Pipeline Integrity Analysis through Data-Driven Approaches
Author:
Affiliation:
1. School of Construction Management Technology, Purdue Univ., West Lafayette, IN.
2. Dept. of Civil, Construction, and Environmental Engineering, North Dakota State Univ., Fargo, ND.
Publisher
American Society of Civil Engineers
Link
https://ascelibrary.org/doi/pdf/10.1061/9780784485262.004
Reference12 articles.
1. Tragedy of commons: Analysis of oil spillage, gas flaring and sustainable development of the Niger Delta of Nigeria;Akpomuvie O. B.;Journal of Sustainable Development,2011
2. Aldosari H. Elfouly R. and Ammar R. 2020. “Evaluation of Machine Learning-Based Regression Techniques for Prediction of Oil and Gas Pipelines Defect.” 2020 International Conference on Computational Science and Computational Intelligence (CSCI) Las Vegas NV 1452–1456.
3. ASME. 2021. Managing System Integrity of Gas Pipelines: ASME Code for Pressure Piping, B31: Supplement to ASME B31. 8. New York: The American Society of Mechanical Engineers.
4. Wireless Sensor Networks based Pipeline Vandalisation and Oil Spillage Monitoring and Detection: Main Benefits for Nigeria Oil and Gas Sectors;Henry N. F.;The SIJ Transactions on Computer Science Engineering & Its Applications (CSEA),2019
5. Quantitative risk assessment of a natural gas pipeline in an underground utility tunnel;Fang W.;Process Safety Progress,2019
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