Application of Artificial Neural Network to Multi-Variables Regression for Estimations of J-Integral for Surface Cracked Pipes

Published: Aug 3, 2020
Abstract
Crack assessment for pipe components of a nuclear power plant or oil/gas pipeline is one of the essential procedures to ensure safe operation services. To assess cracked pipes, J-integral has been considered as a theoretically robust and useful elastic-plastic fracture parameter, so that the estimations of J-integral for various pipe geometries, material properties and loading conditions are highly needed. For this reason, many engineering...
Paper Details
Title
Application of Artificial Neural Network to Multi-Variables Regression for Estimations of J-Integral for Surface Cracked Pipes
Published Date
Aug 3, 2020
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