Abstract

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.

Degree

College and Department

Physical and Mathematical Sciences; Computer Science

Rights

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