• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.651-656
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• 2014

Corrosion has a significant influence upon the reliability assessment and the maintenance planning of gas pipeline. Corrosion defects occurred on the underground pipeline can be obtained by conducting periodic in-line inspection (ILI). However, little study has been done for practical use of ILI data. This paper deals with remaining lifetime prediction of the gas pipeline in the presence of corrosion defects. Because a pipeline parameter includes uncertainty in its operation, a probabilistic approach is adopted in this paper. A pipeline fails when its operating pressure is larger than the pipe failure pressure. In order to estimate the failure probability, this paper uses First Order Reliability Method (FORM) which is popular in the field of structural engineering. A well-known Battelle code is chosen as the computational model for the pipe failure pressure. This paper develops a Matlab GUI for illustrating failure probability predictions Our result indicates that clustering of corrosion defects is helpful for improving a prediction accuracy and preventing an unnecessary maintenance.

• Ocean Systems Engineering
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• v.12 no.3
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• pp.267-284
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• 2022

A subsea pipeline designed across active shipping lane prones to failure against external interferences such as anchorage activities, hence risk assessment is essential. It requires quantifying the geometric probability derived from ship traffic distribution based on Automatic Identification System (AIS) data. The actual probability density function from historical vessel traffic data is ideal, as for rapid assessment, conceptual study, when the AIS data is scarce or when the local vessels traffic are not utilised with AIS. Recommended practices suggest the probability distribution is assumed as a single peak Gaussian. This study compares several fitted Gaussian distributions and Monte Carlo simulation based on actual ship traffic data in main ship direction in an active shipping lane across a subsea pipeline. The results shows that a Gaussian distribution with five peaks is required to represent the ship traffic data, providing an error of 0.23%, while a single peak Gaussian distribution and the Monte Carlo simulation with one hundred million realisation provide an error of 1.32% and 0.79% respectively. Thus, it can be concluded that the multi-peak Gaussian distribution can represent the actual ship traffic distribution in the main direction, but it is less representative for ship traffic distribution in other direction. The geometric probability is utilised in a quantitative risk assessment (QRA) for subsea pipeline against vessel anchor dropping and dragging and vessel sinking.

• Structural Engineering and Mechanics
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• v.47 no.2
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• pp.167-183
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• 2013

Methods for estimating structural reliability using probability ideas are well established. When the residual ultimate strength of a buried pipeline is exceeded the limit, breakage becomes imminent and the overall reliability of the pipe distribution network is reduced. This paper is concerned with estimating structural failure of underground flexible pipes due to corrosion induced excessive deflection, buckling, wall thrust and bending stress subject to externally applied loading. With changes of pipe wall thickness due to corrosion, the moment of inertia and the cross-sectional area of pipe wall are directly changed with time. Consequently, the chance of survival or the reliability of the pipe material is decreased over time. One numerical example has been presented for a buried steel pipe to predict the probability of failure using Hasofer-Lind and Rackwitz-Fiessler algorithm and Monte Carlo simulation. Then the parametric study and sensitivity analysis have been conducted on the reliability of pipeline with different influencing factors, e.g. pipe thickness, diameter, backfill height etc.

• Journal of the Korean Institute of Gas
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• v.24 no.4
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• pp.10-17
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• 2020

The structural reliability assessment can be used to improve the reliability in the asset integrity management of the pipeline by using a geometric variation, mechanical characteristics, load change and operating condition as evaluation factors. When evaluating structural reliability, the failure probability of the natural gas pipe is evaluated by the relationship of the resistance of the pipe material to external loads. The failure probability of the natural gas pipe due to the combined stresses such as the internal pressure, thermal stress and bending stress was evaluated by using COMREL program. When evaluating the failure probability of the natural gas pipe, a buried depth of 1.5 to 30 m, a wheel load of 2.5 to 20 ton, a temperature difference of 45℃, an operating pressure of 6.86MPa, and a soil density of 1.8 kN/㎥ were used. The failure probabilities of the natural gas pipe were evaluated by the Von-Mises stress criterion as the maximum allowable stress criterion under the combined stresses.

• Journal of the Korean Institute of Gas
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• v.7 no.2 s.19
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• pp.1-6
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• 2003

In this work, procedure evaluating failure modes such as pipe rupture, large scale leak, and small scale leak was suggested using equations to assess remaining strength by corrosion failure. Additionally, the method to predict probability of failure was suggested according to the aforementioned failure modes, and by combining data on corrosion rate, probability of long-term failure can be induced. This work will be very useful in predicting lifetime or exchanging period of pipeline.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.343-350
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• 2016

Remaining lifetime prediction of the underground gas pipeline plays a key role in maintenance planning and public safety. One of main causes in the pipeline failure is metal corrosion. This paper deals with estimating the pipeline reliability in the presence of corrosion defects. Because a pipeline has uncertainty and variability in its operation, probabilistic approximation approaches such as first order second moment (FOSM), first order reliability method (FORM), second order reliability method (SORM), and Monte Carlo simulation (MCS) are widely employed for pipeline reliability predictions. This paper presents a fuzzy inference based reliability method (FIRM). Compared with existing methods, a distinction of our method is to incorporate a fuzzy inference into quantifying degrees of variability in corrosion defects. As metal corrosion depends on the service environment, this feature makes it easier to obtain practical predictions. Numerical experiments are conducted by using a field dataset. The result indicates that the proposed method works well and, in particular, it provides more advisory estimations of the remaining lifetime of the gas pipeline.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.175-185
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• 2017

As the gas is manufactured, handled and used more often due to the continuous increase of gas, the related facility gets expanded and more complex causing small and big accident which causes economic loss including damage for humans and materials. The gas pipeline, the most common gas facility, has the biggest risk of accidents. Especially in the urban area and densely populated areas, the accident due to the high pressure pipeline may cause even more serious damages. To prevent the accident caused by the buried pipeline, it is required for the relevant authorities to evaluate the damage and risk of the whole pipeline system effectively. A risk is usually defined as a possibility or probability of an undesired event happening, and there is always a risk even when the probability of failure is set low once the pipeline is installed or under operation. It is reported that the accident caused by the failure of the pipeline rarely happens, however, it is important to minimize the rate of accidents by analyzing the reason of failure as it could cause a huge damage of humans and property. Therefore, the paper rated the risk of pipelines with quantitative numbers using the qualitative risk analysis method of the Scoring Model. It is assumed that the result could be effectively used for practical maintenance and management of pipelines securing the safety of the pipes.

• 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.

• Journal of the Korean Institute of Gas
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• v.19 no.5
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• pp.81-86
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• 2015

A deterministic stress-based methodology has traditionally been applied in pipeline design. Meanwhile, reliability based design and assessment (RBDA) methodology has been extensively applied in offshore or nuclear structures. Lately, the release of ISO standard on reliability based limit state methods for pipelines ISO16708 indicates that the RBDA methodology is one of the newest directions of natural gas pipeline design method. This paper presents a case study of the RBDA procedure for predicting the time-dependent failure probability of pipelines with corrosion defects, where separable Monte Carlo (SMC) method is applied in the reliability estimation for corroded pipeline instead of traditional, crude Monte Carlo(CMC) Method. The result shows the SMC method take advantage of improving accuracy in reliability calculation.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.234-239
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• 2004

A study on the probabilistic methodology for the estimation of the remaining life of Pressurized pipelines containing active corrosion defects is presented. This reliability assessment is earned out using extream value distribution of the corroded defects instead of already published failure perssure moded like NG18 or ASME B31G. The failure probability of pipelines depends on the number of corroded defects. and it could be calculated directly as the area exceeded a defined L V(Limited Value of corrosion depth). The remaining life of pressurized pipelines can also be estimated by the PDF of extream value distribution as calculating the exceeded area with a defined failure probability.