Zhao Wei   

Professor

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Language:English

Paper Publications

Title of Paper:An inverse-identification-based finite element simulation of orthogonal cutting tungsten carbide

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Affiliation of Author(s):机电学院

Journal:J. Braz. Soc. Mech. Sci. Eng.

Abstract:Modeling and simulation using finite element method (FEM) is a powerful estimation tool and has been greatly helpful to study the metal cutting process, such as investigation of cutting mechanism, optimization of cutting parameters, and design of cutting tools. Thereinto, an effective material model and its parameters are still key problems in the FEM-modeling of metal cutting. In this paper, a 2D FE model for simulating the orthogonal cutting of tungsten carbide WC-17.5Co is developed, in which an inverse identification approach is used to identify the parameters of material model based on orthogonal cutting experiments. The commercially available software DEFORM V11.0 is utilized to develop the FE model, whereas the Johnson–Cook model and Brozzo model are selected as the constitutive model and the fracture model of the work material, respectively. Continuous serrated chip formation is obtained in experiments as well as in FE simulations. The simulated chip morphology, cutting force, and specific cutting force are compared with the experimental results to identify the parameters of the material model. It is found that the chip morphology is more difficult to be used to identify inversely the material model parameters than the cutting force and specific cutting force. The material model parameters are derived, and the verification tests show that there is a close agreement between the simulated and experimental results through comparisons of cutting force and specific cutting force. It indicates that the inversely identified parameters of the Johnson–Cook model and the Brozzo model can be used to describe the mechanical property of tungsten carbide. © 2019, The Brazilian Society of Mechanical Sciences and Engineering.

ISSN No.:1678-5878

Translation or Not:no

Date of Publication:2019-02-01

Co-author:Yang, Qi,Khan, Aqib Mashood,hn,Zhang, Anshun

Correspondence Author:Zhao Wei

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