1. using physics-informed generative adversarial networks to enhance multiphase fluid flow simulation Open Access Author: Li, Matthew Title: using physics-informed generative adversarial networks to enhance multiphase fluid flow simulation Area of Honors: Computer Science Keywords: machine learningdeep learningcomputational fluid dynamicscfdnovel methodphysics-informed neural network File: Download thesis_matthew_li.pdf Thesis Supervisors: Chris Mc Comb, Thesis SupervisorJesse Louis Barlow, Thesis Honors Advisor