Seid Koric, Diab Abueidda, and Qyue Le have published a paper that is among the top 10% of the most downloaded articles from Wiley's International Journal for Numerical Methods in Engineering.
Written by
Seid Koric, MechSE Research Associate Professor and NSCA Technical Associate Director
MechSE Research Associate Professor and Technical Associate Director at NCSA Seid Koric continues to lead influential work. Along with MechSE alumnus and NCSA Research Scientist Diab Abueidda (PhD ME 2019), and graduate student Qiyue Le, they have published a paper that is among the top 10% of the most downloaded articles from Wiley's International Journal for Numerical Methods in Engineering.
Their 2021 paper, “Meshless Physics-Informed Deep Learning Method for Three-Dimensional Solid Mechanics,” dives into their work with the deep collocation method and how it is a potentially promising standalone technique to solve partial differential equations.
The researchers have, for the first time, applied physics-informed neural networks (a sophisticated AI/machine learning technique) to nonlinear computational mechanics in a full 3D domain.