Tensile Fracture Behavior of Corroded Pipelines: Part 2—Numerical Simulation Based on Monte Carlo Method

Feng Liu, Yuchao Yang, Feng Xi
2020 Advances in Materials Science and Engineering  
The experimental part in this companion paper revealed that the macroscopic mechanical performance of corroded pipes follows a decreasing trend with the increasing corrosion rate. Inspired by the surface topology by scanning electronic microscopy (SEM) and the scattered distribution of test data, a computational procedure based on the Monte Carlo simulation method was developed in this paper to understand the randomness of the crack propagation process and the performance degradation mechanism
more » ... f the corroded pipelines. A total of 2700 random samples, which contain three corrosion rates of 15%, 45%, and 70% with each corrosion rate having three variances of 0.02 mm, 0.06 mm, and 0.10 mm, were generated and then were mapped to the shell section of the FE model. In the application of the material model considering the damage, a series of "numerical" tensile experiments were carried out. The simulation analysis indicated that the corrosion rate and the standard variance of the thickness collaboratively dominated the mechanical performance of the corroded specimen. Under the same standard deviation, the wall corresponding to the higher corrosion rate is more likely to cause stress concentration in the weak position, which makes the pipe more prone to fail. Furthermore, under the same corrosion rate, the increase of the standard deviation will aggravate the unevenness of the wall thickness distribution, and then the lower tensile load will cause damage at weak locations and lead to randomness of the crack propagation path, thereby reducing the pipe's macroscopic strength and fracture strain. The analytical methods in this paper have the potential of being a useful tool for structural reliability assessments of aged pipelines and the full life cycle design of new pipeline networks.
doi:10.1155/2020/5708969 fatcat:spcpnr73bbeappjl6pytxnn6vm