Data-driven projection method in fluid simulation

• Published in: Computer animation and virtual worlds Vol. 27; no. 3-4; pp. 415 - 424
• Main Authors: Yang, Cheng, Yang, Xubo, Xiao, Xiangyun
• Format: Journal Article
• Language: English
• Published: Chichester Blackwell Publishing Ltd 01.05.2016; Wiley Subscription Services, Inc
• Subjects: artificial neural network; Computation; Computational fluid dynamics; Computer simulation; data-driven; Fluids; grid-based fluid simulation; Mathematical analysis; Mathematical models; Navier-Stokes equations; Projection; projection step
• ISSN: 1546-4261; 1546-427X
• DOI: 10.1002/cav.1695

Physically based fluid simulation requires much time in numerical calculation to solve Navier–Stokes equations. Especially in grid‐based fluid simulation, because of iterative computation, the projection step is much more time‐consuming than other steps. In this paper, we propose a novel data‐driven projection method using an artificial neural network to avoid iterative computation. Once the grid resolution is decided, our data‐driven method could obtain projection results in relatively constant time per grid cell, which is independent of scene complexity. Experimental results demonstrated that our data‐driven method drastically speeded up the computation in the projection step. With the growth of grid resolution, the speed‐up would increase strikingly. In addition, our method is still applicable in different fluid scenes with some alterations, when computational cost is more important than physical accuracy. Copyright © 2016 John Wiley & Sons, Ltd. The simulation results using our data‐driven projection method. It could speed up more than 10 times than preconditioned conjugate method.