Crack initiation
This research is focused around using DAMASK, a simulation software, to analyze the fracture and failure behavior of a sample with specified dimension. The aim of this project is to observe how imparting a load through controlled displacement in a elliptically notched specimen with a given disorder ratio will effect the crack initiation and propagation behavior. The disorder ratio is a measure of how large fluctuations in the critical strain energy release rate are compared to the average value. Also, we observe the trend change from notched-based crack initiation to bulk-disorder crack nucleation in an effort to analyze the transition from brittle to quasi-brittle fracture through these precursors.
Machine Learning
Michael's research is focused on machine learning. Presently we're developing an algorithm to mimic the DIC protocol for obtaining stress-strain curves and creating data sets of these curves to quantify the degree of plasticity of various samples. The objective is to be able to recognize the load-reload history of a sample based on the algorithm. Python is heavily employed to create data sets and machine learning algorithms help us sort and manipulate the data sets in order to achieve our objective.
2D/3D Dislocation Dynamics
Hengxu's research is focused on the study of plasticity at small length scale through 2D/3D discrete dislocation dynamics (DDD) simulations. The focus includes mechanical properties, such as size effect, and statistics of the system.
Currently, Hengxu is working on and involved in the following studies
1. 2D/3D DDD simulations of nanoindentation
2. Obstacle aging in 2D DDD
3. Stress/strain control nano-pillar compression
4. Application of machine learning in plasticity (involved in)
SRD Particle under Shear:
Salehin's research is basically based on LAMMPS, a tool for Molecular Dynamics Simulation, and generate output file which can be visualized in VMD and finally generate movie of the whole phenomena. The goal is to visualize SRD particle flow under shear and calculate the viscocity of different mass value of SRD particles.
This research is focused around using DAMASK, a simulation software, to analyze the fracture and failure behavior of a sample with specified dimension. The aim of this project is to observe how imparting a load through controlled displacement in a elliptically notched specimen with a given disorder ratio will effect the crack initiation and propagation behavior. The disorder ratio is a measure of how large fluctuations in the critical strain energy release rate are compared to the average value. Also, we observe the trend change from notched-based crack initiation to bulk-disorder crack nucleation in an effort to analyze the transition from brittle to quasi-brittle fracture through these precursors.
Machine Learning
Michael's research is focused on machine learning. Presently we're developing an algorithm to mimic the DIC protocol for obtaining stress-strain curves and creating data sets of these curves to quantify the degree of plasticity of various samples. The objective is to be able to recognize the load-reload history of a sample based on the algorithm. Python is heavily employed to create data sets and machine learning algorithms help us sort and manipulate the data sets in order to achieve our objective.
2D/3D Dislocation Dynamics
Hengxu's research is focused on the study of plasticity at small length scale through 2D/3D discrete dislocation dynamics (DDD) simulations. The focus includes mechanical properties, such as size effect, and statistics of the system.
Currently, Hengxu is working on and involved in the following studies
1. 2D/3D DDD simulations of nanoindentation
2. Obstacle aging in 2D DDD
3. Stress/strain control nano-pillar compression
4. Application of machine learning in plasticity (involved in)
SRD Particle under Shear:
Salehin's research is basically based on LAMMPS, a tool for Molecular Dynamics Simulation, and generate output file which can be visualized in VMD and finally generate movie of the whole phenomena. The goal is to visualize SRD particle flow under shear and calculate the viscocity of different mass value of SRD particles.
No comments:
Post a Comment