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Anand K. Kanjarla
Researcher at Indian Institute of Technology Madras
Publications - 47
Citations - 1726
Anand K. Kanjarla is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Grain boundary & Crystal twinning. The author has an hindex of 14, co-authored 36 publications receiving 1379 citations. Previous affiliations of Anand K. Kanjarla include Los Alamos National Laboratory & Indian Institutes of Technology.
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An elasto-viscoplastic formulation based on fast Fourier transforms for the prediction of micromechanical fields in polycrystalline materials
TL;DR: In this paper, the authors presented an infinitesimal-strain version of a formulation based on fast Fourier transforms (FFT) for the prediction of micromechanical fields in polycrystals deforming in the elasto-viscoplastic (EVP) regime.
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Numerical study of the stress state of a deformation twin in magnesium
TL;DR: In this paper, a numerical study of the distribution of the local stress state associated with deformation twinning in Mg is presented, both inside the twinned domain and in its immediate neighborhood, due to the accommodation of the twinning transformation shear.
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Polycrystal Plasticity: Comparison Between Grain- Scale Observations of Deformation and Simulations
Reeju Pokharel,Jonathan Lind,Anand K. Kanjarla,Ricardo A. Lebensohn,S. F. Li,Peter Kenesei,Robert M. Suter,Anthony D. Rollett +7 more
TL;DR: In this article, the response of polycrystals to plastic deformation is studied at the level of variations within individual grains, and comparisons are made to theoretical calculations using crystal plasticity (CP).
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Stochastic modeling of twin nucleation in polycrystals: An application in hexagonal close-packed metals
TL;DR: In this paper, a stochastic model for the nucleation of deformation twins in hexagonal close-packed (hcp) polycrystals is presented, and the model is implemented into a viscoplastic self-consistent (VPSC) crystal plasticity framework to test its predictive capability against previously reported statistical characterization in deformed zirconium at multiple temperatures.
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Novel microstructure quantification framework for databasing, visualization, and analysis of microstructure data
TL;DR: In this paper, the authors developed and presented a novel microstructure quantification framework that facilitates the visualization of complex micro-structure relationships, both within a material class and across multiple material classes.