Failure Pressure Prediction of Medium to High Toughness Pipe with Circumferential Interacting Corrosion Defects Subjected to Combined Loadings Using Artificial Neural Network

Assessment of a corroded pipe is crucial to determine when it must be repaired or replaced. However, the conventional corrosion assessment codes for failure pressure predictions pipes with circumferentially aligned interacting defects are conservative (underestimations more than 40%), resulting in premature repair replacements pipelines. Alternatively, numerical approaches may used, but they time consuming and computationally expensive. In this study, an analytical equation based on finite element analysis prediction API 5L X52, X65, X80 subjected combined loadings proposed. An artificial neural network trained obtained from three grades varied defect spacings, depths lengths, axial compressive stress were used develop equation. Subsequently, parametric study effects these parameters circumferential-interacting was conducted using correlation between geometries pipe. The new equations predicted pressures R2 value 0.99 error range −9.92% 0.98% normalised spacings 0.00 3.00, effective lengths 2.95, 0.80, 0.60.