Neutron diffraction studies and multivariant simulations of shape memory alloys: Concurrent verification of texture development and mechanical response predictions Xiujie Gao a , Aaron Stebner b , Donald W. Brown c , L. Catherine Brinson b,d,⇑ a General Motors Research and Development, Vehicle Development Research Laboratory, Warren, MI 48090, USA b Department of Mechanical Engineering, Northwestern University, Evanston, IL 60208, USA c Los Alamos National Laboratory, Mail Stop H805, Los Alamos, NM 87545, USA d Department of Materials Science and Engineering, Northwestern University, Evanston, IL 60208, USA Received 19 October 2010; received in revised form 1 June 2011; accepted 1 June 2011 Available online 29 June 2011 Abstract A new methodology has been developed to compare texture development and macroscopic response predictions of micromechanical shape memory alloy models directly with diffraction data. Using these methods empirical neutron diffraction data from sequential, multi- axial, compressive loading schemes were compared with calculations from the simplified multivariant model. Through this process the ability of a multivariant model to predict both the texture development and mechanical response trends during the creation of complex stress states in martensitic polycrystalline NiTi was demonstrated for the first time. The result made it evident that a multivariant model is more completely validated through simultaneous verification of micro and macroscale predictions as opposed to only verifying mac- roscale predictions, as was the previous state of the art. The new methodology presented here provides the means to perform this mul- tiscale verification for any multivariant model. It is also shown that in combining a multivariant model with diffraction techniques a new tool for examining the plausibility of variant growth and depletion mechanisms has been created. Ó 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved. Keywords: Shape memory alloy; Texture evolution; Multivariant modeling; Micromechanical modeling; Diffraction 1. Introduction As the significance of texture evolution in shape mem- ory behavior becomes more evident (as briefly reviewed in Stebner et al. [1]) and the number of shape memory alloy (SMA) compositions and applications that use them continue to increase, so does the desire for predic- tive models of shape memory behavior. Implementation of a phenomenological model that is robust enough to replicate the entirety of macroscopic SMA responses for an arbitrary alloy system has proven to be a very challenging feat. Indeed, even formulating a macroscale model capable of replicating the entirety of a single NiTi composition’s behavior without intermediate recalibra- tion and the pre-existence of an extensive thermo- mechanical database has not been achieved, although great advances towards this goal are being made [2–5]. Many of the behavioral phenomena that lead to shape memory qualities are based on changes in microstructure that differ from the mechanisms of traditional elastic– plastic metals, and explicit tracking of the microstructure is not accounted for in macroscopic, phenomenological formulations. In response to the desire for predictive 1359-6454/$36.00 Ó 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.actamat.2011.06.001 ⇑ Corresponding author at: Department of Mechanical Engineering, Northwestern University, Evanston, IL 60208, USA. Tel.: +1 847 467 2347. E-mail address: cbrinson@northwestern.edu (L.C. Brinson). www.elsevier.com/locate/actamat Available online at www.sciencedirect.com Acta Materialia 59 (2011) 5924–5937