Inverse Gaussian process-based corrosion growth modeling and its application in the reliability analysis for energy pipelines |
| |
Authors: | Hao QIN Shenwei ZHANG Wenxing ZHOU |
| |
Affiliation: | Department of Civil and Environmental Engineering, Western University, London N6A 5B9, Canada |
| |
Abstract: | This paper describes an inverse Gaussian process-based model to characterize the growth of metal-loss corrosion defects on energy pipelines. The model parameters are evaluated using the Bayesian methodology by combining the inspection data obtained from multiple inspections with the prior distributions. The Markov Chain Monte Carlo (MCMC) simulation techniques are employed to numerically evaluate the posterior marginal distribution of each individual parameter. The measurement errors associated with the ILI tools are considered in the Bayesian inference. The application of the growth model is illustrated using an example involving real inspection data collected from an in-service pipeline in Alberta, Canada. The results indicate that the model in general can predict the growth of corrosion defects reasonably well. Parametric analyses associated with the growth model as well as reliability assessment of the pipeline based on the growth model are also included in the example. The proposed model can be used to facilitate the development and application of reliability-based pipeline corrosion management. |
| |
Keywords: | pipeline metal-loss corrosion inverse Gaussian process measurement error hierarchical Bayesian Markov Chain Monte Carlo (MCMC) |
|
| 点击此处可从《》浏览原始摘要信息 |
|
点击此处可从《》下载全文 |