A Brief Overview of Crystal Plasticity Approach for Computational Materials Modeling

2020 ◽  
pp. 61-69
Author(s):  
Lakhwinder Singh ◽  
Sanjay Vohra ◽  
Manu Sharma
Keyword(s):  
Crystal Plasticity ◽  
Materials Modeling ◽  
Computational Materials

scholarly journals Studying Grain Boundary Strengthening by Dislocation-Based Strain Gradient Crystal Plasticity Coupled with a Multi-Phase-Field Model

2019 ◽  
Author(s):  
Waseem Amin ◽  
Muhammad Adil Ali ◽  
Napat Vajragupta ◽  
Alexander Hartmaier
Keyword(s):  
Plastic Deformation ◽  
Grain Size ◽  
Microstructural Evolution ◽  
Crystal Plasticity ◽  
Phase Field ◽  
Strain Gradient ◽  
Mechanical Response ◽  
Functional Dependence ◽  
Initial State ◽  
Computational Materials

One ambitious objective of Integrated Computational Materials Engineering (ICME) is to shorten the materials development cycle by using computational materials simulation techniques at different length scales. In this regard, the most important aspects are the prediction of the microstructural evolution during material processing and the understanding of the contributions of microstructural features to the mechanical response of the materials. One possible solution to such a challenge is to apply the Phase Field (PF) method because it can predict the microstructural evolution under the influence of different internal or external stimuli, including deformation. To accomplish this, it is necessary to take into account plasticity or, specifically, non-homogeneous plastic deformation, which is particularly important for investigating the size effects in materials emerging at the micron length scale. In this work, we present quasi-2D simulations of plastic deformation in a face centred cubic system in a finite strain formulation. Our model consists of dislocation-based strain gradient crystal plasticity implemented into a PF code. We apply this model to study the influence of grain size on the mechanical behavior of polycrystals, which includes dislocation storage and annihilation. Furthermore, the initial state of the material before deformation is also considered. The results show that a dislocation-based strain gradient crystal plasticity model can capture the Hall-Petch effect in many aspects. The model reproduced the correct functional dependence of the flow stress of the polycrystal on grain size without assigning any special properties to the grain boundaries. However, the predicted Hall-Petch coefficients are significantly smaller than those found typically in experiments. In any case, we found a good qualitative agreement between our findings and experimental results.

scholarly journals Studying Grain Boundary Strengthening by Dislocation-Based Strain Gradient Crystal Plasticity Coupled with a Multi-Phase-Field Model

Materials ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 2977 ◽  
Author(s):  
Waseem Amin ◽  
Muhammad Adil Ali ◽  
Napat Vajragupta ◽  
Alexander Hartmaier
Keyword(s):  
Plastic Deformation ◽  
Grain Size ◽  
Microstructural Evolution ◽  
Crystal Plasticity ◽  
Phase Field ◽  
Strain Gradient ◽  
Mechanical Response ◽  
Functional Dependence ◽  
Initial State ◽  
Computational Materials

One ambitious objective of Integrated Computational Materials Engineering (ICME) is to shorten the materials development cycle by using computational materials simulation techniques at different length scales. In this regard, the most important aspects are the prediction of the microstructural evolution during material processing and the understanding of the contributions of microstructural features to the mechanical response of the materials. One possible solution to such a challenge is to apply the Phase Field (PF) method because it can predict the microstructural evolution under the influence of different internal or external stimuli, including deformation. To accomplish this, it is necessary to take into account plasticity or, specifically, non-homogeneous plastic deformation, which is particularly important for investigating the size effects in materials emerging at the micron length scale. In this work, we present quasi-2D simulations of plastic deformation in a face centred cubic system using a finite strain formulation. Our model consists of dislocation-based strain gradient crystal plasticity implemented into a PF code. We apply this model to study the influence of grain size on the mechanical behavior of polycrystals, which includes dislocation storage and annihilation. Furthermore, the initial state of the material before deformation is also considered. The results show that a dislocation-based strain gradient crystal plasticity model can capture the Hall-Petch effect in many aspects. The model reproduced the correct functional dependence of the flow stress of the polycrystal on grain size without assigning any special properties to the grain boundaries. However, the predicted Hall-Petch coefficients are significantly smaller than those found typically in experiments. In any case, we found a good qualitative agreement between our findings and experimental results.

scholarly journals Incorporating physically-based microstructures in materials modeling: Bridging phase field and crystal plasticity frameworks

2016 ◽  
Vol 24 (4) ◽  
pp. 045016 ◽  
Author(s):  
Hojun Lim ◽  
Fadi Abdeljawad ◽  
Steven J Owen ◽  
Byron W Hanks ◽  
James W Foulk ◽  
...  
Keyword(s):  
Crystal Plasticity ◽  
Phase Field ◽  
Materials Modeling ◽  
Physically Based

scholarly journals Hexahedral Mesh Generation for Computational Materials Modeling

2017 ◽  
Vol 203 ◽  
pp. 167-179 ◽  
Author(s):  
Steven J. Owen ◽  
Judith A. Brown ◽  
Corey D. Ernst ◽  
Hojun Lim ◽  
Kevin N. Long
Keyword(s):  
Mesh Generation ◽  
Hexahedral Mesh ◽  
Materials Modeling ◽  
Hexahedral Mesh Generation ◽  
Computational Materials

Computational Materials Design

2016 ◽  
pp. 1-12
Author(s):  
Shubhabrata Datta ◽  
Bishnupada Roy ◽  
J. Paulo Davim
Keyword(s):  
Mathematical Models ◽  
Materials Design ◽  
Optimization Techniques ◽  
Data Driven ◽  
Scientific Theories ◽  
Length Scales ◽  
Materials Modeling ◽  
Computational Materials Design ◽  
Computational Materials

The chapter primarily deals with brief description of different methods of materials modeling which utilizes the scientific theories in different length scales. It also gives an account of the available tools for situations where data driven models are required. Utilization of imprecise knowledge of a materials system for developing mathematical models is also discussed. A brief account of the use of optimization techniques for designing materials is discussed here.

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