TY  - CONF
ID  - scholars17297
SP  - 191
TI  - Failure Pressure Prediction of Pipe Elbow with Longitudinally Aligned Interacting Corrosion Defects Subjected to Internal Pressure
KW  - Defects; Failure (mechanical); Forecasting; Neural networks; Pipeline corrosion
KW  -  Corroded pipe; Corrosion assessment; Corrosion defect; Empirical equations; Equation based; Failure pressure; Finite element analyse; Internal pressures; Pipe elbow; Pressure predictions
KW  -  Finite element method
N1  - cited By 0; Conference of 2022 International Conference on Digital Transformation and Intelligence, ICDI 2022 ; Conference Date: 1 December 2022 Through 2 December 2022; Conference Code:185994
N2  - Currently in the industry, the is a lack of designated corrosion assessment method for the failure pressure prediction of pipe elbows. In this study, empirical equations based on artificial neural network and finite element analysis for the failure pressure prediction of API 5L X52 corroded pipe elbow with longitudinally aligned interacting corrosion defects subjected to internal pressure is proposed. Artificial neural networks trained using failure pressure obtained from finite element analysis for varied defect spacings, depths, and lengths were used to develop the equations. The new equations predicted failure pressures for these pipe grades with a coefficient of determination value of 0.99 and an error range of-9.81 to 4.58 for normalized defect spacings of 0.00 to 2.00, normalized defect lengths of 0.00 to 1.00, and normalized defect depths of 0.00 to 0.80. © 2022 IEEE.
AV  - none
EP  - 196
A1  - Vijaya Kumar, S.D.
A1  - Tengku, H.A.
A1  - Karuppanan, S.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146988395&doi=10.1109%2fICDI57181.2022.10007102&partnerID=40&md5=8ae4d883737342002397bd2475dffd93
PB  - Institute of Electrical and Electronics Engineers Inc.
SN  - 9798350397000
Y1  - 2022///
ER  -