Veera Sundararaghavan
Cited by
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A predictive machine learning approach for microstructure optimization and materials design
R Liu, A Kumar, Z Chen, A Agrawal, V Sundararaghavan, A Choudhary
Scientific reports 5 (1), 11551, 2015
Classification and reconstruction of three-dimensional microstructures using support vector machines
V Sundararaghavan, N Zabaras
Computational Materials Science 32 (2), 223-239, 2005
PRISMS-Plasticity: An open-source crystal plasticity finite element software
M Yaghoobi, S Ganesan, S Sundar, A Lakshmanan, S Rudraraju, ...
Computational Materials Science 169, 109078, 2019
A peridynamic implementation of crystal plasticity
S Sun, V Sundararaghavan
International Journal of Solids and Structures 51 (19-20), 3350-3360, 2014
Design of microstructure-sensitive properties in elasto-viscoplastic polycrystals using multi-scale homogenization
V Sundararaghavan, N Zabaras
International Journal of Plasticity 22 (10), 1799-1824, 2006
Stability and strain-driven evolution of β′ precipitate in Mg-Y alloys
ELS Solomon, AR Natarajan, AM Roy, V Sundararaghavan, ...
Acta Materialia 166, 148-157, 2019
Linear analysis of texture–property relationships using process-based representations of Rodrigues space
V Sundararaghavan, N Zabaras
Acta materialia 55 (5), 1573-1587, 2007
Characterizing microscale deformation mechanisms and macroscopic tensile properties of a high strength magnesium rare-earth alloy: A combined experimental and crystal …
A Githens, S Ganesan, Z Chen, J Allison, V Sundararaghavan, S Daly
Acta Materialia 186, 77-94, 2020
A multi-length scale sensitivity analysis for the control of texture-dependent properties in deformation processing
V Sundararaghavan, N Zabaras
International Journal of Plasticity 24 (9), 1581-1605, 2008
The effects of heat treatment on the response of WE43 Mg alloy: crystal plasticity finite element simulation and SEM-DIC experiment
S Ganesan, M Yaghoobi, A Githens, Z Chen, S Daly, JE Allison, ...
International Journal of Plasticity 137, 102917, 2021
Study of temperature dependence of thermal conductivity in cross-linked epoxies using molecular dynamics simulations with long range interactions
A Kumar, V Sundararaghavan, AR Browning
Modelling and Simulation in Materials Science and Engineering 22 (2), 025013, 2014
Stress-point method for stabilizing zero-energy modes in non-ordinary state-based peridynamics
J Luo, V Sundararaghavan
International Journal of Solids and Structures 150, 197-207, 2018
Molecular dynamics simulations of compressive yielding in cross-linked epoxies in the context of Argon theory
V Sundararaghavan, A Kumar
International Journal of Plasticity 47, 111-125, 2013
Microstructure optimization with constrained design objectives using machine learning-based feedback-aware data-generation
A Paul, P Acar, W Liao, A Choudhary, V Sundararaghavan, A Agrawal
Computational Materials Science 160, 334-351, 2019
Reconstruction of three-dimensional anisotropic microstructures from two-dimensional micrographs imaged on orthogonal planes
V Sundararaghavan
Integrating Materials and Manufacturing Innovation 3 (19), 1-11, 2014
Thermal buckling of composite plates with spatial varying fiber orientations
AV Duran, NA Fasanella, V Sundararaghavan, AM Waas
Composite Structures 124, 228-235, 2015
Quantitative study of the effect of grain boundary parameters on the slip system level Hall-Petch slope for basal slip system in Mg-4Al
MT Andani, A Lakshmanan, V Sundararaghavan, J Allison, A Misra
Acta Materialia 200, 148-161, 2020
A Markov random field approach for microstructure synthesis
A Kumar, L Nguyen, M DeGraef, V Sundararaghavan
Modelling and Simulation in Materials Science and Engineering 24 (3), 035015, 2016
A novel approach for modelling of water jet peening
N Rajesh, S Veeraraghavan, N Ramesh Babu
International Journal of Machine Tools and Manufacture 44 (7-8), 855-863, 2004
A Markov random field approach for modeling spatio-temporal evolution of microstructures
P Acar, V Sundararaghavan
Modelling and Simulation in Materials Science and Engineering 24 (7), 075005, 2016
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