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Data‐driven projection method in fluid simulation
Author(s) -
Yang Cheng,
Yang Xubo,
Xiao Xiangyun
Publication year - 2016
Publication title -
computer animation and virtual worlds
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.225
H-Index - 49
eISSN - 1546-427X
pISSN - 1546-4261
DOI - 10.1002/cav.1695
Subject(s) - computer science , computation , projection (relational algebra) , grid , iterative method , algorithm , projection method , artificial neural network , resolution (logic) , computational science , mathematical optimization , artificial intelligence , dykstra's projection algorithm , geometry , mathematics
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.