L2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_2$$\end{document} Stability of Explicit Runge–Kutta Schemes

Explicit Runge–Kutta methods are standard tools in the numerical solution of ordinary differential equations (ODEs). Applying the method of lines to partial differential equations, spatial semidiscretisations result in large systems of ODEs that are solved subsequently. However, stability investigations of high-order methods for transport equations are often conducted only in the semidiscrete setting. Here, strong-stability of semidiscretisations for linear transport equations, resulting in ODEs with semibounded operators, are investigated. For the first time, it is proved that the fourth-order, ten-stage SSP method of Ketcheson (SIAM J Sci Comput 30(4):2113–2136, 2008) is strongly stable for general semibounded operators. Additionally, insights into fourth-order methods with fewer stages are presented.

[1]  Ernst Hairer,et al.  Solving Ordinary Differential Equations I: Nonstiff Problems , 2009 .

[2]  David I. Ketcheson,et al.  Highly Efficient Strong Stability-Preserving Runge-Kutta Methods with Low-Storage Implementations , 2008, SIAM J. Sci. Comput..

[3]  Magnus Svärd,et al.  Review of summation-by-parts schemes for initial-boundary-value problems , 2013, J. Comput. Phys..

[4]  Philipp Öffner,et al.  Summation-by-parts operators for correction procedure via reconstruction , 2015, J. Comput. Phys..

[5]  J. Butcher Numerical methods for ordinary differential equations , 2003 .

[6]  Antony Jameson,et al.  A New Class of High-Order Energy Stable Flux Reconstruction Schemes , 2011, J. Sci. Comput..

[7]  Inmaculada Higueras,et al.  Monotonicity for Runge–Kutta Methods: Inner Product Norms , 2005, J. Sci. Comput..

[8]  Hyunjoong Kim,et al.  Functional Analysis I , 2017 .

[9]  David A. Kopriva,et al.  An Assessment of the Efficiency of Nodal Discontinuous Galerkin Spectral Element Methods , 2013 .

[10]  Arieh Iserles,et al.  A First Course in the Numerical Analysis of Differential Equations: The diffusion equation , 2008 .

[11]  Chi-Wang Shu,et al.  Stability of the fourth order Runge–Kutta method for time-dependent partial differential equations , 2017 .

[12]  D. Whittaker,et al.  A Course in Functional Analysis , 1991, The Mathematical Gazette.

[13]  Steven Roman Advanced Linear Algebra , 1992 .

[14]  E. Hairer,et al.  Geometric Numerical Integration: Structure Preserving Algorithms for Ordinary Differential Equations , 2004 .

[15]  David C. Del Rey Fernández,et al.  Review of summation-by-parts operators with simultaneous approximation terms for the numerical solution of partial differential equations , 2014 .

[16]  Freddie D. Witherden,et al.  An extended range of stable-symmetric-conservative Flux Reconstruction correction functions , 2015 .

[17]  Qing Nie,et al.  DifferentialEquations.jl – A Performant and Feature-Rich Ecosystem for Solving Differential Equations in Julia , 2017, Journal of Open Research Software.

[18]  Gregor Gassner,et al.  An Energy Stable Discontinuous Galerkin Spectral Element Discretization for Variable Coefficient Advection Problems , 2014, SIAM J. Sci. Comput..

[19]  Eitan Tadmor,et al.  From Semidiscrete to Fully Discrete: Stability of Runge-Kutta Schemes by The Energy Method , 1998, SIAM Rev..

[20]  Alan Edelman,et al.  Julia: A Fresh Approach to Numerical Computing , 2014, SIAM Rev..

[21]  David A. Kopriva,et al.  Implementing Spectral Methods for Partial Differential Equations: Algorithms for Scientists and Engineers , 2009 .

[22]  Chi-Wang Shu,et al.  Total variation diminishing Runge-Kutta schemes , 1998, Math. Comput..

[23]  David I. Ketcheson,et al.  Strong stability preserving runge-kutta and multistep time discretizations , 2011 .

[24]  G. J. Cooper Stability of Runge-Kutta Methods for Trajectory Problems , 1987 .

[25]  David A. Kopriva,et al.  Implementing Spectral Methods for Partial Differential Equations , 2009 .