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TECHNICAL PAPERS

# Dynamic Material Behavior Modeling Using Internal State Variable Plasticity and Its Application in Hard Machining Simulations

[+] Author and Article Information
Y. B. Guo1

Department of Mechanical Engineering, The University of Alabama, Tuscaloosa, AL 35487yguo@eng.ua.edu

Q. Wen, K. A. Woodbury

Department of Mechanical Engineering, The University of Alabama, Tuscaloosa, AL 35487

1

To whom correspondence should be addressed.

J. Manuf. Sci. Eng 128(3), 749-759 (Dec 11, 2005) (11 pages) doi:10.1115/1.2193549 History: Received July 28, 2005; Revised December 11, 2005

## Abstract

Work materials experience large strains, high strain rates, high temperatures, and complex loading histories in machining. The problem of how to accurately model dynamic material behavior, including the adiabatic effect is essential to understand a hard machining process. Several conventional constitutive models have often been used to approximate flow stress in machining analysis and simulations. The empirical or semiempirical conventional models lack mechanisms for incorporating isotropic/kinematic hardening, recovery, and loading history effects. In this study, the material constants of AISI 52100 steel (62 HRc) were determined for both the Internal State Variable (ISV) plasticity model and the conventional Johnson-Cook (JC) model. The material constants were obtained by fitting the ISV and JC models using nonlinear least square methods to same baseline test data at different strains, strain rates, and temperatures. Both models are capable of modeling strain hardening and thermal softening phenomena. However, the ISV model can also accommodate the adiabatic and recovery effects, while the JC model is isothermal. Based on the method of design of experiment, FEA simulations and corresponding cutting tests were performed using the cutting tool with a $20$ deg chamfer angle. The predicted chip morphology using the ISV model is consistent with the measured chips, while the JC model is not. The predicted temperatures can be qualitatively verified by the subsurface microstructure. In addition, the ISV model gave larger subsurface von Mises stress, plastic strain, and temperature compared with those by the JC model.

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## Figures

Figure 1

A comparison between the test data of AISI 52100 steel and BCJ model predictions

Figure 2

Adiabatic curves predicted by the BCJ model

Figure 3

A comparison between the test data of AISI 52100 steel and JC model predictions

Figure 4

Schematic of orthogonal cutting test (not to scale)

Figure 5

Cutting tool and edge geometry

Figure 6

Schematic of simulation and node path in the subsurface

Figure 7

Chip morphology characterization

Figure 8

Measured and simulated chip morphology (JC model)

Figure 9

(a) Measured and simulated chip morphology (BCJ model) at V=1.5m∕s, DOC=120μm; (b) measured and simulated chip morphology (BCJ model) at V=1.7m∕s, DOC=120μm; (c) measured and simulated chip morphology (BCJ model) at V=2.09m∕s, DOC=120μm

Figure 10

(a) Measured and simulated chip morphology (BCJ model) at DOC=60μm, V=1.7m∕s; (b) measured and simulated chip morphology (BCJ model) at DOC=90μm, V=1.7m∕s

Figure 11

(a) The velocity effect on von Mises stress; (b) the DOC effect on von Mises stress

Figure 12

(a) The velocity effect on PEEQ; (b) the DOC effect on PEEQ

Figure 13

(a) The velocity effect on temperature; (b) the DOC effect on temperature

Figure 14

The effects of process parameters on subsurface microstructure

Figure 15

(a) A comparison of von Mises stress distribution by the BCJ vs JC model; (b) a comparison of PEEQ distribution by the BCJ vs JC model; (c) a comparison of the temperature distribution by the BCJ vs JC model

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