ANN-and FEA-Based Assessment Equation for a Corroded Pipeline with a Single Corrosion Defect

Most of the standards available for the assessment of the failure pressure of corroded pipelines are limited in their ability to assess complex loadings, and their estimations are conservative. To overcome this research gap, this study employed an artificial neural network (ANN) model trained with d...

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Main Authors: Lo, M., Karuppanan, S., Ovinis, M.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.33159 /
Published: MDPI 2022
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128370526&doi=10.3390%2fjmse10040476&partnerID=40&md5=7106bf71608adb1763e57c2968b1ca7f
http://eprints.utp.edu.my/33159/
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spelling utp-eprints.331592022-06-09T08:23:15Z ANN-and FEA-Based Assessment Equation for a Corroded Pipeline with a Single Corrosion Defect Lo, M. Karuppanan, S. Ovinis, M. Most of the standards available for the assessment of the failure pressure of corroded pipelines are limited in their ability to assess complex loadings, and their estimations are conservative. To overcome this research gap, this study employed an artificial neural network (ANN) model trained with data obtained using the finite element method (FEM) to develop an assessment equation to predict the failure pressure of a corroded pipeline with a single corrosion defect. A finite element analysis (FEA) of medium-toughness pipelines (API 5L X65) subjected to combined loads of internal pressure and longitudinal compressive stress was carried out. The results from the FEA with various corrosion geometric parameters and loads were used as the training dataset for the ANN. After the ANN was trained, its performance was evaluated, and its weights and biases were obtained for the development of a corrosion assessment equation. The prediction from the newly developed equation has a good correlation value, R2 of 0.9998, with percentage errors ranging from �1.16 to 1.78, when compared with the FEA results. When compared with the failure pressure estimates based on the Det Norske Veritas (DNV-RP-F101) guidelines, the standard was more conservative in its prediction than the assessment equation developed in this study. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. MDPI 2022 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128370526&doi=10.3390%2fjmse10040476&partnerID=40&md5=7106bf71608adb1763e57c2968b1ca7f Lo, M. and Karuppanan, S. and Ovinis, M. (2022) ANN-and FEA-Based Assessment Equation for a Corroded Pipeline with a Single Corrosion Defect. Journal of Marine Science and Engineering, 10 (4). http://eprints.utp.edu.my/33159/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Most of the standards available for the assessment of the failure pressure of corroded pipelines are limited in their ability to assess complex loadings, and their estimations are conservative. To overcome this research gap, this study employed an artificial neural network (ANN) model trained with data obtained using the finite element method (FEM) to develop an assessment equation to predict the failure pressure of a corroded pipeline with a single corrosion defect. A finite element analysis (FEA) of medium-toughness pipelines (API 5L X65) subjected to combined loads of internal pressure and longitudinal compressive stress was carried out. The results from the FEA with various corrosion geometric parameters and loads were used as the training dataset for the ANN. After the ANN was trained, its performance was evaluated, and its weights and biases were obtained for the development of a corrosion assessment equation. The prediction from the newly developed equation has a good correlation value, R2 of 0.9998, with percentage errors ranging from �1.16 to 1.78, when compared with the FEA results. When compared with the failure pressure estimates based on the Det Norske Veritas (DNV-RP-F101) guidelines, the standard was more conservative in its prediction than the assessment equation developed in this study. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
format Article
author Lo, M.
Karuppanan, S.
Ovinis, M.
spellingShingle Lo, M.
Karuppanan, S.
Ovinis, M.
ANN-and FEA-Based Assessment Equation for a Corroded Pipeline with a Single Corrosion Defect
author_sort Lo, M.
title ANN-and FEA-Based Assessment Equation for a Corroded Pipeline with a Single Corrosion Defect
title_short ANN-and FEA-Based Assessment Equation for a Corroded Pipeline with a Single Corrosion Defect
title_full ANN-and FEA-Based Assessment Equation for a Corroded Pipeline with a Single Corrosion Defect
title_fullStr ANN-and FEA-Based Assessment Equation for a Corroded Pipeline with a Single Corrosion Defect
title_full_unstemmed ANN-and FEA-Based Assessment Equation for a Corroded Pipeline with a Single Corrosion Defect
title_sort ann-and fea-based assessment equation for a corroded pipeline with a single corrosion defect
publisher MDPI
publishDate 2022
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128370526&doi=10.3390%2fjmse10040476&partnerID=40&md5=7106bf71608adb1763e57c2968b1ca7f
http://eprints.utp.edu.my/33159/
_version_ 1741197811820527616
score 11.62408

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