• Water for future
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• v.29 no.5
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• pp.161-172
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• 1996

Studied are the existing equations of Hazen-Williams and Colebrook-White, and the equations of Yoo's (1995) mean zero velocity point and mean friction factor developed for the estimation of commercial pipe friction factor. Simple arrangements of pipe network are devised by changing the diameter, flow discharge and length, and the characteristics of four equations are investigated by comparing the computed results of pressures at each node. Three groups of pipe diameter, small, medium, large, are considered in the comparison, and various problems of existing equations are discussed based on the computed results of pressures and velocities.

• The KSFM Journal of Fluid Machinery
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• v.11 no.1
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• pp.26-32
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• 2008

The safe operation of high pressure pipe line systems is of significant importance. Leaks due to faulty operation from the pipelines can lead to considerable product losses and to exposure of community to dangerous gases. There are several leak detection methods of pipeline network which have recently been suggested. The negative pressure wave detection technology, which has advantages of short time detection availability, accurate leaking location estimate capability and cost effective, is concentrated in this study. Theoretical analysis of the flow characteristics for leaking through a hole on the pipe wall has been performed by using Fluent 6.3, commercial CFD package. The results of 3-dimensional analysis near leaking hole confirm the occurrence of negative pressure wave, and the results of 2-dimensional analysis verify the characteristics of propagation of the wave which travels with speed equal to the speed of sound in the pipeline contents. Characteristics of leakage and pressure in a pipe with a hole have been analyzed for the various pipe and hole sizes.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.19 no.2
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• pp.93-101
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• 2023

In this study, a deep learning algorithm was used to diagnose electric potential signals obtained through CIPS and DCVG, used indirect inspection methods to confirm the soundness of buried pipes. The deep learning algorithm consisted of CNN(Convolutional Neural Network) model for diagnosing the electric potential signal and Grad CAM(Gradient-weighted Class Activation Mapping) for showing the flaw prediction point. The CNN model for diagnosing electric potential signals classifies input data as normal/abnormal according to the presence or absence of flaw in the buried pipe, and for abnormal data, Grad CAM generates a heat map that visualizes the flaw prediction part of the buried pipe. The CIPS/DCVG signal and piping layout obtained from the 3D finite element model were used as input data for learning the CNN. The trained CNN classified the normal/abnormal data with 93% accuracy, and the Grad-CAM predicted flaws point with an average error of 2m. As a result, it confirmed that the electric potential signal of buried pipe can be diagnosed using a CNN-based deep learning algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.4
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• pp.79-86
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• 2010

Mechanical structures with power sources experience repeated force produced by motors. In result, the life of the pipes reduces and ultimately, the pipes collapse. Such pipes are formed into several shapes and particularly, the U-shape pipe is damaged frequently. In most cases, the U-shape pipe is made with a straight pipe by complicated bending work. During this work process, plastic deformation of the pipe produces residual stress in the pipe. This residual stress significantly affects the fracture behavior of the pipe and induces the change of the stress ratio (min. stress/Max. stress = R). For this reason, residual stress has to be evaluated. In this paper, the residual stress of a U-shaped pipe was evaluated by FEM analysis. In addition, fatigue tests of the U-shaped pipe were performed by using a uniaxial fatigue testing machine. The results of the fatigue test were modified with the results of FEM (Finite Element Method) analysis for residual stress. The modified fatigue test results of the U-shaped pipe were compared with those of a straight pipe.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.38-48
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• 1996

We implemented and evaluated the preformance of a task level pipelined multicomputer "RV860-PIPE(Realtime Vision i860 system using PIPEline)" for computer vision applications. RV860-PIPE is a message-passing MIMD computer having ring interconnection network which is appropriate for vision processing. We designed the node computer of RV860-PIPE using a 64-bit microprocessor to have generality and high processing power for various vision algorithms. Furthermore, to reduce the communication overhead between node computers and between node computer and a frame grabber, we designed dedicated high speed communication channels between them. We showed the practical applicability of the implemented system by evaluting performances of various computer vision applications like edge detection, real-time moving object tracking, and real-time face recognition.

• Structural Monitoring and Maintenance
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• v.3 no.4
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• pp.377-393
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• 2016

The present work develops an expert system for detecting and predicting the crude oil types and properties at normal temperature ${\theta}=25^{\circ}C$, by evaluating the dielectric properties of the fluid transfused inside glass fiber reinforced epoxy (GFRE) composite pipelines, by using electrical capacitance sensor (ECS) technique, then used the data measurements from ECS to predict the types of the other crude oil transfused inside the pipeline, by designing an efficient artificial neural network (ANN) architecture. The variation in the dielectric signatures are employed to design an electrical capacitance sensor (ECS) with high sensitivity to detect such problem. ECS consists of 12 electrodes mounted on the outer surface of the pipe. A finite element (FE) simulation model is developed to measure the capacitance values and node potential distribution of ECS electrodes by ANSYS and MATLAB, which are combined to simulate sensor characteristic. Radial Basis neural network (RBNN), structure is applied, trained and tested to predict the finite element (FE) results of crude oil types transfused inside (GFRE) pipe under room temperature using MATLAB neural network toolbox. The FE results are in excellent agreement with an RBNN results, thus validating the accuracy and reliability of the proposed technique.

• Korean Chemical Engineering Research
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• v.46 no.3
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• pp.598-603
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• 2008

In petrochemical complex, Hydrogen Network optimization is surveying the extra Hydrogen and needed Hydrogen of each company and calculating the optimized distribution. This paper compares the case of using the existing pipeline and the case of not using the existing pipeline to show the effect quantitatively and clearly by modeling the both cases and using mathematical programming. As a result, using the existing pipeline can save the pipe cost over 20% and increase the whole network benefit by thirteen billion won.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.145-145
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• 2021

Water distribution networks (WDNs) are designed to satisfy water requirement of an urban community. One of the central issues in human history is providing sufficient quality and quantity of water through WDNs. A WDN consists of a great number of pipelines with different ages, lengths, materials, and sizes in varying degrees of deterioration. The available annual budget for rehabilitation of these infrastructures only covers part of the network; thus it is important to manage the limited budget in the most cost-effective manner. In this study, a novel pipe replacement scheduling approach is proposed in order to smooth the annual investment time series based on a life cycle cost assessment. The proposed approach is applied to a real WDN currently operating in South Korea. The proposed scheduling plan considers both the annual budget limitation and the optimum investment on pipes' useful life. A non-dominated sorting genetic algorithm is used to solve a multi-objective optimization problem. Three decision-making objectives, including the minimum imposed LCC of the network, the minimum standard deviation of annual cost, and the minimum average age of the network, are considered to find optimal pipe replacement planning over long-term time period. The results indicate that the proposed scheduling structure provides efficient and cost-effective rehabilitation management of water network with consistent annual budget.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.305-308
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• 1996

An analyzing method for pressure fluctuation in oil hydraulic pipe network was developed in this study. The object pipe network has multi-branch configuration, and the pipeline of it is composed of steel tubes, flexible hoses. Also, accumulators, orifices and lumped oil volume components are attached on it. Transfer matrix method, in other words impedance method, was used for the analysis. The reliablity and usefulness of the analyzing method was confirmed by comparing and investigating computed results and experimental results got in this study.

• Proceedings of the SAREK Conference
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• 2008.06a
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• pp.637-642
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• 2008

The concept of district heating involves centralised heat production where heat is distributed to consumer via a piping network. The objective of this work is to identify the Flexible Pipe from an economy, execution, maintenance point of view. Flexible Pipe has in some countries, especially in Europe, been used for many years in district heating. In spite of years of experience, there still exist doubts about the possibilities of using flexible pipes in district heating applications, mostly because of no experiences in domestic market. The advantage of flexible pipe systems is their flexibility. This holds not only for the inner pipe but also for the total pipe system including insulation and jacket. Even for the largest diameter the minimum radius of curvature is given to 1.5m. The most important difference between flexible pipe systems and preinsulated steel pipes is their simple and quick assembly. Such information could provide a basis for making reasonable hypotheses about consumer preferences, to foam a basis for making future marketing more effective.