A Fast Explicit Operator Splitting Method for Passive Scalar Advection

The dispersal and mixing of scalar quantities such as concentrations or thermal energy are often modeled by advection-diffusion equations. Such problems arise in a wide variety of engineering, ecological and geophysical applications. In these situations a quantity such as chemical or pollutant concentration or temperature variation diffuses while being transported by the governing flow. In the passive scalar case, this flow prescribed and unaffected by the scalar. Both steady laminar and complex (chaotic, turbulent or random) time-dependent flows are of interest and such systems naturally lead to questions about the effectiveness of the stirring to disperse and mix the scalar. The development of reliable numerical methods for advection-diffusion equations is crucial for understanding their properties, both physical and mathematical. In this paper, we extend a fast explicit operator splitting method, recently proposed in (A. Chertock, A. Kurganov, G. Petrova, Int. J. Numer. Methods Fluids 59:309–332, 2009), for solving deterministic convection-diffusion equations, to the problems with random velocity fields and singular source terms. A superb performance of the method is demonstrated on several two-dimensional examples.

[1]  Chi-Wang Shu,et al.  High order time discretization methods with the strong stability property , 2001 .

[2]  Charles R. Doering,et al.  Mixing effectiveness depends on the source–sink structure: simulation results , 2008, 0804.2805.

[3]  William R. Young,et al.  A bound on scalar variance for the advection–diffusion equation , 2006, Journal of Fluid Mechanics.

[4]  G. Marchuk Splitting and alternating direction methods , 1990 .

[5]  J. Verwer,et al.  Numerical solution of time-dependent advection-diffusion-reaction equations , 2003 .

[6]  A. Medovikov High order explicit methods for parabolic equations , 1998 .

[7]  Alexander Kurganov,et al.  Semidiscrete Central-Upwind Schemes for Hyperbolic Conservation Laws and Hamilton-Jacobi Equations , 2001, SIAM J. Sci. Comput..

[8]  Jean-Luc Thiffeault,et al.  Multiscale mixing efficiencies for steady sources. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[9]  Andreas Meister,et al.  Central Schemes and Systems of Balance Laws , 2002 .

[10]  Alexander Kurganov,et al.  On Splitting-Based Numerical Methods for Convection-Diffusion Equations , 2008 .

[11]  A. Kurganov,et al.  On the Reduction of Numerical Dissipation in Central-Upwind Schemes , 2006 .

[12]  I. T. Drummond Path-integral methods for turbulent diffusion , 1982 .

[13]  G. Strang On the Construction and Comparison of Difference Schemes , 1968 .

[14]  K. P.,et al.  HIGH RESOLUTION SCHEMES USING FLUX LIMITERS FOR HYPERBOLIC CONSERVATION LAWS * , 2012 .

[15]  E. Tadmor,et al.  New High-Resolution Central Schemes for Nonlinear Conservation Laws and Convection—Diffusion Equations , 2000 .

[16]  Eitan Tadmor,et al.  Solution of two‐dimensional Riemann problems for gas dynamics without Riemann problem solvers , 2002 .

[17]  Alexander Kurganov,et al.  Fast explicit operator splitting method for convection–diffusion equations , 2009 .

[18]  Alexander Kurganov,et al.  Propagation of Diffusing Pollutant by a Hybrid Eulerian–Lagrangian Method , 2008 .

[19]  Charles R. Doering,et al.  Stirring up trouble: Multi-scale mixing measures for steady scalar sources , 2007 .

[20]  D. Kröner Numerical Schemes for Conservation Laws , 1997 .

[21]  Serge Alinhac,et al.  Hyperbolic Partial Differential Equations , 2009 .

[22]  E. Tadmor,et al.  Hyperbolic Problems: Theory, Numerics, Applications , 2003 .

[23]  A. Majda,et al.  SIMPLIFIED MODELS FOR TURBULENT DIFFUSION : THEORY, NUMERICAL MODELLING, AND PHYSICAL PHENOMENA , 1999 .

[24]  Chi-Wang Shu,et al.  Strong Stability-Preserving High-Order Time Discretization Methods , 2001, SIAM Rev..

[25]  Knut-Andreas Lie,et al.  On the Artificial Compression Method for Second-Order Nonoscillatory Central Difference Schemes for Systems of Conservation Laws , 2002, SIAM J. Sci. Comput..

[26]  R. LeVeque Finite Volume Methods for Hyperbolic Problems: Characteristics and Riemann Problems for Linear Hyperbolic Equations , 2002 .

[27]  E. Tadmor,et al.  Non-oscillatory central differencing for hyperbolic conservation laws , 1990 .

[28]  H. Yoshida Construction of higher order symplectic integrators , 1990 .

[29]  Bengt Fornberg,et al.  A split step approach for the 3-D Maxwell's equations , 2003 .

[30]  Alexander Kurganov,et al.  Fast Explicit Operator Splitting Method . Application to the Polymer System , 2006 .

[31]  P. Raviart,et al.  Numerical Approximation of Hyperbolic Systems of Conservation Laws , 1996, Applied Mathematical Sciences.

[32]  J. Craggs Applied Mathematical Sciences , 1973 .

[33]  Centro internazionale matematico estivo. Session,et al.  Advanced Numerical Approximation of Nonlinear Hyperbolic Equations , 1998 .

[34]  Gabriella Puppo,et al.  Numerical methods for balance laws , 2009 .

[35]  Vittorio Romano,et al.  Central schemes for systems of balance laws , 1999 .