1-3 of 3
Haibo Xie
Close
Save search
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Close Modal
Sort by
Journal Articles

Prediction of Friction Coefficients During Scratch Based on an Integrated Finite Element and Artificial Neural Network Method

Haibo Xie, Zhanjiang Wang, Na Qin, Wenhao Du, Linmao Qian
Journal: Journal of Tribology
Publisher: ASME
Article Type: Research Papers
J. Tribol. February 2020, 142(2): 021703.
Paper No: TRIB-18-1430
https://doi.org/10.1115/1.4045013
Published Online: October 17, 2019
View Article titled, Prediction of Friction Coefficients During Scratch Based on an Integrated Finite Element and Artificial Neural Network Method
Open the PDF for Prediction of Friction Coefficients During Scratch Based on an Integrated Finite Element and Artificial Neural Network Method in another window
Topics: Artificial neural networks, Finite element analysis, Friction, Shear (Mechanics), Simulation, Deformation
Journal Articles

Comparative Study of RC Members with Strengthening Using Strain Hardening Cementitious Composite and Fiber Reinforced Mortar

Yongxing Zhang, Cheng Liu, Weihua Lu, Haibo Xie, Hui Peng
Journal: Journal of Testing and Evaluation
Publisher: ASTM International
Article Type: Technical Papers
J. Test. Eval.. January 2019, 47(1): 35–42.
Paper No: JTE20170439
https://doi.org/10.1520/JTE20170439
Published Online: January 2, 2019
View Article titled, Comparative Study of RC Members with Strengthening Using Strain Hardening Cementitious Composite and Fiber Reinforced Mortar
Open the PDF for Comparative Study of RC Members with Strengthening Using Strain Hardening Cementitious Composite and Fiber Reinforced Mortar in another window
Proceedings Papers

Finite State Machine Assisted Automatic Tonnage Signal Clustering for Multiple-Operation Forging Processes

Yong Lei, Haibo Xie
Proc. ASME. IMECE2013, Volume 2A: Advanced Manufacturing, V02AT02A065, November 15–21, 2013
Publisher: American Society of Mechanical Engineers
Paper No: IMECE2013-63493
https://doi.org/10.1115/IMECE2013-63493
View Paper titled, Finite State Machine Assisted Automatic Tonnage Signal Clustering for Multiple-Operation Forging Processes
Open the PDF for Finite State Machine Assisted Automatic Tonnage Signal Clustering for Multiple-Operation Forging Processes in another window
Topics: Forging, Machinery, Signals, Errors, Forging machinery, Deformation, Manufacturing, Metalworking, Modeling, Process monitoring