics & informatics
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• v.7 no.2
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• pp.379-389
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• 2000

FORD and FULKERSON have shown that a stationary maximal dynamic flow can be obtained by solving a transhipment problem associated with the static network and thereby finding the maximal temporally repeated dynamic flow. This flow is known to be an optimal dynamic flow. this paper presents the remark that temporally repeated flows may be not optimal for a minimal dynamic flow and an algorithm for such a flow. a numerical example is presented.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.3
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• pp.48-56
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• 1995

This paper presents a method of implementing efficient optical flow estimation for dynamic scene analysis using the hierarchical Hopfield neural networks. Given the two consequent inages, Zhou and Chellappa suggested the Hopfield neural network for computing the optical flow. The major problem of this algorithm is that Zhou and Chellappa's network accompanies self-feedback term, which forces them to check the energy change every iteration and only to accept the case where the lower the energy level is guaranteed. This is not only undesirable but also inefficient in implementing the Hopfield network. The another problem is that this model cannot allow the exact computation of optical flow in the case that the disparities of the moving objects are large. This paper improves the Zhou and Chellapa's problems by modifying the structure of the network to satisfy the convergence condition of the Hopfield model and suggesting the hierarchical algorithm, which enables the computation of the optical flow using the hierarchical structure even in the presence of large disparities.

• Journal of Korean Society of Transportation
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• v.20 no.1
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• pp.101-110
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• 2002

This study first explains general features of traffic assignment models and network loading methods, and investigates the relationship between them. Then it introduces a dynamic network loading method, which accounts far time variable additionally. First of all, this study suggests that it is important to consider some requirements for the dynamic network loading, such as causality, FIFO(First-In-First-Out) discipline, the flow propagation, and the flow conservation. The details of dynamic network loafing methods are explained in the form of algorithm, and numerical examples are shown in the test network by adopting deterministic queuing model for a link Performance function.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.9
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• pp.849-858
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• 2012

We proposed a scheme to accurately detect elephant flows. Along the ever increasing traffic trend, certain flows occupy the network heavily in terms of time and network bandwidth. These flows are called elephant flows. Elephant flows raises complicated issues to manage for Internet traffics and services. One of the methods to identify elephant flows is the Landmark LRU cache scheme, which improved the previous method of Least Recently Used scheme. We proposed a cache update algorithm, to further improve the existing Landmark LRU. The proposed scheme improves the accuracy to detect elephant flow while maintaining efficiency of Landmark LRU. We verified our algorithm by simulating on Sangmyung University's wireless real network traces and evaluated the improvement.