Abstract
Numerical methods such as finite element analysis (FEA) can accurately predict remaining strength, with strong correlation with actual burst tests. However, parametric studies with FEA are time and computationally intensive. Alternatively, an artificial neural network-based equation can be used. In this work, an equation for predicting the remaining strength of mid-to-high strength pipelines (API 5L X52, X65, and X80) with a single corrosion defect subjected to combined loadings of internal pressure and longitudinal compressive stress was derived from an ANN model trained based on FEA results. For FEA, the pipe was assumed to be isotropic and homogenous, and the effects of temperature on the pipe failure pressure were not considered. The error of remaining strength predictions, based on the equation, ranged from −6.33% to 2.39% when compared to an unseen FEA dataset, with a correlation value (R2) of 0.9975. A parametric study was subsequently performed using the equation to determine the effects of material property, defect depth, defect length, and longitudinal compressive stress on the remaining strength of pipelines with a single corrosion defect. Defect depth reduced the failure pressure by more than 65% on average, longitudinal compressive stress by more than 20% on average, and defect length by more than 21% on average.
Highlights
Pipelines play a critical role in the continuous supply of hydrocarbons from one point to another
The authors of this paper propose an artificial neural network (ANN)-based equation to predict the failure pressure of a mid-to-high strength pipeline with a single corrosion defect subject to combined loadings of internal pressure and longitudinal compressive stress
Bjørnøy et al carried out full-scale burst tests on an API 5L X52 pipeline with a single corrosion defect subjected to internal pressure and longitudinal compressive stress
Summary
Pipelines play a critical role in the continuous supply of hydrocarbons from one point to another. Maintaining the integrity of pipelines requires routine inspection and remaining strength assessments Assessment standards such as ASME B31G, Modified B31G, RSTRENG Effective Area, PCORRC, and DNV RP-F101 are widely used to determine the remaining strength of corroded pipelines. They are mostly applicable for corroded pipelines with single defects only subjected to internal pressure. Of all the established corrosion assessment standards, DNV RP-F101 is the most comprehensive, as it can assess the remaining strength of a corroded pipeline with single defect corrosion subjected to internal pressure and longitudinal compressive stress. Pipelines are usually pressurised to transport hydrocarbons, and they experience hoop stress due to internal pressure uniformly acting outward in a circumferential direction
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