Parhitosh Sharma - Academia.edu (original) (raw)
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CSIC (Consejo Superior de Investigaciones CientÃficas-Spanish National Research Council)
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Papers by Parhitosh Sharma
Mechanics Research Communications
This work proposes a dislocation density-based strain gradient J 2 plasticity framework that mode... more This work proposes a dislocation density-based strain gradient J 2 plasticity framework that models the strength contribution due to Geometrically Necessary Dislocations (GNDs) using a lower order, Taylor hardening backstress model. An anisotropy factor is introduced to phenomenologically represent the differential hardening between grains in this J 2 plasticity framework. An implicit numerical algorithm is implemented for the time integration of the finite deformation plasticity model. The framework is first used to predict directional hardening due to the GND-induced backstress during cyclic loading. Deformation contours are studied to understand the substructure attributes contributing to directional hardening. The framework is then used to predict the intrinsic, grain size-dependent strengthening of polygrain ensembles. Model predictions of simulations with different grain sizes are shown to agree with the Hall-Petch effect and also with Ashby's model of hardening due to GNDs in polygrain ensembles.
Mechanics Research Communications
This work proposes a dislocation density-based strain gradient J 2 plasticity framework that mode... more This work proposes a dislocation density-based strain gradient J 2 plasticity framework that models the strength contribution due to Geometrically Necessary Dislocations (GNDs) using a lower order, Taylor hardening backstress model. An anisotropy factor is introduced to phenomenologically represent the differential hardening between grains in this J 2 plasticity framework. An implicit numerical algorithm is implemented for the time integration of the finite deformation plasticity model. The framework is first used to predict directional hardening due to the GND-induced backstress during cyclic loading. Deformation contours are studied to understand the substructure attributes contributing to directional hardening. The framework is then used to predict the intrinsic, grain size-dependent strengthening of polygrain ensembles. Model predictions of simulations with different grain sizes are shown to agree with the Hall-Petch effect and also with Ashby's model of hardening due to GNDs in polygrain ensembles.