Exploration of Data Interpretation Methods and Machine Learning–Based Failure Prediction Models for Plastic Gas Distribution Pipelines

Abstract

AbstractGas pipelines are a vital part of North America’s energy infrastructure, and analyzing reported incidents is essential for assessing their reliability. Previous studies lack comprehensive data interpretation of contributing factors in pipeline ...Practical ApplicationsThis study provides a data-driven tool for utility owners, pipeline engineers, and asset managers to better understand, assess, and predict failure trends in plastic gas distribution pipelines. By analyzing real-world failure ...