腐蚀
管道运输
石油工程
碳钢
预测建模
潜艇
海底管道
材料科学
环境科学
工程类
冶金
岩土工程
海洋工程
计算机科学
环境工程
机器学习
作者
Junguo Cui,Yuyin Wu,Zhongqi Lu,Wensheng Xiao
出处
期刊:Applied sciences
[Multidisciplinary Digital Publishing Institute]
日期:2023-11-27
卷期号:13 (23): 12713-12713
被引量:10
摘要
To predict the corrosion failure of carbon steel oil and gas pipelines more accurately, a new corrosion failure prediction model for submarine oil and gas transport pipelines was constructed. A corrosion failure prediction management system was also developed based on the constructed model. To construct the model, corrosion experiments were carried out to analyze the influences of temperature, partial pressure of CO2, pH value, and flow rate acting on the corrosion rate. Based on the analysis results and the corrosion experiment data, a new corrosion failure prediction model containing the time and flow rate for oil and gas pipelines was constructed. The model is based on the existing corrosion prediction model and has a determination coefficient, R2, of 0.9573, which indicates good prediction accuracy. A machine learning prediction model was also used to predict, and the prediction results are compared with that of the proposed model, which further verifies the accuracy and feasibility of the proposed model. A corrosion failure prediction management system for carbon steel oil and gas pipelines was developed based on the constructed model, which makes corrosion failure prediction more convenient and faster and provides a reference for the accurate prediction and efficient control of oil and gas pipeline corrosion failure.
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