scholarly journals Incompressible fluid simulation on CUDA using SPH method

2012 ◽  
Vol 12 (7) ◽  
Author(s):  
Artem Suravkin
2019 ◽  
Vol 6 (4) ◽  
pp. 529-544 ◽  
Author(s):  
Daniel Morikawa ◽  
Mitsuteru Asai ◽  
Nur’Ain Idris ◽  
Yusuke Imoto ◽  
Masaharu Isshiki

Author(s):  
JIAWEN WU ◽  
FENGQUAN ZHANG ◽  
XUKUN SHEN

In this paper, we present a method for fluid simulation based on smoothed particle hydrodynamic (SPH) with fast collision detection on boundaries on GPU. The major goal of our algorithm is to get a fast SPH simulation and rendering on GPU. Additionally, our algorithm has the following three features: At first, to make the SPH method GPU-friendly, we introduce a spatial hash method for neighbor search. After sorting the particles based on their grid index, neighbor search can be done quickly on GPU. Second, we propose a fast particle-boundary collision detection method. By precomputing the distance field of scene boundaries, collision detection's computing cost arrived as O(n), which is much faster than the traditional way. Third, we propose a pipeline with fine-detail surface reconstruction, and progressive photon mapping working on GPU. We experiment our algorithm on different situations and particle numbers of scenes, and find out that our method gets good results. Our experimental data shows that we can simulate 100K particles, and up to 1000K particles scene at a rate of approximately 2 times per second.


2014 ◽  
Vol 989-994 ◽  
pp. 1724-1727
Author(s):  
Xin Zhao

An improved SPH method for water fluid simulation was proposed in this paper. We used higher order splines to improve the stability, and two layers virtual particles to solve particle inconsistency problem near the boundary area. Due to the improvements paid more attention on details, we obtained more realistic and stalbe effect, which was different with previous works. Experimental results showed that our method was realistic, and could achieve real-time frame rate when particle amount was less than 10000.


2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Xiao Nie ◽  
Leiting Chen ◽  
Tao Xiang

We present a parallel framework for simulating incompressible fluids with predictive-corrective incompressible smoothed particle hydrodynamics (PCISPH) on the GPU in real time. To this end, we propose an efficient GPU streaming pipeline to map the entire computational task onto the GPU, fully exploiting the massive computational power of state-of-the-art GPUs. In PCISPH-based simulations, neighbor search is the major performance obstacle because this process is performed several times at each time step. To eliminate this bottleneck, an efficient parallel sorting method for this time-consuming step is introduced. Moreover, we discuss several optimization techniques including using fast on-chip shared memory to avoid global memory bandwidth limitations and thus further improve performance on modern GPU hardware. With our framework, the realism of real-time fluid simulation is significantly improved since our method enforces incompressibility constraint which is typically ignored due to efficiency reason in previous GPU-based SPH methods. The performance results illustrate that our approach can efficiently simulate realistic incompressible fluid in real time and results in a speed-up factor of up to 23 on a high-end NVIDIA GPU in comparison to single-threaded CPU-based implementation.


2014 ◽  
Vol 543-547 ◽  
pp. 1667-1670
Author(s):  
Zhong Xing Zhang ◽  
Peng Zhe Qiao ◽  
Tao Li ◽  
Tao Xiang

In this paper, we present an efficient approach based on Smoothed Particle Hydrodynamics (SPH) to simulate nearly incompressible fluids. The proposed method is an extension of the traditional SPH method designed for compressible fluids. We first introduce a new scheme for pressure evaluation to satisfy the incompressibility constraints. Then novel calculation methods for pressure force and viscosity force are discussed. Finally, the results demonstrate that our method is more capable of realistically simulating fluids with near-incompressibility than previous method.


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