In this paper,a simplified lattice Boltzmann method(SLBM)without evolution of the distribution function is developed for simulating incompressible viscous flows.This method is developed from the application of fractio...In this paper,a simplified lattice Boltzmann method(SLBM)without evolution of the distribution function is developed for simulating incompressible viscous flows.This method is developed from the application of fractional step technique to the macroscopic Navier-Stokes(N-S)equations recovered from lattice Boltzmann equation by using Chapman-Enskog expansion analysis.In SLBM,the equilibrium distribution function is calculated from the macroscopic variables,while the non-equilibrium distribution function is simply evaluated from the difference of two equilibrium distribution functions.Therefore,SLBM tracks the evolution of the macroscopic variables rather than the distribution function.As a result,lower virtual memories are required and physical boundary conditions could be directly implemented.Through numerical test at high Reynolds number,the method shows very nice performance in numerical stability.An accuracy test for the 2D Taylor-Green flow shows that SLBM has the second-order of accuracy in space.More benchmark tests,including the Couette flow,the Poiseuille flow as well as the 2D lid-driven cavity flow,are conducted to further validate the present method;and the simulation results are in good agreement with available data in literatures.展开更多
文摘In this paper,a simplified lattice Boltzmann method(SLBM)without evolution of the distribution function is developed for simulating incompressible viscous flows.This method is developed from the application of fractional step technique to the macroscopic Navier-Stokes(N-S)equations recovered from lattice Boltzmann equation by using Chapman-Enskog expansion analysis.In SLBM,the equilibrium distribution function is calculated from the macroscopic variables,while the non-equilibrium distribution function is simply evaluated from the difference of two equilibrium distribution functions.Therefore,SLBM tracks the evolution of the macroscopic variables rather than the distribution function.As a result,lower virtual memories are required and physical boundary conditions could be directly implemented.Through numerical test at high Reynolds number,the method shows very nice performance in numerical stability.An accuracy test for the 2D Taylor-Green flow shows that SLBM has the second-order of accuracy in space.More benchmark tests,including the Couette flow,the Poiseuille flow as well as the 2D lid-driven cavity flow,are conducted to further validate the present method;and the simulation results are in good agreement with available data in literatures.
