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Journal of Manufacturing Science and Engineering | Volume 127 | Issue 3 | TECHNICAL PAPERS
TECHNICAL PAPERS

Numerical Simulations and Design of Shearing Process for Aluminum Alloys

[+] Author and Article Information
Aniruddha Khadke

Department of Mechanical Engineering,  The Ohio State University, Columbus, OH 43210

Somnath Ghosh1

Department of Mechanical Engineering,  The Ohio State University, Columbus, OH 43210ghosh.5@osu.edu

Ming Li2

Department of Mechanical Engineering,  The Ohio State University, Columbus, OH 43210

1

Author to whom correspondence should be addressed.

2

Currently Section Head, Process Mechanics, Alcoa Technical Center, PA 15069.

J. Manuf. Sci. Eng 127(3), 612-621 (Jul 21, 2004) (10 pages) doi:10.1115/1.1951787 History: Received September 22, 2003; Revised July 21, 2004
Article
References
Figures
Tables
Citing Articles

This work combines experimental studies with finite element simulations to develop a reliable numerical model for the simulation of shearing process in aluminum alloys. The critical concern with respect to product quality in this important process is burr formation. Numerical simulations are aimed at understanding the role of process variables on burr formation and for recommending process design parameters. The commercial code ABAQUS -Explicit with the arbitrary Lagrangian-Eulerian kinematic description is used in this study for numerical simulations. An elastic-plastic constitutive model with experimentally validated damage models are incorporated through the user subroutine VUMAT in ABAQUS , for modeling deformation and ductile fracture in the material. Macroscopic experiments with microscopic observations are conducted to characterize the material and to calibrate the constitutive and damage models. Parametric study is done to probe the effect of process parameters and finally, a genetic algorithm (GA) based design method is used to determine process parameters for minimum burr formation.
Copyright © 2005 by American Society of Mechanical Engineers
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References

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Figures

Grahic Jump Location
+(a) Schematic of (a) the shearing process and (b) the cut profile
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(a) Schematic of (a) the shearing process and (b) the cut profile
Figure 1

(a) Schematic of (a) the shearing process and (b) the cut profile

Grahic Jump Location
+(a) Dimensions of the dog-bone specimen (in inches), (b) true stress-plastic strain response of the aluminum alloy AA6022-T4, (c) geometric imperfection introduced in the FE model of the dogbone specimen
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(a) Dimensions of the dog-bone specimen (in inches), (b) true stress-plastic strain response of the aluminum alloy AA6022-T4, (c) geometric imperfection introduced in the FE model of the dogbone specimen
Figure 2

(a) Dimensions of the dog-bone specimen (in inches), (b) true stress-plastic strain response of the aluminum alloy AA6022-T4, (c) geometric imperfection introduced in the FE model of the dogbone specimen

Grahic Jump Location
+(a) Dimensions of the notched specimen (in inches), (b) the corresponding quarter finite element model, and (c) sample micrograph near the notch at 11.2% strain
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(a) Dimensions of the notched specimen (in inches), (b) the corresponding quarter finite element model, and (c) sample micrograph near the notch at 11.2% strain
Figure 3

(a) Dimensions of the notched specimen (in inches), (b) the corresponding quarter finite element model, and (c) sample micrograph near the notch at 11.2% strain

Grahic Jump Location
+Load-strain experimental curve for the dog-bone specimen showing failure with simulated results of three damage models
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Load-strain experimental curve for the dog-bone specimen showing failure with simulated results of three damage models
Figure 4

Load-strain experimental curve for the dog-bone specimen showing failure with simulated results of three damage models

Grahic Jump Location
+Crack profiles in the dogbone sample for: (a) Experiment, (b) simulations with the Tvergaard-Gurson model, (c) simulations with the Cockroft-Latham model, (d) simulations with the shear failure model
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Crack profiles in the dogbone sample for: (a) Experiment, (b) simulations with the Tvergaard-Gurson model, (c) simulations with the Cockroft-Latham model, (d) simulations with the shear failure model
Figure 5

Crack profiles in the dogbone sample for: (a) Experiment, (b) simulations with the Tvergaard-Gurson model, (c) simulations with the Cockroft-Latham model, (d) simulations with the shear failure model

Grahic Jump Location
+Flowchart showing steps of the genetic algorithm (GA) method
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Flowchart showing steps of the genetic algorithm (GA) method
Figure 6

Flowchart showing steps of the genetic algorithm (GA) method

Grahic Jump Location
+Convergence of GA in the calibration of parameters with Tvergaard-Gurson model
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Convergence of GA in the calibration of parameters with Tvergaard-Gurson model
Figure 7

Convergence of GA in the calibration of parameters with Tvergaard-Gurson model

Grahic Jump Location
+Void volume fraction as a function of the overall strain for experiments and simulations with the Tvergaard-Gurson model
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Void volume fraction as a function of the overall strain for experiments and simulations with the Tvergaard-Gurson model
Figure 8

Void volume fraction as a function of the overall strain for experiments and simulations with the Tvergaard-Gurson model

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+(a) The finite element model setup of the edge shearing problem in ABAQUS explicit, (b) Zoomed view of the mesh in the deformation zone showing the transition between coarse and fine mesh
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(a) The finite element model setup of the edge shearing problem in ABAQUS explicit, (b) Zoomed view of the mesh in the deformation zone showing the transition between coarse and fine mesh
Figure 9

(a) The finite element model setup of the edge shearing problem in ABAQUS explicit, (b) Zoomed view of the mesh in the deformation zone showing the transition between coarse and fine mesh

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+(a) Contour plot of void volume fraction with the Tvergaard-Gurson model showing arrested cracking, (b) contour plot of equivalent plastic strain with the Cockroft-Latham model
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(a) Contour plot of void volume fraction with the Tvergaard-Gurson model showing arrested cracking, (b) contour plot of equivalent plastic strain with the Cockroft-Latham model
Figure 10

(a) Contour plot of void volume fraction with the Tvergaard-Gurson model showing arrested cracking, (b) contour plot of equivalent plastic strain with the Cockroft-Latham model

Grahic Jump Location
+Results of simulation with shear failure model showing contour plots of equivalent plastic strain, for 5% clearance, 0.025mm blade radius and 0deg cutting angle. (a) at 0.14mm blade travel, (b) at 0.15mm blade travel, (c) at 0.18mm blade travel and (d) experimentally obtained micrographs of the sheared region
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Results of simulation with shear failure model showing contour plots of equivalent plastic strain, for 5% clearance, 0.025mm blade radius and 0deg cutting angle. (a) at 0.14mm blade travel, (b) at 0.15mm blade travel, (c) at 0.18mm blade travel and (d) experimentally obtained micrographs of the sheared region
Figure 11

Results of simulation with shear failure model showing contour plots of equivalent plastic strain, for 5% clearance, 0.025mm blade radius and 0deg cutting angle. (a) at 0.14mm blade travel, (b) at 0.15mm blade travel, (c) at 0.18mm blade travel and (d) experimentally obtained micrographs of the sheared region

Grahic Jump Location
+Simulation results of shearing process using 3D model, isometric view of the process showing the cut surface. The elements with value 0 for the STATUS variable correspond to the failed elements (crack)
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Simulation results of shearing process using 3D model, isometric view of the process showing the cut surface. The elements with value 0 for the STATUS variable correspond to the failed elements (crack)
Figure 12

Simulation results of shearing process using 3D model, isometric view of the process showing the cut surface. The elements with value 0 for the STATUS variable correspond to the failed elements (crack)

Grahic Jump Location
+Convergence of GA in the minimization of the burr height as functions of the design variables with increasing generation numbers
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Convergence of GA in the minimization of the burr height as functions of the design variables with increasing generation numbers
Figure 13

Convergence of GA in the minimization of the burr height as functions of the design variables with increasing generation numbers

Grahic Jump Location
+(a) Simulated and (b) experimentally observed burr height as functions of the clearance for different radii, for 0deg cutting angle
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(a) Simulated and (b) experimentally observed burr height as functions of the clearance for different radii, for 0deg cutting angle
Figure 14

(a) Simulated and (b) experimentally observed burr height as functions of the clearance for different radii, for 0deg cutting angle

Grahic Jump Location
+(a) Simulated and (b) experimental burr heights as functions of cutting angles for different blade radii for 5% clearance
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(a) Simulated and (b) experimental burr heights as functions of cutting angles for different blade radii for 5% clearance
Figure 15

(a) Simulated and (b) experimental burr heights as functions of cutting angles for different blade radii for 5% clearance

Grahic Jump Location
+Simulated burr height as a function of the cutting angle at 5% clearance and 0.025mm blade radius
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Simulated burr height as a function of the cutting angle at 5% clearance and 0.025mm blade radius
Figure 16

Simulated burr height as a function of the cutting angle at 5% clearance and 0.025mm blade radius

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