Pipeline corrosion prediction and uncertainty analysis with an ensemble Bayesian neural network approach-Reference-Cited by-同舟云学术

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Pipeline corrosion prediction and uncertainty analysis with an ensemble Bayesian neural network approach

Published:2024-07 Issue: Volume:187 Page:483-494
ISSN:0957-5820
Container-title:Process Safety and Environmental Protection
language:en
Short-container-title:Process Safety and Environmental Protection

Author:

Cui Bingyan,Wang Hao

Funder

Pipeline and Hazardous Materials Safety Administration

Publisher

Elsevier BV

Reference54 articles.

1. Reliability estimation of pressurised pipelines subject to localised corrosion defects;Ahammed;Int. J. Press. Vessels Pip.,1996

2. Predictive deep learning for pitting corrosion modeling in buried transmission pipelines;Akhlaghi;Process Saf. Environ. Prot.,2023

3. Localized corrosion and mitigation approach of steel materials used in oil and gas pipelines – an overview;Alamri;Eng. Fail. Anal.,2020

4. Reliability assessments of corroded pipelines based on internal pressure – a review;Amaya-Gómez;Eng. Fail. Anal.,2019

5. External corrosion pitting depth prediction using Bayesian spectral analysis on bare oil and gas pipelines;Balekelayi;Int. J. Press. Vessels Pip.,2020

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