Implementation of parallel processing on GPU for fluid flow simulation using Lattice Boltzmann method and Smoothed Profile method

Investigation of fluid-solid interaction has been studied as an introduction to simulate a wide range of engineering problems such as fluidized beds, sediment transportation and catalyst inks in fuel cells. An efficient method for performing such simulations is a combination of Lattice Boltzmann method (LBM) and Smoothed Profile Method (SPM). In addition, the operations in the SPM are local; it can be easily programmed for parallel processing. In this approach, the flow is computed on fixed Eulerian grids which are also used for the particles. Owing to the use of the same grids for simulation of fluid flow and particles, this method is highly efficient for purpose of parallel processing by means of GPU. In this study, a combination of Lattice Boltzmann method (LBM) and Smoothed Profile method has been implemented in parallel processing on GPU. For validation purpose, the fluid flow within a channel was investigated. Results suggest that computational time can be reduced up to 80 times by means of GPU.Then, drag force exerted on a sphere in fluid flow and the sedimentation of one sphere in a quiescent fluid were studied. Results show that performance of GPU can be increased up to 6.5 million fluid nods per second by using this method.