Fluids in computer generated imagery can add an impressive amount of realism to a scene, but are particularly time-consuming to simulate. In an attempt to run ﬂuid simulations in real-time, recent eﬀorts have attempted to simulate ﬂuids by using machine learning techniques to approximate the movement of ﬂuids. We explore utilizing machine learning to simulate ﬂuids while also integrating the Fluid-Implicit-Particle (FLIP) simulation method into machine learning ﬂuid simulation approaches.
College and Department
Physical and Mathematical Sciences; Computer Science
BYU ScholarsArchive Citation
Pack, Javid Kennon, "Toward Real-Time FLIP Fluid Simulation through Machine Learning Approximations" (2018). Theses and Dissertations. 8828.
ﬂuid simulation, machine learning, water