• Proceedings of the Korean Magnestics Society Conference
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• 2001.10a
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• pp.122-123
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• 2001

• 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.

• Corrosion Science and Technology
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• v.16 no.5
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• pp.235-240
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• 2017

Regional cathodic protection has significant impact on pipeline integrity management. After risk analyses of a newly built gas distribution station constructed in an area with large dwelling density, risk score was high because of potential threat caused by galvanic corrosion. Except reinforced steel in concrete, there are four kinds of metal buried under earth: carbon steel, galvanized flat steel, zinc rod and graphite module. To protect buried pipeline from external corrosion, design and construction of regional cathodic protection was proposed. Current density was measured with potential using potential dynamic test and boundary element method (BEM) was used to calculate current requirement and optimize best anode placement during design. From our calculation on the potential, optimized conditions for this area were that an applied current was 3A and anode was placed at 40 meters deep from the soil surface. It results in potential range between $-1.128V_{CSE}$ and $-0.863V_{CSE}$, meeting the $-0.85V_{CSE}$ criterion and the $-1.2V_{CSE}$ criterion that no potential was more negative than $-1.2V_{CSE}$ to cause hydrogen evolution at defects in coating of the pipeline.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.1
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• pp.61-69
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• 2001

EFP(Fitness For Purpose) type defect assessment methodologies based on ECA(Engineering Critical Analysis) have been established and are in use for the structural integrity evaluation of gas pipelines. ECA usually includes the fracture mechanics analysis, and it is assumed that the J-integral uniquely characterizes the crack-tip stress-strain field. However, it has been proven that the J-integral alone can not be sufficient to characterize the crack-tip field under low levels of constraint with a single parameter. Since pipeline structures are made of ductile material, locally loaded in tension, cracks may experience low level of constraint, and therefore, J-dominance will be lost. For this reason, the level of constraint must be quantified to establish a precise assessment procedure for pipeline defects. The objective of this paper is to investigate the fracture behavior of a crack in gas pipeline(KS D 3507) by quantifying the level of constraint. For this purpose, tensile tests and CTOD tests were performed at room temperature(24$\^{C}$) and low temperature(-40$\^{C}$) to obtain the material properties. J-Q analyses were performed for SENB and SENT specimens based on 2-D finite element analyses, in order to investigate the in-plane constraint effects on pipeline defects. For precise assessment of cracks, especially shallow cracks, in KS D 3507 pipeline, constraint effect must be considered.

• Journal of the Korean Institute of Gas
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• v.6 no.1 s.17
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• pp.10-16
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• 2002

This paper introduces developed prototype intelligent pig which detects corrosion on pipeline by using Magnetic Flux Leakage technology. The 8 inch developed MFL(Magnetic Flux Leakage) pig is composed of 5 yokes which magnetize pipeline wall and 45 Hall sensors which detect MFL signal. The designed MFL modules are analyzed by using magnetic circuit method in order to confirm whether pipeline wall is fully saturated. A variety of artificial defects are manufactured on 8 inch diameter steel pipeline in order to acquire MFL signals. So leakage flux of the axial, radial and circumferential component was acquired as defects. The results of this paper show that design technique for 8 inch MFL pig can be applied to large diameter MFL pig and 0.5mm defect depth can be detected.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.11 s.170
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• pp.2096-2101
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• 1999

This paper presents the effect of shape of external corrosion in pipeline on failure prediction by using numerical simulation. The numerical study for the pipeline failure analysis is based on the FEM(Finite Element Method) with an elastic-plastic and large-deformation analysis. The predicted failure stress assessed for the simulated corrosion defects having different corroded shapes along the pipeline axis are compared with those by methods specified in ANSl/ASME B31G code and a modified B31G code.

• Proceedings of the Korean Magnestics Society Conference
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• 2008.12a
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• pp.39.1-39.1
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• 2008

• Journal of the Korean Magnetics Society
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• v.15 no.6
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• pp.325-331
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• 2005

The magnetic Hut leakage (MFL) type nondestructive testing (NDT) method is widely used to detect corrosion and defects, mechanical deformation of the underground gas pipelines. The object pipeline is magnetically saturated by the magnetic system with permanent magnet and yokes. Because of the strong magnetic field enough to saturate the pipe, there could be distortion of the sensing signals because of the magnetization of the pipeline itself, To detect the defects precisely, the sensing signals are need to be compensated to eliminate the distortions coming from the media hysteresis. In this paper, the magnetizations of the pipeline in MFL type NDT are analyzed by Preisach model and 3D FEM. The distortions of the sensing signals are analyzed.

• Journal of Magnetics
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• v.16 no.1
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• pp.36-41
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• 2011

If gas is leaking out of gas pipelines, it could cause a huge explosion. Accordingly, it is important to ensure the integrity of gas pipelines. Traditionally, over the years, gas-operating companies have used the ILI system, which is based on axial magnetic flux leakage (MFL), to inspect the gas pipelines. Relatively, there is a low probability of detection (POD) for the axial defects with the axial MFL-based ILI. To prevent the buried pipeline from corrosion, it requires a protective coating. In addition to the potential damage to the coating by environmental factors and external forces, there could be defects on the damaged coating area. Thus, it is essential that nondestructive evaluation methods for detecting axial defects (axial cracks, axial groove) and damaged coating be developed. In this study, an electromagnetic acoustic transducer (EMAT) sensor was designed and fabricated for detecting axial defects and coating disbondment. In order to validate the performances of the developed EMAT sensor, experiments were performed with specimens from axial cracks, axial grooves, and coating disbondment. The experimental results showed that the developed EMAT sensor could detect not only the axial cracks (minimum 5% depth of wall thickness) and axial grooves (minimum 10% depth of wall thickness), but also the coating disbondment.

• Structural Monitoring and Maintenance
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• v.3 no.3
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• pp.297-314
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• 2016

As the study of internal corrosion of pipeline need a large number of experiments as well as long time, so there is a need for new computational technique to expand the spectrum of the results and to save time. The present work represents a new non-destructive evaluation (NDE) technique for detecting the internal corrosion inside pipeline by evaluating the dielectric properties of steel pipe at room temperature by using electrical capacitance sensor (ECS), then predict the effect of pipeline environment temperature (${\theta}$) on the corrosion rates by designing an efficient artificial neural network (ANN) architecture. ECS consists of number of electrodes mounted on the outer surface of pipeline, the sensor shape, electrode configuration, and the number of electrodes that comprise three key elements of two dimensional capacitance sensors are illustrated. The variation in the dielectric signatures was employed to design electrical capacitance sensor (ECS) with high sensitivity to detect such defects. The rules of 24-electrode sensor parameters such as capacitance, capacitance change, and change rate of capacitance are discussed by ANSYS and MATLAB, which are combined to simulate sensor characteristic. A feed-forward neural network (FFNN) structure are applied, trained and tested to predict the finite element (FE) results of corrosion rates under room temperature, and then used the trained FFNN to predict corrosion rates at different temperature using MATLAB neural network toolbox. The FE results are in excellent agreement with an FFNN results, thus validating the accuracy and reliability of the proposed technique and leads to better understanding of the corrosion mechanism under different pipeline environmental temperature.