eprintid: 14381
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/43/81
datestamp: 2023-11-10 03:28:57
lastmod: 2023-11-10 03:28:57
status_changed: 2023-11-10 01:56:45
type: article
metadata_visibility: show
creators_name: Kumar, S.D.V.
creators_name: Karuppanan, S.
creators_name: Ovinis, M.
title: An empirical equation for failure pressure prediction of high toughness pipeline with interacting corrosion defects subjected to combined loadings based on artificial neural network
ispublished: pub
note: cited By 5
abstract: Conventional pipeline corrosion assessment methods for failure pressure prediction do not account for interacting defects subjected to internal pressure and axial compressive stress. In any case, the failure pressure predictions are conservative. As such, numerical methods are required. This paper proposes an alternative to the computationally expensive numerical methods, specifically an empirical equation based on Finite Element Analysis (FEA). FEA was conducted to generate training data for an ANN after validating the method against full scale burst test results from past research. An ANN with four inputs and one output was developed. The equation was developed based on the weights and biases of an ANN model trained with failure pressure from the FEA of a high toughness pipeline for various defect spacings, defect depths, defect lengths, and axial compressive stresses. The proposed model was validated against actual burst test results for high toughness materials, with a R2 value of 0.99. Extensive parametric study was subsequently conducted to determine the effects of defect spacing, defect length, defect depth, and axial compressive stress on the failure pressure of the pipe. The results of the empirical equation are comparable to the results from numerical methods for the pipes and loadings considered in this study. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
date: 2021
publisher: MDPI
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117492483&doi=10.3390%2fmath9202582&partnerID=40&md5=070e0d706d67152c2f2b15c179bf303a
id_number: 10.3390/math9202582
full_text_status: none
publication: Mathematics
volume: 9
number: 20
refereed: TRUE
issn: 22277390
citation:   Kumar, S.D.V. and Karuppanan, S. and Ovinis, M.  (2021) An empirical equation for failure pressure prediction of high toughness pipeline with interacting corrosion defects subjected to combined loadings based on artificial neural network.  Mathematics, 9 (20).   ISSN 22277390