Bayesian Modeling of External Corrosion in Underground Pipelines Based on the Integration of Markov Chain Monte Carlo Techniques and Clustered Inspection Data

Author:

Wang Hui1,Yajima Ayako1,Liang Robert Y.1,Castaneda Homero2

Affiliation:

1. Department of Civil Engineering; The University of Akron; Akron OH USA

2. Department of Chemical and Biomolecular Engineering; National Center for Research in Corrosion and Materials Performance; The University of Akron; Akron OH USA

Funder

SENER-CONACYT

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Graphics and Computer-Aided Design,Computer Science Applications,Civil and Structural Engineering

Cited by 53 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Spatial Statistical Analysis: A “Blind-Approach”;Corrosion and Reliability Assessment of Inspected Pipelines;2023-08-14

2. Introduction;Corrosion and Reliability Assessment of Inspected Pipelines;2023-08-14

3. Evolution of corrosion prediction models for oil and gas pipelines: From empirical-driven to data-driven;Engineering Failure Analysis;2023-04

4. Advances in corrosion growth modeling for oil and gas pipelines: A review;Process Safety and Environmental Protection;2023-03

5. Development of a distributed MR-IoT method for operations and maintenance of underground pipeline network;Tunnelling and Underground Space Technology;2023-03

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