• Corrosion Science and Technology
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• v.14 no.6
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• pp.325-330
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• 2015

Pipe wall-thinning by flow-accelerated corrosion (FAC) is a significant and costly damage of secondary system piping in nuclear power plants (NPPs). All NPPs have their management programs to ensure pipe integrity from wall-thinning. This study analyzed the pipe wall-thinning caused by changing the amine, which is used for adjusting the water chemistry in the secondary system of NPPs. The pH change was analyzed according to the addition of amine. Then, the wear rate calculated in two different amines was compared at the steam cycle in NPPs. As a result, increasing the pH at operating temperature (Hot pH) can reduce the rate of FAC damage significantly. Wall-thinning is affected by amine characteristics depending on temperature and quality of water.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.61-66
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• 2001

Fracture behaviors of pipes with local wall thinning is very important for the integrity of nuclear power plant. In pipes of energy plants, sometimes, the local wall thinning may result from severe drosion-corrosion damage. However, effect of local wall thinning on strength and fracture behaviors of piping system were not well studied. In this paper, the monotonic bending tests were performed of full-scale carbon steel pipes with local wall thinning. A monotonic bending load was applied to straight pipe specimens by four-point loading at ambient temperature without internal pressure. From the tests, fracture behaviors and fracture strength of locally thinned pipe were manifested systematically. The observed failure modes were divided into four types; ovalization, ovalization+cracking, local buckling and local buckling+cracking. Also, maximum load was successfully evaluated.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.622-628
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• 2003

The purpose of this study is to evaluate the effect of local wall thinning on the collapse of elbow subjected to internal pressure and bending moment. Thus, the nonlinear 3D finite element analyses were performed to obtained collapse moment of elbow containing various wall thinning defects under two loading; modes (closing and opening modes) and defect locations (intrados and extrados). From the results of analyses, the influence of wall thinning defect on the global moment-rotation behavior of elbow was discussed, and the dependance of collapse moment of elbow on wall thinning depth, length, and circumferential angle was investigated under different loading mode and defect location.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.27-28
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• 2006

This study performs to investigate deformation of wall thinning pipe and to find out the position of the internal thinning defect by shearography. Shearography is one of optical methods those have applied to nondestructive testing (NDT) and the strain/stress analysis. This technique has the merit of the directly measuring the first derivative of displacement, sensitivity of which can be adjusted by the handling of optical component in interferometer. In this paper, we tested carbon steel pipe locally wall thinned and loaded internal pressure and developed the nondestructive out-of-plane deformation analysis technique fur internal thinning defect of elbow by shearography. From the results, it was confirmed that this technique is proper to the practical application on the pipe line system with internal defect.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2008.04a
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• pp.321-324
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• 2008

Forest fire danger rate of thinning area was lower than that of non thinning area, because height rate of leewardside in burned stem of tree, damage rate of crown and mortality of tree in thinning area were 30.8%, 37% and 48.4% lower than that in non-thinning area, respectively. Intensity of forest fire varied depending upon topographical condition up slope, down slope, aspect, location as well as species, breast height diameter and forest tree density. Especially, a mountaintop area was burned down when forest fire was spread to up slope ridge of mountain.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.7 no.1
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• pp.27-34
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• 2011

The objective of this study is to classify the geometry of wall-thinning defect that causes a circumferential crack in the pipe elbows subjected to internal pressure. For this objective, first of all a criterion to determine the occurrence of circumferential cracking at wall-thinned area was developed based on finite element simulation for burst tests of pipe elbow specimens that showed axial and circumferential cracking at wall-thinned area. In addition, parametric finite element analysis including various wall-thinning geometries, locations, and pipe geometries was conducted and the wall-thinning geometries that initiate circumferential crack were determined by applying the criterion to the results of parametric analysis. It showed that the circumferential crack occurs at wall-thinning defect, which has a deep, wide, and short geometry. Also, it is indicated that the pipe elbows with larger radius to thickness ratio are more susceptible to circumferential cracking at wall-thinned area.

• Journal of the Korean Society of Safety
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• v.18 no.4
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• pp.28-34
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• 2003

In the present study, three-dimensional finite element analysis was performed to investigate the effects of internal wall thinning defect on the failure pressure of elbow in the piping system and to develop the failure pressure evaluation model. From the results of finite element analysis, the failure pressure was derived by employing local stress criteria, and the effects of thinning location, bend radius, and defect geometry on the failure pressure of internally wall thinned elbow were investigated. Also, based on these investigations and previous model developed to estimate the failure pressure of elbow with an external pitting defect, the failure pressure evaluation model to be applicable to the elbow containing an internal thinning defect was proposed and compared with the results of finite element analysis. The failure pressure calculated by the model agreed well with the results of finite element analysis.

• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.829-843
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• 2010

To test for the serial dependence in time series of counts data, Jung and Tremayne (2003) evaluated the size and power of several tests under the class of INARMA models based on binomial thinning operations for Poisson marginal distributions. The overdispersion phenomenon(i.e., a variance greater than the expectation) is common in the real world. Overdispersed count data can be modeled by using alternative thinning operations such as random coefficient thinning, iterated thinning, and quasi-binomial thinning. Such thinning operations can lead to time series models of counts with negative binomial or generalized Poisson marginal distributions. This paper examines whether the test statistics used by Jung and Tremayne (2003) on serial dependence in time series of counts data are affected by overdispersion.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.4
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• pp.402-409
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• 2004

The purpose of this study is to investigate the effect of local wall thinning on the collapse of elbow subjected to internal pressure and bending moment. Thus, the nonlinear three-dimensional finite element analyses were performed to obtain the collapse moment of elbow containing various wall thinning defects located at intrados and extrados under two loading modes (closing and opening modes) with internal pressure. From the results of analysis, the effect of wall thinning defect on the global moment-rotation behavior of elbow was discussed, and the dependence of collapse moment of elbow on wall thinning depth, length, and circumferential angle was investigated under different loading mode and defect location.

• Nuclear Engineering and Technology
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• v.53 no.12
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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.