文献类型：期刊文献

英文题名：Evaluation of Strength Properties of In-Service X80 Pipeline Steel Using Small Punch Test and Backpropagation Neural Network

作者：Song, Ming[1]; Li, Xuyang[1]; Jiang, Wenchun[2]; Zhong, Jiru[3]; Guan, Kaishu[3]

机构：[1] College of Pipeline and Civil Engineering, China University of Petroleum [East China], Qingdao, 266580, China; [2] College of New Energy, China University of Petroleum [East China], Qingdao, 266580, China; [3] School of Mechanical and Power Engineering, East China University of Science and Technology, Shanghai, 200237, China

年份：2021

外文期刊名：Research Square

收录：EI(收录号：20220216487)

语种：英文

外文关键词：Backpropagation - Elastoplasticity - Materials handling - Neural networks - Nondestructive examination - Pipelines - Steel pipe - Strain - Strength of materials - Stress-strain curves - Tensile testing

摘要：Evaluating the strength properties of materials of an in-service pipeline without shutting down transportation has been always a challenge. A novel and non-destructive method for determining the true stress-strain curve of pipeline steel based on backpropagation artificial neural network and small punch test is proposed in this study. The elastoplastic mechanical properties of the pipeline steels could be obtained by this method. The load-displacement curves of 2261 groups of different hypothetical materials were obtained by the finite element model of small punch test within Gurson-Tvergaard-Needleman (GTN) damage parameters and used to train the neural network. The relationship between the load-displacement curve of small punch test and the true stress-strain curve of the conventional uniaxial tensile test was established based on the trained neural network. The accuracy and wide applicability of the trained neural network were verified by the experimental data of four types of materials obtained by small punch test and standard tensile test, respectively. The established relationship can be used to predict the true stress-strain curve of the pipeline steels to determine the elastoplastic mechanical properties only by the load-displacement curve of the small punch test without performing the conventional tensile test. ? 2021, CC BY.