Spatio-temporal extrapolation for fluid animation

Abstract

a) Coarse Grid Simulation 160 × 128 × 64 (b) Fine Grid Simulation 320 × 256 × 128 (c) Spatio-temporal Extrapolation 320 × 256 × 128 Figure 1: Our spatio-temporal extrapolation method can enhance the fluid simulation result by applying a black-box grid-based solver on two grid scales and combining the solutions together at each time step. The extrapolation technique produces better motion quality (c) than those from directly applying the solver on the two scales separately (a) and (b). AbstractWe introduce a novel spatio-temporal extrapolation technique for fluid simulation designed to improve the results without using higher resolution simulation grids. In general, there are rigid demands associated with pushing fluid animations to higher resolutions given limited computational capabilities. This results in tradeoffs between implementing high-order numerical methods and increasing the resolution of the simulation in space and time. For 3D problems, such challenges rapidly become cost-ineffective. The extrapolation method we present improves the flow features without using higher resolution simulation grids. In this paper, we show that simulation results from our extrapolation are comparable to those from higher resolution simulations. In addition, our method differs from high-order numerical methods because it does not depend on the equation or specific solver. We demonstrate that it is easy to implement and can significantly improve the fluid animation results.

Data-driven synthesis of smoke flows with CNN-based feature descriptors

“…However, the amount of representable details is still inherently limited by the chosen grid resolutions for these algorithms. Hybrid methods have likewise been proposed to couple Eulerian simulations with Lagrangian vorticity simulations [Golas et al 2012], while other researchers have proposed extrapolations of ow motions [Zhang and Ma 2013]. Our approach instead o -loads the computational burden to produce small-scale details to a pre-computation stage.…”

Physical‐based spatio‐temporal resolution enhancement of scalar data for fluid visualization

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