• 한국수자원학회논문집
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• 제39권2호
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• pp.89-98
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• 2006

기존의 상수관 파괴로 인한 피해 영역의 산정에서는 파괴된 관만을 피해영역으로 고려하였으나 이는 파괴된 관만이 차폐되었을 경우에만 정확하다 할 수 있다. 차폐에 이용되는 밸브의 배치에 따라 추가로 더 많은 관들이 파괴된 관과 함께 차폐가 될 수 있으며 Walski에 의하여 제안된 segment 개념으로 이러한 추가적인 관의 차폐를 고려할 수 있는 방법이 Jun에 의해서 개발되었다. 그러나, segment 개념으로 찾아질 수 있는 피해영역보다 더 많은 부분이 관 파괴의 영향을 받을 수 있으며, 이는 관들의 연결형상에 의한 차폐와 용수 수요지점에서 적정한 압력수두를 확보하지 못하여 발생하는 추가적인 피해에 기인한다 본 연구에서는 밸브의 위치에 따른 추가적인 피해영역과 함께 관들의 연결형상 그리고 압력수두에 따른 피해를 순차적으로 고려할 수 있는 방법을 제안하여 제안된 방법을 실제 상수관망에 적용하여 적용성을 검토한다 실제 상수관망에 적용한 결과 한 개의 상수관 파괴에 의한 피해 영역이 밸브위치와 용수노선의 설계에 따라 많은 지역에 피해를 발생시킬 수 있음을 보여 주고 있다. 따라서 본 연구에서 제안된 방법을 적용하여 산정된 상수관 파괴에 따른 피해영역이 현실을 정확히 반영함을 알 수 있었다.

• 한국유체기계학회 논문집
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• 제13권3호
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• pp.54-58
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• 2010

The pneumatic waste collection system, which is a complete solution for solving the waste collection problems, are constructed in many countries all over the world. However, research data for piping network design are insufficient. In this paper the pressure losses of the straight and curved pipes, pipe junctions are obtained using the numerical method in order to investigate the optimal pipe network design for the waste collection system. As an experimental result, the length of 1.8 meter is the reasonable for the radius of curvature of a curved pipe and the angle of 30 degree is suitable for confluent pipe.

• 한국환경과학회지
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• 제31권1호
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• pp.33-42
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• 2022

The objective of this study is to determine the appropriate size of the inlet pipe diameter and thereby conduct hydraulic analysis for the Korean water distribution network. To this end, the data tables for equivalent pipe diameters and outflow rates presently employed in Korea were adopted. By incorporating the table of equivalent pipe diameters, it was found that the size of the inlet pipe diameter was overestimated, which can cause shortage of water pressure and malfunctioning or insufficiency of outflow rate in the corresponding adjacent region. However, by conducting hydraulic analysis based on the table of outflow rates, relatively reasonable flow rates were observed. Furthermore, by comparing the real demand-driven analysis (RDDA) approach and demand-driven analysis (DDA) approach toward managing the huge water demand, it was observed that DDA could not effectively respond to real hourly usage conditions, whereas RDDA (which reflects the hourly effects of inlet pipe diameter and storage tanks) demonstrated results similar to that of real water supply.

• 한국농공학회지
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• 제43권4호
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• pp.69-78
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• 2001

In this study optimal analysis of pipe network was performed using linear and non linear analysis method for complex real pipe network system of Mungyeong water purification field system which consists of 70 nodes and 86 elements. From the examination result of total flow which is distributed to each pipe, it is found that KYPIPE2 Model supplies less amount than NLAM. It is known that dynamic water level and pressure head of KYPIPE2 Model and NLAM are nearly in accordance with each other from each method of the pipe network analyses, and appeared that both methods of analysis shows high reliable result since the distribution of dynamic water level for every node is the short range of EL. 205.0m~EL. 210.0m besides the pressed dynamic water level. The analysis results of pressure in the methods of pipe network analysis for KYPIPE2 Model and NLAM are similar and it is satisfactory result that the pressure distributions of the tab water design criterion of 5.0kgf/cm$^2$ besides the small part of highland.

• 상하수도학회지
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• 제16권6호
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• pp.686-699
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• 2002

The purpose of this study is to estimate deterioration factors and weighting factors in pipe network which each local self-governments takes rehabilitation and replacement work present time. Deterioration factors in pipe network are able to effected of specific province or location related with water supply. Most of water supply pipes are laid under the ground, it is hard to quantify deterioration degree of water system. Moreover, the timing and economic limitation and insufficient information on the spot survey gives a difficulty to look over how old water supply system is. Accordingly, this study collects and analyses five data as the laying environment, visual analysis, analysis of soil contents, analysis of pipe material, and questionary survey data in water pipe of A city. The deterioration factor estimates 14 factors with excavation and experimental analysis and 9 factors without excavation and experimental analysis. Also, the weighting factors are estimated by using the multiple linear regressions and the linear programming. The estimated deterioration factor and weighting results are compared the analysis result of visual, pipe material, and soil contents with the Probabilistic Neural Network Model. Consequently, the model results of estimated 9 factors in this study and 14 factors show the 1-2% difference. The result show that the proposed model could be used to decide the deterioration condition of pipe line with real excavation and experimental analysis.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2005년도 하계학술발표대회
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• pp.119-119
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• 2005

• 한국지반환경공학회 논문집
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• 제14권5호
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• pp.15-22
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• 2013

해저관로는 중요한 해안구조물의 하나로 연안 및 해양개발을 위해 폭넓게 사용되고 있다. 해저관로는 해저지반의 상태에 따라 파와 흐름으로 인해 주변에 세굴이 발생한다. 이로 인해 관이 뜨거나 가라앉는 경우가 발생하여 관의 내구성에 악영향을 미친다. 최근에는 해양환경에서 구조물과 여러 요인들의 복잡한 상호작용에 의한 세굴에 대해 많은 연구들이 이루어졌지만, 아직까지 세굴을 정확히 예측하는 것은 어렵다. 본 연구에서는 신경망 기법으로 관로의 세굴심 자료를 분석하여 세굴심을 예측하였다. 학습을 위해 역전파 알고리즘을 사용하였다. 신경망 모델의 학습과 검증에 총 58개의 모형실험 자료들이 사용되었다. 또한 동일한 데이터에 대해 회귀분석 기법을 통한 예측과 비교 분석하여 세굴심 예측을 위한 신경망 기법의 적용성을 검토하였다.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2003년도 학술발표논문집
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• pp.251-254
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• 2003

For improving the flow capacity of pipeline system the hydraulic inspection method was developed conducting on-site with survey of pipeline facility such as diversion work, air vent, etc. and pipe network analysis. The pipe network analysis method determine pipe diameter with trial and error. The validity of the hydraulic inspection method proved adapting on S-district pipeline system.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2007년도 추계학술대회 논문집
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• pp.227-228
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• 2007

• Nuclear Engineering and Technology
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• 제53권12호
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• pp.4060-4066
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• 2021

Flow-accelerated corrosion (FAC) of carbon steel piping is a significant problem in nuclear power plants. The basic process of FAC is currently understood relatively well; however, the accuracy of prediction models of the wall-thinning rate under an FAC environment is not reliable. Herein, we propose a methodology to construct pipe wall-thinning rate prediction models using artificial neural networks and a convolutional neural network, which is confined to a straight pipe without geometric changes. Furthermore, a methodology to generate training data is proposed to efficiently train the neural network for the development of a machine learning-based FAC prediction model. Consequently, it is concluded that machine learning can be used to construct pipe wall thinning rate prediction models and optimize the number of training datasets for training the machine learning algorithm. The proposed methodology can be applied to efficiently generate a large dataset from an FAC test to develop a wall thinning rate prediction model for a real situation.