Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/81684
Title: Turbulence Simulation by Adaptive Multi-Relaxation Lattice Boltzmann Modeling
Authors: Liu, Xiaopei
Pang, Wai-Man
Qin, Jing
Fu, Chi-Wing
Keywords: Turbulence simulation
lattice Boltzmann models
Issue Date: 2014
Source: Liu, X., Pang, W.-M., Qin, J., & Fu, C.-W. (2014). Turbulence Simulation by Adaptive Multi-Relaxation Lattice Boltzmann Modeling. IEEE Transactions on Visualization and Computer Graphics, 20(2), 289-302.
Series/Report no.: IEEE Transactions on Visualization and Computer Graphics
Abstract: 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.
URI: https://hdl.handle.net/10356/81684
http://hdl.handle.net/10220/40928
ISSN: 1077-2626
DOI: 10.1109/TVCG.2012.303
Schools: School of Computer Engineering 
Rights: © 2014 IEEE.
Fulltext Permission: none
Fulltext Availability: No Fulltext
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