Prediction of maximum pitting corrosion depth in oil and gas pipelines
Author:
Publisher
Elsevier BV
Subject
General Engineering,General Materials Science
Reference48 articles.
1. Hybrid intelligent method for fuzzy reliability analysis of corroded X100 steel pipelines;Bagheri;Eng. Comput.,2020
2. Artificial neural network models for predicting condition of offshore oil and gas pipelines;El-Abbasy;Autom. Constr.,2014
3. Condition prediction models for oil and gas pipelines using regression analysis;El-Abbasy;J. Constr. Eng. Manag.,2014
4. Reliability analysis of low, mid and high-grade strength corroded pipes based on plastic flow theory using adaptive nonlinear conjugate map;El Amine Ben Seghier;Eng. Fail. Anal.,2018
5. Reliability analysis of corroded pipelines: novel adaptive conjugate first order reliability method;Keshtegar;J. Loss Prev. Process Ind.,2019
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