Crack evaluation in a pipeline using classical equations with Bayesian network and detection probability assessment using Gaussian Monte-Carlo simulation
Proceedings Publication Date
Santosh Kumar
Santosh Kumar, Deepak Agarwal, Saumitra Gupta, Atul Parmar
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Liquid pipelines are known to have higher pressure cycling during their operations. The higher pressure cycling increases the chances of fatigue-related failures in pipelines. The failures could be related to different threats where some are more prevalent such as Seam failures, stress corrosion cracks, corrosion fatigue, etc. The paper discusses the seam cracks and their assessments using API 579.

It is prudent to note that the material properties and test procedures are usually evaluated on the minimum boundary lines of the specifications. The paper however evaluates the entire test conditions spectrum and material property spectrum. The complete procedure is of initial crack size estimation, crack growth, evaluation, and detection is bound by separate layers of a complete framework based on a Bayesian model.

The complete process includes initial crack size estimation based on the hydro-test procedure and all over the spectrum of property distributed for a particular pipe based on its material testing. As a second step, the crack is grown on the complete spectrum of pipeline pressure cycling and other material properties over the span of evaluation.

At every stage, the grown cracks were studied for their behavior, distribution, and acceptance criteria. At the end of the simulation, the final failure frequencies were estimated based on the expected pressure cycling. A simulated inline inspection was done to gather the information for estimation of the probability of detection of these cracks. The detection of cracks during a run for a specific crack assessment tool was estimated based on its performance. A Gaussian distribution function was created for estimation of detection capability and the Monte-Carlo method was adopted for final estimation of crack-related failure at a given time in comparison to whether the ILI tool has been used or not and what type of ILI tool has been used.

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