Xiaoben Liu

Prof. Dr. Xiaoben Liu

Department of Oil&Gas Storage and Transportation Engineering, China University of Petroleum-Beijing, Beijing 102249, China
orcid

Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2015 in Engineering Failure Analysis
Verified
Journal Article
Closed access
YCYanfei Chen
Yanfei Chen
HZHong Zhang
Hong Zhang
JZJuan Zhang
Juan Zhang
Xiaoben LiuXiaoben Liu
Xiaoben Liu
XLXin Li
Xin Li
JZJing Zhou
Jing Zhou

1 May 2016 in Journal of Natural Gas Science and Engineering
Verified
Journal Article
Closed access
Xiaoben LiuXiaoben Liu
Xiaoben Liu
HZHong Zhang
Hong Zhang
YHYinshan Han
Yinshan Han
MXMengying Xia
Mengying Xia
WZWei Zheng
Wei Zheng

1 July 2017 in Engineering Failure Analysis
Verified
Journal Article
Closed access
Xiaoben LiuXiaoben Liu
Xiaoben Liu
HZHong Zhang
Hong Zhang
KWKai Wu
Kai Wu
MXMengying Xia
Mengying Xia
YCYanfei Chen
Yanfei Chen
MLMeng Li
Meng Li

1 July 2016 in Journal of Natural Gas Science and Engineering
Verified
Journal Article
Closed access
Xiaoben LiuXiaoben Liu
Xiaoben Liu
HZHong Zhang
Hong Zhang
MLMeng Li
Meng Li
MXMengying Xia
Mengying Xia
WZWei Zheng
Wei Zheng
YHYinshan Han
Yinshan Han

1 August 2018 in Engineering Failure Analysis
Verified
Journal Article
Closed access
Xiaoben LiuXiaoben Liu
Xiaoben Liu
HZHong Zhang
Hong Zhang
MXMengying Xia
Mengying Xia
KWKai Wu
Kai Wu
YCYanfei Chen
Yanfei Chen
JLJun Li
Jun Li

3 November 2019 in Energy Science & Engineering
Verified
Journal Article
Open access
PDF file
Xiaoben LiuXiaoben Liu
Xiaoben Liu
MXMengying Xia
Mengying Xia
DBDinaer Bolati
Dinaer Bolati
JLJianping Liu
Jianping Liu
QZQian Zheng
Qian Zheng
HZHong Zhang
Hong Zhang
With continued increasing construction of both electrified facilities and buried high‐strength pipelines in China, stray current corrosion defects have become an nonignorable threat for these pipelines. A comprehensive investigation on a new failure pressure prediction model for high‐strength pipes with stray current corrosion defects was conducted in this study. The mechanism of stray current corrosion in steel pipes was firstly elaborated in brief. After that, a parameterized finite element model for stress analysis of pipes with external corrosion defects was programmed by APDL code developed by general software ANSYS. By comparing numerical results with full‐scale experimental results, both the numerical model and the failure criteria for pipe burst were proven to be reasonable. Based on the finite element model, parametric analysis was performed using a calculation matrix set by orthogonal testing method to investigate the effects of three main dimensionless factors, that is, ratio of pipe diameter to wall thickness, nondimensional corrosion defect length, and nondimensional corrosion defect depth on pipe's failure pressure. Utilizing the parametric analysis results as database, a multilayer feed‐forward artificial neural network (ANN) was developed for failure pressure prediction. By comparison with experimental burst test results and results of previous failure pressure estimation model, the ANN model results were proven to have both high accuracy and efficiency, which could be referenced in residual strength or safety assessment of high‐strength pipes with corrosion defects.