Real Time Fluid Simulation Framework Based on DirectCompute

Abstract

Abstract: A real time fluid simulation framework based on DirectCompute acceleration was proposed to solve problems of low simulation efficiency that caused by the increasing fluid particle size and long processing time that caused by the complex solid-liquid boundary. In the simulation, a grid local collision detection method was adopted to speed up the search for the solid-liquid boundary. Fluid calculation, collision detection and surface reconstruction were computed parallel in the GPU with DirectCompute technology to accelerate the SPH fluid simulation. It could optimize the storage structure of fluid simulation, and save the storage space. Experimental results show that the framework can effectively improve the fluid simulation speed with more complex static scene, and can show the details of the fluid spray.

Key words: fluid simulation, smoothed particle hydrodynamics, collision detection, GPU acceleration

CLC Number:

TP391.9

Liu Lu, Liu Zhen, He Gaoqi, Chen Tian, Liu Tingting, Liu Cuijuan. Real Time Fluid Simulation Framework Based on DirectCompute[J]. Journal of System Simulation, 2016, 28(10): 2467-2475.

References 18

[1]	柳有权, 王章野, 朱鉴, 等. 基于物理的流体动画加速技术的研究进展[J]. 计算机辅助设计与图形学学报, 2013, 25(3): 312-321.
[2]	谭捷, 杨旭波. 基于物理的流体动画综述[J]. 中国科学(F辑:信息科学), 2009, 39(5): 499-514.
[3]	Müller M, Charypar D, Gross M.Particle based fluid simulation for interactive applications [C]// Proceedings of EUROGRAPHICS/ACMSIGGRAPH Symposium on Computer Animation. San Diego, USA: ACM Press, 2003: 154-159.
[4]	Green S. Particle simulation using cuda [CP/OL]. NVIDIA Whitepaper Packaged with CUDA ToolKit, Nvidia Coporation, 2010. http://developer.nvidia.com/cuda-downloads.
[5]	Øystein E Krog, Elster A C.Fast GPU-based fluid simulations using SPH[C]// Applied Parallel and Scientific Computing-International Conference, Iceland: Berlin Heidelberg, 2010: 98-109.
[6]	Junior J R S, Joselli M, Zamith M, et al. An architecture for real time fluid simulation using multiple GPUs[C]// SBC-Proceedings of SBGames. Brazil: SBGames, 2012: 93-100.
[7]	周煜坤, 陈清华, 余潇. 基于CUDA的大规模流体实时模拟[J]. 计算机应用与软件, 2015, 32(1): 143-147.
[8]	刘良平, 刘箴, 方昊, 等. 基于GPU的三维场景表面流体碰撞检测方法研究[J]. 系统仿真学报, 2015, 27(10): 2439-2445,2452.
[9]	Monaghan J J.Simulating Free Surface Flows with SPH[J]. Journal of Computational Physics (S0021-9991), 1994, 110(2): 399-406.
[10]	Liu G R, Liu M B, Li S.Smoothed Particle Hydrodynamics-A Mesh-Free Particle Method[J]. Computational Mechanics (S0178-7675), 2004, 33(6): 491-491.
[11]	刘旭, 班晓娟, 杨鸣远, 等. 一种SPH流体仿真边界校正方法[J]. 图学学报, 2015, 36(3): 462-467.
[12]	张桂娟, 朱登明, 邱显杰, 等. 一种面向流体仿真的场景处理方法[J]. 计算机辅助设计与图形学学报, 2010, 22(8): 1360-1365.
[13]	Lorensen W E, Cline H E.Marching cubes: a high resolution 3D surface construction algorithm[J]. SIGGRAPH Comput Graph (S0097-8930), 1987, 21(4): 163-169.
[14]	Zhu Y, Bridson R.Animating sand as fluid[J]. Acm Transactions on Graphics (S0730-0301), 2005, 24(3): 965-972.
[15]	Solenthaler B, Schläfli J, Pajarola R.A unified particle model for fluid-solid interactions.[J]. Computer Animation & Virtual Worlds (S1546-4261), 2007, 18(1): 69-82.
[16]	Yu J, Turk G.Reconstructing surfaces of particle-based fluids using anisotropic kernels[J]. Proc. of the Acm Siggraph/Eurographics Symp. on Comp. Anim. Eurographics Association (S0730-0301), 2010, 32(1): 217-225.
[17]	刘世光, 王泽, 彭群生. 基于物理的浑浊水体的光照模拟[J]. 计算机辅助设计与图形学学报, 2011, 23(1): 40-45.
[18]	Möller T, Trumbore B.Fast, minimum storage ray/triangle intersection[C]// ACM SIGGRAPH 2005 Courses. USA: ACM, 2005: 7.