Mathematics of Computation · 2015 · 37 citations · 26 references
Natural SciencesComputational EngineeringComputational Fluid DynamicsComputational MechanicsFluid DynamicsNumerical AlgorithmsNumerical AnalysisNumerical Methods For Differential EquationsNumerical StabilityTime IntegrationTime Integration SchemesAdvectionBuckley-leverett TheoryStability Of Numerical SchemesTime DiscretizationTime-stepping SchemesTotal Variation Diminishing SchemesTotal Variation MinimizationUpper Bound Computation
High-order spatial discretizations of hyperbolic PDEs are often designed to have strong stability properties, such as monotonicity. We study explicit multistep Runge–Kutta strong stability preserving (SSP) time integration methods for use with such discretizations. We prove an upper bound on the SSP coefficient of explicit multistep Runge–Kutta methods of order two and above. Numerical optimization is used to find optimized explicit methods of up to five steps, eight stages, and tenth order. These methods are tested on the linear advection and nonlinear Buckley-Leverett equations, and the results for the observed total variation diminishing and/or positivity preserving time-step are presented.
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A PDE-Based Fast Local Level Set Method
Danping Peng, Barry Merriman, Stanley Osher et al. · Journal of Computational Physics · 1999 · 1.2K citations