Issue No. 02 - Feb. (2014 vol. 20)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2012.303
Xiaopei Liu , Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore, Singapore
Wai-Man Pang , Caritas Inst. of Higher Educ., Hong Kong, China
Jing Qin , Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Hong Kong, China
Chi-Wing Fu , Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore, Singapore
This paper presents a novel approach to simulating turbulent flows by developing an adaptive multirelaxation scheme in the framework of lattice Boltzmann equation (LBE). Existing LBE methods in graphics simulations are usually insufficient for turbulent flows since the collision term disturbs the underlying stability and accuracy. We adopt LBE with the multiple relaxation time (MRT) collision model (MRT-LBE), and address this issue by enhancing the collision-term modeling. First, we employ renormalization group analysis and formulate a new turbulence model with an adaptive correction method to compute more appropriate eddy viscosities on a uniform lattice structure. Efficient algebraic calculations are retained with small-scale turbulence details while maintaining the system stability. Second, we note that for MRT-LBE, predicting single eddy viscosity per lattice node may still result in instability. Hence, we simultaneously predict multiple eddy viscosities for stress-tensor-related elements, thereby asynchronously computing multiple relaxation parameters to further enhance the MRT-LBE stability. With these two new strategies, turbulent flows can be simulated with finer visual details even on coarse grid configurations. We demonstrate our results by simulating and visualizing various turbulent flows, particularly with smoke animations, where stable turbulent flows with high Reynolds numbers can be faithfully produced.
Computational modeling, Mathematical model, Viscosity, Numerical models, Adaptation models, Lattice Boltzmann methods
Xiaopei Liu, Wai-Man Pang, Jing Qin and Chi-Wing Fu, "Turbulence Simulation by Adaptive Multi-Relaxation Lattice Boltzmann Modeling," in IEEE Transactions on Visualization & Computer Graphics, vol. 20, no. 2, pp. 289-302, 2014.