• 물과 미래
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• 제29권5호
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• pp.161-172
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• 1996

상용관 마찰계수 산정을 위해 개발된 기존의 Hazen-Williams 식, Colebrook-White 식과 유동훈(1995)이 제안한야 영점높이 평균법과 마찰계수 평균법의 산정식들을 비교 검토하였다. 간단한 관망에 대하여 관종류, 관경, 유속, 관길이를 변화시켜 수리조건을 구성하였으며, 네가지 상용관 마찰계수 산정식을 적용하여 구한 압력차이를 비교하여 각각의 산정식들이 가지는 특징을 논하였고, 입력자료의 변화에 따라 마찰손실이 어떠한 거동을 하는지 알아보았다. 관경을 소형관 및대형관으로 변화시켰을 때의 분석결과와 중형관일 때의 분석결과를 세 종류의 강관에 대하여 비교하였고, 유속 변화와 압력 변화와의 비교를 통하여 기존 상용관 마찰 계수 산정식의 문제점에 대하여 논하였다.

• 한국유체기계학회 논문집
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• 제11권1호
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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.

• 한국압력기기공학회 논문집
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• 제19권2호
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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.

• 한국정밀공학회지
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• 제27권4호
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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.

• 전자공학회논문지B
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• 제33B권1호
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• pp.38-48
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• 1996

본 논문에서는 컴퓨터 비젼응용을 위한 태스크레벨 파이프라인 멀티컴퓨터인 "RV860-PIPE(Realtime Vision i860 system using PIPEline)"를 구현하고 성능평가 하였다. RV860-PIPE는 MIMD형태의 아키텍쳐를 가지며, 시각처리에 적합한 ring 형태의 상호연결망(interconnection network)을 갖는 매시지 패싱타입의 컴퓨터로 구현되었다. RV860-PIPE의 단위 노드 컴퓨터는 일반적인 시각알고리즘의 수행을 위하여 법용성과 강력한 처리능력을 갖도록 64-bit 프로세서를 사용하여 설계하였다. 또한 단위 노드간 양방향 통신 및 영상 입출력기와의 통신 부담을 덜기 위한 전용화된 고속 통신 채널을 설계하였다. 구현된 시스템은 edge 검출, 실시간 이동물체 추적, 실시간 얼굴인식과 같은 시각 처리 응용프로그램들을 성능평가함으로써 컴퓨터 비젼응용에 실용적으로 적용가능함을 보였다.

• Structural Monitoring and Maintenance
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• 제3권4호
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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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• 제46권3호
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• pp.598-603
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• 2008

석유화학산업단지의 수소 네트워크 최적화는 석유화학산업 단지 내 각 업체 간 잉여 수소와 필요 수소의 양과 순도를 조사하여 최적의 분배를 구해는 것이다. 본 논문에서는 새로운 네트워크를 구성할 때 기존의 파이프라인을 고려한다면 비용을 줄일 수 있는 효과를 정량적으로 명확하게 알아보기 위해 가상의 수소 네트워크를 구성하여 기존의 파이프라인을 활용하는 것과 활용하지 않는 두 가지의 case를 모델링하고 수리계획법을 사용하여 계산, 비교해 보았다. 그 결과 기존의 파이프라인을 활용한다면 가정된 조건 하 에서 파이프비용을 20%이상 줄이고 전체네트워크 이익을 약 14억 원 증가시키는 결과를 얻을 수 있었다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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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.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 춘계학술대회 논문집
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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.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2008년도 하계학술발표대회 논문집
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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.