Contacts

Research interests:

• Computational Quantum Mechanics
• Density Functional Theory
• Ab Initio Methods

Summary of work:

Improvements in the energy absorption capabilities of materials can be achieved through tailoring of alloying compositions to optimize micro and macro-mechanical properties. Although classical continuum mechanics methods can describe micro and macro-mechanical properties, these models cannot predict the influence of alloying in materials within crystalline structures on these properties. These predictions require the understanding of lower length-scale interactions of atoms, which is better described through quantum mechanics methods, such as density functional theory. Through the use of “ab initio” methods, which is a density functional theory-based method, simulations can be performed to understand the interactions of alloying atoms in compositions from a first principles perspective instead of a phenomenological manner. The goal of my research is to employ density functional theory to understand and predict the influence of alloying atoms within the crystal structure of bulk materials and determine the effects on microstructure and macro-mechanical properties.

Education:

• BASc, Punjab Technical University, India
• MASc, Thapar University, India

Research interests:

• Spectral Methods
• Crystal Plasticity
• Peridynamics
• Modeling Failure and Fracture of Materials
• Micromechanics and Homogenization
• Multi-scale Modeling
• CAD/CAM/CAE
• Design Automation and CNC Toolpath Generation

Summary of work:

Virtual fabrication is a key ingredient for increasing the competitiveness of the industry, by reducing the time from concept to market and by increasing quality and reliability of the final product. Nowadays, in automotive and aerospace industries, an important part of the virtual factory relies on the numerical simulations of aluminum parts using state-of-the-art crystal plasticity techniques. Better understanding of microstructure evolution of aluminum can significantly improve the accuracy of the numerical predictions.

To achieve this, the crystal plasticity model must capture the evolution of 3D microstructural features such as texture, grain shape and grain interactions with deformation. The goals of my research include development of an efficient spectral method based full-field crystal plasticity framework and development of in-house codes for bond-based and state-based Peri dynamic techniques.

Eventually creating a hierarchical multiscale framework (virtual laboratory) that can accurately model the effects of microstructure on fracture and crack propagation in the lab-scale components.

Jaspreet Nagra's Google Scholar

Education:

• BSC, Saint Petersburg State University, Russia
• MSC, Saint Petersburg State University, Russia
• PhD, University of Waterloo, Canada

Research interests:

• Crystal Plasticity
• Artificial Intelligence
• Material Modeling
• Multiphysical Dislocation Dynamics Models

Summary of work:

Discrete Dislocation Dynamics models provide a framework to advance the understanding of plasticity. Multiphysical phenomena are often present during plastic deformation.

Two particular examples are the electromechanical behavior of plastically deformed piezoelectric materials and the thermomechanical behavior of metals under high strain rate plastic deformation. Therefore, two new Discrete Dislocation Dynamics models were developed; dislocations are directly modeled as crystallographic line defects in an elastic continuum.

These models are based on the Extended Finite Element Method (XFEM), which is a versatile tool used to analyze discontinuities, singularities, localized deformations, and complex geometries. 

Currently, I am working on developing and implementing machine learning techniques for the crystal plasticity models.

Research interests

• Crystal plasticity large strain modelling
• Crashworthiness applications
• Texture stability
• Static recrystallization

Summary of work

Automotive companies use forming operations like stamping and extrusion for various car body and structural parts. Crystal plasticity simulations of these processes enables designers to study the effect of texture and stress-strain data on the final part. Some of these processes are carried out at higher temperatures and therefore the final texture and material properties are affected by other phenomenon.

These phenomenon such as recrystallization need to be considered to accurately predict the final texture. My work involves simulating large strain problems such as rolling at different temperatures and strain-rates while accounting for the texture and flow behavior. This involves using a crystal plasticity framework along with an in-house recrystallization code.