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Author:

Li, Matthew

Title:

using physics-informed generative adversarial networks to enhance multiphase fluid flow simulation

Area of Honors:

Computer Science

Keywords:

machine learning
deep learning
computational fluid dynamics
cfd
novel method
physics-informed neural network

File:

Download thesis_matthew_li.pdf

Thesis Supervisors:

Chris Mc Comb, Thesis Supervisor
Jesse Louis Barlow, Thesis Honors Advisor