4.5 Article

Subsurface Deformation Generated by Orthogonal Cutting: Analytical Modeling and Experimental Verification

出版社

ASME
DOI: 10.1115/1.4036994

关键词

subsurface deformation; analytical modeling; orthogonal cutting; digital image correlation

资金

  1. National Natural Science Foundation of China [51375005]
  2. National Basic Research Program of China [2014CB046704]

向作者/读者索取更多资源

Subsurface deformation of the cutting process has attracted a great deal of attention due to its tight relationship with subsurface hardening, microstructure alteration, grain refinement, and white layer formation. To predict the subsurface deformation of the machined components, an analytical model is proposed in this paper. The mechanical and thermal loads exerted on the workpiece by the primary and tertiary shear zones are predicted by a combination of Oxley's predictive model and Fang's slip line field. The stress field and temperature field are calculated based on contact mechanics and the moving heat source theory, respectively. However, the elastic-plastic regime induced by the material yielding hinders the direct derivation of subsurface plastic deformation from the stress field and the work material constitutive model. To tackle this problem, a blending function of the increment of elastic strain is developed to derive the plastic strain. In addition, a sophisticated material constitutive model considering strain hardening, strain rate sensitivity, and thermal softening effects of work material is incorporated into this analytical model. To validate this model, finite element simulations of the subsurface deformation during orthogonal cutting of AISI 52100 steel are conducted. Experimental verification of the subsurface deformation is carried out through a novel subsurface deformation measurement technique based on digital image correlation (DIC) technique. To demonstrate applications of the subsurface deformation prediction, the subsurface microhardness of the machined component is experimentally tested and compared against the predicted values based on the proposed method.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据