A5081412838- Elasticity and Material Modeling
- Cellular and Composite Structures
- Automotive and Human Injury Biomechanics
- EEG and Brain-Computer Interfaces
- Advanced Control Systems Optimization
- Manufacturing Process and Optimization
- Advanced Neuroimaging Techniques and Applications
- Elevator Systems and Control
- Gaze Tracking and Assistive Technology
- Machine Learning in Materials Science
- Neurological disorders and treatments
- Composite Material Mechanics
- Model Reduction and Neural Networks
- Scheduling and Optimization Algorithms
- Welding Techniques and Residual Stresses
- Additive Manufacturing Materials and Processes
Rutgers, The State University of New Jersey
2021-2024
Georgia Institute of Technology
2019
Abstract A novel finite element method (FEM) is developed to study mechanical response of axons embedded in extra cellular matrix (ECM) when subjected harmonic uniaxial stretch under purely non-affine kinematic boundary conditions. The proposed modeling approach combines hyper-elastic (such as Ogden model) and time/frequency domain viscoelastic constitutive models evaluate the effect parametrically varying oligodendrocyte-axon tethering at 50Hz. hybrid hyper-viscoelastic material (HVE) model...
Abstract Numerical simulations using non-linear hyper-elastic material models to describe interactions between brain white matter (axons and extra cellular matrix (ECM)) have enabled high-fidelity characterization of stress-strain response. In this paper, a novel finite element model (FEM) has been developed study mechanical response axons embedded in ECM when subjected tensile loads under purely non-affine kinematic boundary conditions. FEM leveraging Ogden is deployed understand impact...