Session: DA-12-01: Fracture

Paper Number: 80412

80412 - Reliability-Based Assessment of Cracked Pipelines Using Monte Carlo Simulation Technique With CorLAS™ 

Operating pipelines often experience leak or rupture that were caused by unstable crack growth resulting in the occurrence of failure. Fracture mechanics models are typically used to evaluate the failure probability of a pipeline due to the presence of crack or crack-like anomalies. To this end, an inelastic fracture mechanics model, known as CorLAS^TM model, has been developed and frequently used by pipeline operators. This paper first reviews the development of the CorLAS^TM model and derives the probabilistic characteristics, including mean and coefficient of variation (COV) associated with the CorLAS^TM model using the collected 94 full-scale burst test data from the literature. A comprehensive reliability assessment of cracked pipes based on the CorLAS^TM model is performed through the Monte Carlo Simulation (MCS) method. For each reported scenario, the probability of failure (POF) is calculated by using the Monte Carlo technique that considers all the important uncertainties associated with various parameters such as pipe geometry, material properties, and including the uncertainty due to the fracture model itself, namely, model error. Finally, a sensitivity study is conducted considering the input parameters including the pipe grade, pipe diameter, wall thickness, the ratio of crack length to depth, the ratio of crack depth to wall thickness, and the model error COV. As a result, the POFs are highly sensitive to the model error COV, i.e., the POFs increase significantly with the increase of the COV values, however, the effects of other input parameters on the POFs are insignificant.

Presenting Author: Xinfang Zhang University of Alberta

Presenting Author Biography: Hi everyone, My name is Xinfang (Sissi) Zhang, a 2nd year PhD student at the University of Alberta in Canada.

Authors:

Xinfang Zhang University of Alberta
Qian Zheng University of Alberta
Juliana Leung University of Alberta
Samer Adeeb University of Alberta