Failure risk analysis of pipelines using data-driven machine learning algorithms

Author:

Mazumder Ram K.,Salman Abdullahi M.,Li Yue

Funder

NSF

CRISP

Publisher

Elsevier BV

Subject

Safety, Risk, Reliability and Quality,Building and Construction,Civil and Structural Engineering

Reference61 articles.

1. Prediction of remaining strength of corroded pressurised pipelines;Ahammed;Int J Press Vessels Pip,1997

2. An experimental investigation of the effect of defect shape and orientation on the burst pressure of pressurised pipes;Al-Owaisi;Eng Fail Anal,2018

3. Risk-based assessment of offshore crude oil pipelines and condition-monitoring systems;Aljaroudi;J Pipeline Eng,2016

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

5. Probability concepts in engineering planning and design: Emphasis on application to civil and environmental engineering;Ang,2007

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