Stochastic Based Multi-Objective Optimization of Corroded Gas Transmission Pipelines Using Importance Sampling Technique and Genetic Algorithm

The purpose of this work is to perform a comprehensive comparison between different Failure Pressure Model (FPM)s in terms of probability. In order to simulate rate of internal corrosion, Poisson Wave Square Process (PSWP) is applied. Furthermore, as the most effective parameter on Burst Capacity(BC) of pipelines is internal pressure and there is no distinct relationship for expressing variation of it versus time, a stochastic process is used instead to predict maximum pressure of pipeline. For determining Probability of Failure (POF), Importance Sampling (IS) technique is applied to FPMs. Both Pipeline Diameter (PD) and Pipeline Thickness (PT) are considered as variables in optimization stage that is done using MATLAB Optimization Toolbox. The presented method is applied to a pipeline in Southern parts of Persian Gulf. For getting to as much accurate as possible result, mean and Coefficient of Variation (COV) of input parameters are adopted using In-Line Inspection (ILI) data of the pipeline. Finally, in order to present a better view on selecting different FPMs, a financial assessment is carried out.

کلیدواژه ها:

pipeline ، corrosion ، reliability ، GA ، BCR