Optimization of Shot Peening Effective Parameters on Surface Hardness Improvement

被引：28
|
作者：
Maleki, Erfan [1 ,2 ]
Unal, Okan [3 ]
机构：
[1] Sharif Univ Technol, Mech Engn Dept, Int Campus, Kish Isl 111558639, Iran
[2] Politecn Milan, Mech Engn Dept, I-23994488 Milan, Italy
[3] Karabuk Univ, Mech Engn Dept, TR-78050 Karabuk, Turkey
来源：
METALS AND MATERIALS INTERNATIONAL | 2021年 / 27卷 / 09期
关键词：
Shot peening; Surface treatments; Hardness; Modeling; Artificial neural network; ARTIFICIAL NEURAL-NETWORK; FINITE-ELEMENT SIMULATION; FATIGUE BEHAVIOR; RESIDUAL-STRESS; CARBON-STEEL; AISI; 304; MODEL; MICROSTRUCTURE; DEFORMATION; PREDICTION;
D O I：
10.1007/s12540-020-00758-x
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Shot peening is well-known process for mechanical properties integrity in metallic materials. In present study influences of different shot peening treatments on the surface hardness of different carbon steels were investigated experimentally and then alternative approach by using artificial neural network is presented for hardness prediction of the shot peened surface. After modeling a comprehensive parametric investigations and sensitivity analysis were applied according to the influence of the related effective parameters on surface hardness improvements. Graphic
引用
收藏
页码：3173 / 3185
页数：13
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