Project 1: Better algorithms for complex differential equations
Project abstract:
Mathematics guide the design of improved algorithms for solving complex differential equations on modern computers. By decomposing complex structures into simpler blocks, the finite element method (FEM) is able to numerically solve partial differential equations on complicated geometries. The research of our group is aimed at developing more accurate and more efficient types of FEM through mathematical insights.
For Summer 2019, we are offering an undergraduate research project in collaboration with a local start-up company Microstructure Engineering. The company’s goal is to develop affordable computational tools for predicting microstructural evolution and its effect on the properties of metals. The student will learn about field dislocation models, conduct parameter studies, and catalog results obtained using a certain type of FEM. The student will be introduced to High Performance Computing (HPC) and will be provided access to a local HPC cluster through membership in the Portland Institute for Computational Science (PICS).
Keywords:
- Computational Mechanics
- Finite Elements
- Plastic Distortion
Faculty Mentor:
Jay Gopalakrishnan http://web.pdx.edu/~gjay/
Department:
Mathematics and Statistics
Community Partner(s):
Microstructure Engineering, Portland OR (owned by entrepreneur Dr. Saurabh Puri)
Microstructure Engineering, Portland OR (owned by entrepreneur Dr. Saurabh Puri)
Tools to be used:
Python 3, SLURM
Python 3, SLURM
Involves teamwork:
Yes. The student will be expected to work closely with a PSU PhD student, a PSU faculty, and a company expert.
Yes. The student will be expected to work closely with a PSU PhD student, a PSU faculty, and a company expert.