NDLI: Parametric study on single shot peening by dimensional analysis method incorporated with finite element method

Content Provider	Springer Nature Link
Author	Wu, Xian Qian Wang, Xi Wei, Yan Peng Song, Hong Wei Huang, Chen Guang
Copyright Year	2012
Abstract	Shot peening is a widely used surface treatment method by generating compressive residual stress near the surface of metallic materials to increase fatigue life and resistance to corrosion fatigue, cracking, etc. Compressive residual stress and dent profile are important factors to evaluate the effectiveness of shot peening process. In this paper, the influence of dimensionless parameters on maximum compressive residual stress and maximum depth of the dent were investigated. Firstly, dimensionless relations of processing parameters that affect the maximum compressive residual stress and the maximum depth of the dent were deduced by dimensional analysis method. Secondly, the influence of each dimensionless parameter on dimensionless variables was investigated by the finite element method. Furthermore, related empirical formulas were given for each dimensionless parameter based on the simulation results. Finally, comparison was made and good agreement was found between the simulation results and the empirical formula, which shows that a useful approach is provided in this paper for analyzing the influence of each individual parameter.
Starting Page	825
Ending Page	837
Page Count	13
File Format	PDF
ISSN	05677718
Journal	Acta Mechanica Sinica
Volume Number	28
Issue Number	3
e-ISSN	16143116
Language	English
Publisher	The Chinese Society of Theoretical and Applied Mechanics; Institute of Mechanics, Chinese Academy of Sciences
Publisher Date	2012-07-10
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Shot peening Maximum compressive residual stress Maximum depth of the dent Dimensional analysis method Finite element method Theoretical and Applied Mechanics Classical Continuum Physics Engineering Fluid Dynamics Computational Intelligence
Content Type	Text
Resource Type	Article
Subject	Mechanical Engineering Computational Mechanics

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