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Correlation between crystallographic orientation and mechanical response in a three-dimensional β-Ti microstructure

Published online by Cambridge University Press:  21 March 2011

A.C. Lewis ,
S.M. Qidwai ,
D.J. Rowenhorst  and
A.B. Geltmacher
A.C. Lewis*
Affiliation:
U.S. Naval Research Laboratory, Code 6350, Washington, District of Columbia 20375
S.M. Qidwai
Affiliation:
Science Applications International Corporation, Washington, District of Columbia 20375
D.J. Rowenhorst
Affiliation:
U.S. Naval Research Laboratory, Code 6350, Washington, District of Columbia 20375
A.B. Geltmacher
Affiliation:
U.S. Naval Research Laboratory, Code 6350, Washington, District of Columbia 20375
*
a)Address all correspondence to this author. e-mail: [email protected]
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Abstract

Three-dimensional image-based modeling is used to investigate the correlations between crystallographic orientation and mechanical response in a body-centered cubic (BCC) β-titanium microstructure. Statistical significance is achieved by combining the simulation data of multiple image-based crystal plasticity models. Each individual model contains ∼100 grains and is subjected to uniaxial and biaxial tensile loading conditions. Although the use of smaller sub-volumes instead of a single large representative volume may preclude accurate prediction of the global stress–strain response of the material, it is demonstrated here that the microstructural and mechanical information at the local (grain) scale can be used to establish statistically significant microstructure–property correlations. It is shown that grains with <100> orientations aligned with the loading axis experienced much smaller effective stresses and strains than those with <110> and <111> orientations aligned with the loading axis under both types of loading conditions.

Keywords

MicrostructureCrystallographic structureSimulation
Type
Invited Feature Paper
Information
Journal of Materials Research , Volume 26 , Issue 8 , 28 April 2011 , pp. 957 - 964
Copyright
Copyright © Materials Research Society 2011

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References

REFERENCES

1.Aretz, H., Luce, R., Wolske, M., Kopp, R., Gordeler, M., Pomana, G., and Gottstein, G.: Incorporation of microstructure and texture models into FEM. J. Phys. IV 11, 115 (2001).Google Scholar
2.Barbe, F., Forest, S., and Cailletaud, G.: Intergranular and intragranular behavior of polycrystalline aggregates. Part 2. Results. Int. J. Plasticity 17, 537 (2001).CrossRefGoogle Scholar
3.Brahme, A., Alvi, M.H., Saylor, D., Fridy, J., and Rollett, A.D.: 3D reconstruction of microstructure in a commercial purity aluminum. Scr. Mater. 55, 75 (2006).CrossRefGoogle Scholar
4.Buffiere, J.Y., Cloetens, P., Ludwig, W., Maire, E., and Salvo, L.: In situ x-ray tomography studies of microstructural evolution combined with 3D modeling. MRS Bull. 33, 611 (2008).CrossRefGoogle Scholar
5.Cailletaud, G., Forest, S., Jeulin, D., Feyel, F., Galliet, I., Mounoury, V., and Quilici, S.: Some elements of microstructural mechanics. Comput. Mater. Sci. 27, 351 (2003).CrossRefGoogle Scholar
6.Chawla, N. and Chawla, K.K.: Microstructure-based modeling of the deformation behavior of particle reinforced metal matrix composites. J. Mater. Sci. 41, 913 (2006).CrossRefGoogle Scholar
7.Chawla, N., Ganesh, V.V., and Wunsch, B.: Three-dimensional (3D) microstructure visualization and finite element modeling of the mechanical behavior of SiC particle reinforced aluminum composites. Scr. Mater. 51, 161 (2004).CrossRefGoogle Scholar
8.Chawla, N. and Sidhu, R.S.: Microstructure-based modeling of deformation in Sn-rich (Pb-free) solder alloys. J. Mater. Sci. Mater. Electron. 18, 175 (2007).CrossRefGoogle Scholar
9.Fife, J.L. and Voorhees, P.W.: Self-similar microstructural evolution of dendritic solid-liquid mixtures during coarsening. Scr. Mater. 60, 839 (2009).CrossRefGoogle Scholar
10.Groeber, M.A., Haley, B.K., Uchic, M.D., Dimiduk, D.M., and Ghosh, S.: 3D reconstruction and characterization of polycrystalline microstructures using a FIB-SEM system. Mater. Charact. 57, 259 (2006).CrossRefGoogle Scholar
11.Jensen, D.J., Offerman, S.E., and Sietsma, J.: 3DXRD characterization and modeling of solid-state transformation processes. MRS Bull. 33, 621 (2008).CrossRefGoogle Scholar
12.Juul Jensen, D. and Godiksen, R.B.N.: Neutron and synchrotron x-ray studies of recrystallization kinetics. Metall. Mater. Trans. A 39A, 3065 (2008).CrossRefGoogle Scholar
13.Kammer, D. and Voorhees, P.W.: Analysis of complex microstructures: Serial sectioning and phase-field simulations. MRS Bull. 33, 603 (2008).CrossRefGoogle Scholar
14.Lewis, A.C., Qidwai, S.M., and Geltmacher, A.B.: Slip systems and initiation of plasticity in a BCC titanium alloy. Metall. Mater. Trans. A 41, 2522 (2010).CrossRefGoogle Scholar
15.Madison, J., Spowart, J., Rowenhorst, D., Aagesen, L.K., Thornton, K., and Pollock, T.M.: Modeling fluid flow in three-dimensional single crystal dendritic structures. Acta Mater. 58, 2864 (2010).CrossRefGoogle Scholar
16.Qidwai, M.A.S., Lewis, A.C., and Geltmacher, A.B.: Using image-based computational modeling to study microstructure–yield correlations in metals. Acta Mater. 57, 4233 (2009).CrossRefGoogle Scholar
17.Rohrer, G.S., Holm, E.A., Rollett, A.D., Foiles, S.M., Li, J., and Olmsted, D.L.: Comparing calculated and measured grain boundary energies in nickel. Acta Mater. 58, 5063 (2010).CrossRefGoogle Scholar
18.Rowenhorst, D.J., Gupta, A., Feng, C.R., and Spanos, G.: 3D crystallographic and morphological analysis of coarse martensite: Combining EBSD and serial sectioning. Scr. Mater. 55, 11 (2006).CrossRefGoogle Scholar
19.Rowenhorst, D.J., Kuang, J.P., Thornton, K., and Voorhees, P.W.: Three-dimensional analysis of particle coarsening in high volume fraction solid-liquid mixtures. Acta Mater. 54, 2027 (2006).CrossRefGoogle Scholar
20.Spanos, G., Rowenhorst, D.J., Lewis, A.C., and Geltmacher, A.B.: Combining serial sectioning, EBSD analysis, and image-based finite element modeling. MRS Bull. 33, 597 (2008).CrossRefGoogle Scholar
21.Spowart, J.E., Mullens, H.M., and Puchala, B.T.: Collecting and analyzing microstructures in three dimensions: A fully automated approach. JOM 55, 35 (2003).CrossRefGoogle Scholar
22.Thornton, K. and Poulsen, H.F.: Three-diemensional materials science: An intersection of three-dimensional reconstructions and simulations. MRS Bull. 33, 587 (2008).CrossRefGoogle Scholar
23.Zhang, Y.B., Godfrey, A., Liu, Q., Liu, W., and Juul Jensen, D.: Analysis of the growth of individual grains during recrystallization in pure nickel. Acta Mater. 57, 2631 (2009).CrossRefGoogle Scholar
24.Barbe, F., Decker, L., Jeulin, D., and Cailletaud, G.: Intergranular and intragranular behavior of polycrystalline aggregates. Part 1: F.E. model. Int. J. Plast. 17, 513 (2001).CrossRefGoogle Scholar
25.Asaro, R.J.: Crystal plasticity. J. Appl. Mech. Trans. ASME 50, 921 (1983).CrossRefGoogle Scholar
26.Ortiz, C., Eriksson, O., and Klintenberg, M.: Data mining and accelerated electronic-structure theory as a tool in the search for new functional materials. Comput. Mater. Sci. 44, 1042 (2009).CrossRefGoogle Scholar
27.Rajan, K.: Combinatorial materials sciences: Experimental strategies for accelerated knowledge discovery. Annu. Rev. Mater. Res. 38, 299 (2008).CrossRefGoogle Scholar
28.Suh, C. and Rajan, K.: Data mining and informatics for crystal chemistry: Establishing measurement techniques for mapping structure-property relationships. Mater. Sci. Technol. 25, 466 (2009).CrossRefGoogle Scholar
29.Sundararaghavan, V. and Zabaras, N.: Linear analysis of texture-property relationships using process-based representations of Rodrigues space. Acta Mater. 55, 1573 (2007).CrossRefGoogle Scholar
30.Carpay, F.M.A., Chin, G.Y., Mahajan, S., and Rubin, J.J.: Constrained deformation of molybdenum single-crystals. Acta Metall. 23, 1473 (1975).CrossRefGoogle Scholar
31.Orlans-Joliet, B., Bacroix, B., Montheillet, F., Driver, J.H., and Jonas, J.J.: Yield surfaces of bcc crystals for slip on the (110) (111) and (112) (111) systems. Acta Metall. 36, 1365 (1988).CrossRefGoogle Scholar
32.Fullwood, D.T., Niezgoda, S.R., Adams, B.L., and Kalidindi, S.R.: Microstructure sensitive design for performance optimization. Prog. Mater. Sci. 55, 477 (2010).CrossRefGoogle Scholar
33.Rowenhorst, D.J., Lewis, A.C., and Spanos, G.: Three-dimensional analysis of grain topology and interface curvature in a beta titanium alloy. Acta Mater. 58, 5511 (2010).CrossRefGoogle Scholar
34.Lewis, A.C. and Geltmacher, A.B.: Image-based modeling of the response of experimental 3D microstructures to mechanical loading. Scr. Mater. 55, 81 (2006).CrossRefGoogle Scholar
35.Lewis, A. C., Jordan, K. A., and Geltmacher, A. B.: Determination of critical microstructural features in an austenitic stainless steel using image-based finite element modeling. Metall. Mater. Trans A 39A, 1109–1117 (2008).CrossRefGoogle Scholar
36.Asaro, R.J.: Micromechanics of crystals and polycrystals, in Advances in Applied Mechanics, edited by Hutchinson, J.W. and Wu, T.Y. (Academic Press, New York, 1983), p. 1–115.Google Scholar
37.Huang, Y.: A User-Material Subroutine Incorporating Single Crystal Plasticity in the ABAQUS Finite Element Program (Division of Applied Sciences, Harvard University, Cambridge, MA, 1991).Google Scholar
38.Raabe, D., Sachtleber, M., Zhao, Z., Roters, F., and Zaefferer, S.: Micromechanical and macromechanical effects in grain scale polycrystal plasticity experimentation and simulation. Acta Mater. 49, 3433 (2001).CrossRefGoogle Scholar