Data-driven Methods to Predict the Burst Strength of Corroded Line Pipelines Subjected to Internal Pressure

Engineering

• Internal Pressure 100%
• Corroded Pipeline 100%
• Corrosion Defect 100%
• Finite Element Analysis 100%
• Support Vector Machine 100%
• Machine Learning Algorithm 50%
• Surrogate Model 50%
• Artificial Neural Network Model 50%
• Limited Application 50%
• Burst Pressure 50%
• Transfer Learning 50%
• Artificial Neural Network 50%

Chemical Engineering

• Support Vector Machine 100%
• Neural Network 100%
• Learning System 50%

Material Science

• Corrosion 100%
• Finite Element Method 66%
• High Pressure Pipeline 33%