Probabilistic assessment of complex corrosion in pipelines considering River-Bottom Profile information

Abstract

One of the important causes of failure and incidents in pipelines is corrosion. Due to the severe consequences and impact in several social, economic, and environmental areas, pipelines must be regularly inspected. The possibilities for pipeline assessment are standard equations and numerical simulations. While the first is simple and fast, it tends to be conservative and the second is expensive. The finite element method (FEM) has been successfully used to predict the failure pressure of pipelines under different conditions. Commonly assessment methods overlook the uncertainties for failure predictions, often relying on safety factors. However, it is imperative to consider uncertainties to ascertain the reliability and risk of corroded pipes. While the reliability analysis of pipelines with idealized defects has been extensively explored in the literature, studies considering complex corrosion profiles, are still demanding. This paper addresses this gap considering the traditional Monte Carlo (MC) and first-order reliability (FORM) methods. The assessment is based on the Effective Area Method (EAM) within the failure function. As well know, MC can be expensive due to the high number of function evaluations. To mitigate this, FORM is employed as it requires fewer function evaluations. However, function gradients are required as it relies on an iterative optimization algorithm. Particularly challenges arise when computing the gradient using EAM for burst pressure estimation. The EAM is an iterative procedure, and small perturbations can yield incorrect sensitivity values, causing problems for FORM convergence. To address this, we propose a novel procedure for efficiently and less conservatively obtaining the gradients required by FORM using EAM as a failure function. The modified FORM method achieved convergence within 15 iterations for all test cases. This alternative approach offers a faster, more precise and less conservative method for Level-2 probabilistic failure analysis of complex-shaped corrosion defects compared to traditional Level-1 methods.