Slip Systems and Initiation of Plasticity in a Body-Centered-Cubic Titanium Alloy
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TRODUCTION
RECENT advances in three-dimensional (3-D) materials characterization, along with ever-increasing computational capability, have allowed for simulation of the mechanical response of large 3-D volumes of materials microstructures. In prior work, image-based finite element (FE) simulations were performed on datasets of relatively small reconstructed 3-D microstructures of metals to determine critical features, such as grain boundaries, triple junctions, or grain clusters, where plasticity is likely to initiate.[1–4] Applying image-based analysis tools to substantially larger 3-D datasets will allow for a comprehensive understanding of the complex relationships between microstructure and the mechanical behavior of materials systems. Accurate determination of microstructure-mechanical response correlations depends upon statistically adequate representations of the microstructure in computational models and accurate constitutive models, as well as data analysis through efficient data warehousing and mining. To represent a material microstructure, sufficiently large representative models are needed. The size of these models, however, is often constrained by ALEXIS C. LEWIS, Materials Research Engineer, and ANDREW B. GELTMACHER, Section Head, are with the Multifunctional Materials Branch, Code 6350, United States Naval Research Laboratory, Washington, DC. Contact e-mail: [email protected] SIDDIQ M. QIDWAI, Manager, is with the Science Applications International Corporation, c/o United States Naval Research Laboratory, Washington, DC 20375. Manuscript submitted September 4, 2009. Article published online June 29, 2010 2522—VOLUME 41A, OCTOBER 2010
computational time and cost. Some recent efforts to preclude the analysis of large volumes in single simulations aim to extract structure-property correlations with spectral methods borrowed from the signal processing industry (i.e., Reference 5). In many cases, however, the volume of the microstructural dataset must still be quite large to be representative of the bulk material while being sufficiently detailed to capture important behaviors at the microscale. Another potential technique for reducing computation times is to simplify the constitutive description. For example, in bcc materials, slip may occur on 48 individual slip systems. These systems, defined by the crystallographic direction along which slip occurs and the crystallographic slip plane normal, represent three families of planes: 12 systems are in the h111i{110} family, 12 in the h111i{112} family, and 24 in the h111i{123} family. The three families of planes for bcc slip are shown schematically in a cubic unit cell in Figure 1, and the associated plane normals and slip directions are given in Table I. While previous simulations have shown plastic slip to occur in slip systems of all three families,[3] some researchers have found the majority of slip activity to take place in the first two families of slip systems, h111i{110} and h111i{112}.[6,7] The contribution of slip on the {123} planes in bcc system
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