• Title/Summary/Keyword: pipe-network model

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Development and Application of Pipeline Network Optimization Simulator (파이프라인 네트워킹 최적화 모델의 개발 및 활용)

  • Sung Won-Mo;Kwon Oh-kwang;Lee Chung-Hwan;Huh Dae-ki,
    • Journal of the Korean Institute of Gas
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    • v.1 no.1
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    • pp.56-63
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    • 1997
  • This paper presents a hybrid network model(HY-PIPENET) implementing a minimum cost spanning tree(MCST) network algorithm to be able to determine optimum path and constrained derivative(CD) method to select optimum Pipe diameter. The HY-PIPENET has been validated with the published data of 6-node/7-pipe network. Networking system and also this system has been optimized with MCST-CD method. As a result, it was found that the gas can be sufficiently supplied at the lower pressure with the smaller diameters of pipe compared to the original system in 6-node/7-pipe network. Hence, the construction cost was reduced about $40\%$ in the optimized system. The hybrid networking model has been also applied to a complicated domestic gas pipeline network in metropolitan area, Korea. In this simulation, parametric study was peformed to understand the role of each individual parameter such as source pressure, flow rate, and pipe diameter on the optimized network. From the results of these simulations, we have proposed the optimized network as tree-type structure with optimum pipe diameter and source pressure in metropolitan area, Korea, however, this proposed system does not consider the environmental problems or safety concerns.

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Statistical Approach for Corrosion Prediction Under Fuzzy Soil Environment

  • Kim, Mincheol;Inakazu, Toyono;Koizumi, Akira;Koo, Jayong
    • Environmental Engineering Research
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    • v.18 no.1
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    • pp.37-43
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    • 2013
  • Water distribution pipes installed underground have potential risks of pipe failure and burst. After years of use, pipe walls tend to be corroded due to aggressive soil environments where they are located. The present study aims to assess the degree of external corrosion of a distribution pipe network. In situ data obtained through test pit excavation and direct sampling are carefully collated and assessed. A statistical approach is useful to predict severity of pipe corrosion at present and in future. First, criteria functions defined by discriminant function analysis are formulated to judge whether the pipes are seriously corroded. Data utilized in the analyses are those related to soil property, i.e., soil resistivity, pH, water content, and chloride ion. Secondly, corrosion factors that significantly affect pipe wall pitting (vertical) and spread (horizontal) on the pipe surface are identified with a view to quantifying a degree of the pipe corrosion. Finally, a most reliable model represented in the form of a multiple regression equation is developed for this purpose. From these analyses, it can be concluded that our proposed model is effective to predict the severity and rate of pipe corrosion utilizing selected factors that reflect the fuzzy soil environment.

determination of Optimum Pipe diameter Using Multi-Stage Iterative Method in Water Distribution system (다단계 반복기법을 이용한 관로시스템의 최적관경 결정)

  • Han, Geon-Yeon;Park, Jae-Hong
    • Journal of Korea Water Resources Association
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    • v.31 no.3
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    • pp.327-335
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    • 1998
  • The distribution network is an essential part of all water supply systems. The cost of this portion of any sizable water supply system may amount to most of the entire cost of the project. This study tried to reduce the cost of the distribution system through optimization in system design. To determine pipe diameter considered in water distribution system design, a iterative procedure linked the flow analysis model and optimization model was used. Linear theory was introduced to analyze flowrate and revised-simplex method based on linear programming is used to optimize pipe diameter. This model was applied to wter distribution system with 22 and 35 pipes, and rapidly determine optimized commercial pipe diameters. Keywords : water distribution system, revised simplex method, optimum pipe diameters.

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Crack detection method for step-changed non-uniform beams using natural frequencies

  • Lee, Jong-Won
    • Smart Structures and Systems
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    • v.30 no.2
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    • pp.173-181
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    • 2022
  • The current paper presents a technique to detect crack in non-uniform cantilever-type pipe beams, that have step changes in the properties of their cross sections, restrained by a translational and rotational spring with a tip mass at the free end. An equation for estimating the natural frequencies for the non-uniform beams is derived using the boundary and continuity conditions, and an equivalent bending stiffness for cracked beam is applied to calculate the natural frequencies of the cracked beam. An experimental study for a step-changed non-uniform cantilever-type pipe beam restrained by bolts with a tip mass is carried out to verify the proposed method. The translational and rotational spring constants are updated using the neural network technique to the results of the experiment for intact case in order to establish a baseline model for the subsequent crack detection. Then, several numerical simulations for the specimen are carried out using the derived equation for estimating the natural frequencies of the cracked beam to construct a set of training patterns of a neural network. The crack locations and sizes are identified using the trained neural network for the 5 damage cases. It is found that the crack locations and sizes are reasonably well estimated from a practical point of view. And it is considered that the usefulness of the proposed method for structural health monitoring of the step-changed non-uniform cantilever-type pipe beam-like structures elastically restrained in the ground and have a tip mass at the free end could be verified.

A Multi-Objective Genetic Algorithm Approach to the Design of Reliable Water Distribution Networks

  • T.Devi Prasad;Park, Nam-Sik
    • Proceedings of the Korea Water Resources Association Conference
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    • 2002.05b
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    • pp.829-836
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    • 2002
  • The paper presents a multi-objective genetic algorithm approach to the design of a water distribution network. The objectives considered are minimization of network cost and maximization of a reliability measure. In this study, a new reliability measure, called network resilience, is introduced. This measure mimics a designer's desire of providing excess power at nodes and designing reliable loops with practicable pipe diameters. The proposed method produces a set of Pareto-optimal solutions in the search space of cost and network resilience. Genetic algorithms are observed to be poor in handling constraints. To handle constraints in a better way, a constraint handling technique that does not require a penalty coefficient and applicable to water distribution systems is presented. The present model is applied to two example problems, which were widely reported. Pipe failure analysis carried out on some of the solutions obtained revealed that the network resilience based approach gave better results in terms of network reliability.

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Development of a Failure Probability Model based on Operation Data of Thermal Piping Network in District Heating System (지역난방 열배관망 운영데이터 기반의 파손확률 모델 개발)

  • Kim, Hyoung Seok;Kim, Gye Beom;Kim, Lae Hyun
    • Korean Chemical Engineering Research
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    • v.55 no.3
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    • pp.322-331
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    • 2017
  • District heating was first introduced in Korea in 1985. As the service life of the underground thermal piping network has increased for more than 30 years, the maintenance of the underground thermal pipe has become an important issue. A variety of complex technologies are required for periodic inspection and operation management for the maintenance of the aged thermal piping network. Especially, it is required to develop a model that can be used for decision making in order to derive optimal maintenance and replacement point from the economic viewpoint in the field. In this study, the analysis was carried out based on the repair history and accident data at the operation of the thermal pipe network of five districts in the Korea District Heating Corporation. A failure probability model was developed by introducing statistical techniques of qualitative analysis and binomial logistic regression analysis. As a result of qualitative analysis of maintenance history and accident data, the most important cause of pipeline damage was construction erosion, corrosion of pipe and bad material accounted for about 82%. In the statistical model analysis, by setting the separation point of the classification to 0.25, the accuracy of the thermal pipe breakage and non-breakage classification improved to 73.5%. In order to establish the failure probability model, the fitness of the model was verified through the Hosmer and Lemeshow test, the independent test of the independent variables, and the Chi-Square test of the model. According to the results of analysis of the risk of thermal pipe network damage, the highest probability of failure was analyzed as the thermal pipeline constructed by the F construction company in the reducer pipe of less than 250mm, which is more than 10 years on the Seoul area motorway in winter. The results of this study can be used to prioritize maintenance, preventive inspection, and replacement of thermal piping systems. In addition, it will be possible to reduce the frequency of thermal pipeline damage and to use it more aggressively to manage thermal piping network by establishing and coping with accident prevention plan in advance such as inspection and maintenance.

Study on the applicability of the principal component analysis for detecting leaks in water pipe networks (상수관망의 누수감지를 위한 주성분 분석의 적용 가능성에 대한 연구)

  • Kim, Kimin;Park, Suwan
    • Journal of Korean Society of Water and Wastewater
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    • v.33 no.2
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    • pp.159-167
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    • 2019
  • In this paper the potential of the principal component analysis(PCA) technique for the application of detecting leaks in water pipe networks was evaluated. For this purpose the PCA was conducted to evaluate the relevance of the calculated outliers of a PCA model utilizing the recorded pipe flows and the recorded pipe leak incidents of a case study water distribution system. The PCA technique was enhanced by applying the computational algorithms developed in this study which were designed to extract a partial set of flow data from the original 24 hour flow data so that the effective outlier detection rate was maximized. The relevance of the calculated outliers of a PCA model and the recorded pipe leak incidents was analyzed. The developed algorithm may be applied in determining further leak detection field work for water distribution blocks that have more than 70% of the effective outlier detection rate. However, the analysis suggested that further development on the algorithm is needed to enhance the applicability of the PCA in detecting leaks by considering series of leak reports happening in a relatively short period.

Detecting and predicting the crude oil type inside composite pipes using ECS and ANN

  • Altabey, Wael A.
    • 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.

The development of a practical pipe auto-routing system in a shipbuilding CAD environment using network optimization

  • Kim, Shin-Hyung;Ruy, Won-Sun;Jang, Beom Seon
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.5 no.3
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    • pp.468-477
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    • 2013
  • An automatic pipe routing system is proposed and implemented. Generally, the pipe routing design as a part of the shipbuilding process requires a considerable number of man hours due to the complexity which comes from physical and operational constraints and the crucial influence on outfitting construction productivity. Therefore, the automation of pipe routing design operations and processes has always been one of the most important goals for improvements in shipbuilding design. The proposed system is applied to a pipe routing design in the engine room space of a commercial ship. The effectiveness of this system is verified as a reasonable form of support for pipe routing design jobs. The automatic routing result of this system can serve as a good basis model in the initial stages of pipe routing design, allowing the designer to reduce their design lead time significantly. As a result, the design productivity overall can be improved with this automatic pipe routing system.

Preliminary design and assessment of a heat pipe residual heat removal system for the reactor driven subcritical facility

  • Zhang, Wenwen;Sun, Kaichao;Wang, Chenglong;Zhang, Dalin;Tian, Wenxi;Qiu, Suizheng;Su, G.H.
    • Nuclear Engineering and Technology
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    • v.53 no.12
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    • pp.3879-3891
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    • 2021
  • A heat pipe residual heat removal system is proposed to be incorporated into the reactor driven subcritical (RDS) facility, which has been proposed by MIT Nuclear Reactor Laboratory for testing and demonstrating the Fluoride-salt-cooled High-temperature Reactor (FHR). It aims to reduce the risk of the system operation after the shutdown of the facility. One of the main components of the system is an air-cooled heat pipe heat exchanger. The alkali-metal high-temperature heat pipe was designed to meet the operation temperature and residual heat removal requirement of the facility. The heat pipe model developed in the previous work was adopted to simulate the designed heat pipe and assess the heat transport capability. 3D numerical simulation of the subcritical facility active zone was performed by the commercial CFD software STAR CCM + to investigate the operation characteristics of this proposed system. The thermal resistance network of the heat pipe was built and incorporated into the CFD model. The nominal condition, partial loss of air flow accident and partial heat pipe failure accident were simulated and analyzed. The results show that the residual heat removal system can provide sufficient cooling of the subcritical facility with a remarkable safety margin. The heat pipe can work under the recommended operation temperature range and the heat flux is below all thermal limits. The facility peak temperature is also lower than the safety limits.