Failure Pressure Prediction of a Corroded Pipeline with Longitudinally Interacting Corrosion Defects Subjected to Combined Loadings Using FEM and ANN

Saravanan Karuppanan,Mark Ovinis,Michael Lo

doi:10.3390/jmse9030281

Saravanan Karuppanan, Mark Ovinis + Show 1 more

Open Access

https://doi.org/10.3390/jmse9030281

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Abstract

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 equations to predict the failure pressure of a corroded pipeline with longitudinally interacting corrosion defects subjected to combined loads of internal pressure and longitudinal compressive stress were derived, based on an artificial neural network (ANN) model trained with data obtained from the finite element method (FEM). The FEM was validated against full-scale burst tests and subsequently used to simulate the failure of a pipeline with various corrosion geometric parameters and loadings. The results from the finite element analysis (FEA) were also compared with the Det Norske Veritas (DNV-RP-F101) method. The ANN model was developed based on the training data from FEA and its performance was evaluated after the model was trained. Analytical equations to predict the failure pressure were derived based on the weights and biases of the trained neural network. The equations have a good correlation value, with an R2 of 0.9921, with the percentage error ranging from −9.39% to 4.63%, when compared with FEA results.

Highlights

Pipelines are the most economical means of transport between gas wells, storage facilities, refinery plants and power plants
This paper proposes the application of an artificial neural network (ANN) together with the finite element method (FEM) to formulate an equation to predict the failure pressure of a corroded pipeline with varying longitudinally interacting corrosion defect geometries, subjected to internal pressure and longitudinal compressive stress
The finite element analysis (FEA) for corroded API 5L X65 pipes with a single corrosion defect were designated with the prefix SDOFAT, while the FEAs for corroded pipes with longitudinally interacting corrosion defects were designated with the prefix LIDOFAT

Summary

Introduction

Pipelines are the most economical means of transport between gas wells, storage facilities, refinery plants and power plants. Corrosion is a significant cause of pipeline failure as it thins the pipe wall, weakening the structural integrity of the pipeline by reducing the load-carrying capacity of the pipeline due to stress concentration at the corrosion region [2]. Interacting defects are more detrimental towards the structural integrity of a pipeline than single defects, as they may interact with each other and reduce the failure capacity of the pipeline [3]. They need to be considered differently when assessing corroded pipelines. Defect spacing s equal or greater than the interaction limit will be treated as a single defect, due to the negligible interaction effect [5]

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