Corrosion defects occurring in natural gas pipelines are common and annoying. The
residual strength prediction of corroded pipelines is usually carried out based on theoretical …

This paper aims to predict the failure pressure of corroded offshore pipelines, employing
different machine learning techniques. To this end, an efficient finite element based …

For the residual strength prediction of corroded pipelines, the existing standard has a small
application range, and the finite-element method has too many assumptions. This paper …

Corrosion is a common type of defect that causes failure of oil and gas pipelines. Pipelines
often bear the combined loadings of axial compression force, bending moment and internal …

Corrosion defects occur very often on the internal and external surfaces of pipelines, which
may result in a serious threat to the integrity of the pipelines. Numerous studies investigated …

This paper describes the development and application of artificial neural network (ANN) to
predict the failure pressure of single corrosion affected pipes subjected to internal pressure …

A fast calculation of the reliability is meaningful to the in-line inspection of corroding natural
gas pipelines. However, the traditional Monte Carlo simulation (MCS) method is time …

Machine learning tools are increasingly adopted in various industries because of their
excellent predictive capability, with high precision and high accuracy. In this work, analytical …

Understanding the corrosion risk of a pipeline is vital for maintaining health, safety and the
environment. This study implemented a data-driven machine learning approach that relied …

With the complexity of geological conditions and corrosive environments, the evaluation of
failure pressure for defective pipelines under external loads has gradually become an …