Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published November 19, 2008 | Published
Journal Article Open

Rise of correlations of transformation strains in random polycrystals

Abstract

We investigate the statistics of the transformation strains that arise in random martensitic polycrystals as boundary conditions cause its component crystallites to undergo martensitic phase transitions. In our laminated polycrystal model the orientation of the n grains (crystallites) is given by an uncorrelated random array of the orientation angles θ_i, i = 1, . . . ,n. Under imposed boundary conditions the polycrystal grains may undergo a martensitic transformation. The associated transformation strains ε_i, i = 1, . . . ,n depend on the array of orientation angles, and they can be obtained as a solution to a nonlinear optimization problem. While the random variables θ_i, i = 1, . . . ,n are uncorrelated, the random variables ε_i, i = 1, . . . ,n may be correlated. This issue is central in our considerations. We investigate it in following three different scaling limits: (i) Infinitely long grains (laminated polycrystal of height L = ∞); (ii) Grains of finite but large height (L » 1); and (iii) Chain of short grains (L = l_0/(2n), l_0 « 1). With references to de Finetti's theorem, Riesz' rearrangement inequality, and near neighbor approximations, our analyses establish that under the scaling limits (i), (ii), and (iii) the arrays of transformation strains arising from given boundary conditions exhibit no correlations, long-range correlations, and exponentially decaying short-range correlations, respectively

Additional Information

© 2008 Society for Industrial and Applied Mathematics. Received by the editors January 9, 2007; accepted for publication (in revised form) June 24. 2008; published electronically November 19, 2008. We thank Alexei Borodin and Omri Sarig for useful discussions. We are grateful to anonymous referees for their useful suggestions. AMS subject classifications. 35J20, 74N15, 82B44

Attached Files

Published - Berlyand2008p247Siam_J_Math_Anal.pdf

Files

Berlyand2008p247Siam_J_Math_Anal.pdf
Files (516.1 kB)
Name Size Download all
md5:a34c840cc34d4871378fd76bbbd0a472
516.1 kB Preview Download

Additional details

Created:
August 19, 2023
Modified:
October 18, 2023