Experimental Validation of Two-dimensional Finite Element Method for Simulating Constitutive Response of Polycrystals During High Temperature Plastic Deformation
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A finite element method was recently designed to model the mechanisms that cause superplastic deformation (A.F. Bower and E. Wininger, A Two-Dimensional Finite Element Method for Simulating the Constitutive Response and Microstructure of Polycrystals during High-Temperature Plastic Deformation, J. Mech. Phys. Solids, 2004, 52, p 1289–1317). The computations idealize the solid as a collection of two-dimensional grains, separated by sharp grain boundaries. The grains may deform plastically by thermally activated dislocation motion, which is modeled using a conventional crystal plasticity law. The solid may also deform by sliding on the grain boundaries, or by stress-driven diffusion of atoms along grain boundaries. The governing equations are solved using a finite element method, which includes a front-tracking procedure to monitor the evolution of the grain boundaries and surfaces in the solid. The goal of this article is to validate these computations by systematically comparing numerical predictions to experimental measurements of the elevated-temperature response of aluminum alloy AA5083 (M.-A. Kulas, W.P. Green, E.M. Taleff, P.E. Krajewski, and T.R. McNelley, Deformation Mechanisms in Superplastic AA5083 materials. Metall. Mater. Trans. A, 2005, 36(5), p 1249–1261). The experimental work revealed that a transition occurs from grain-boundary sliding to dislocation (solute-drag) creep at approximately 0.001/s for temperatures between 425 and 500 °C. In addition, increasing the grain size from 7 to 10 μm decreased the transition to significantly lower strain rates. Predictions from the finite element method accurately predict the effect of grain size on the transition in deformation mechanisms.
Keywordsaluminum constitutive response deformation mechanisms dislocation creep finite element simulations grain-boundary sliding superplastic forming
This work was performed as part of the General Motors Collaborative Research Laboratory on Computational Materials Research at Brown University. Research at The University of Texas was funded by General Motors.
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