Implicit and Implicit–Explicit Strong Stability Preserving Runge–Kutta Methods with High Linear Order

Strong stability preserving (SSP) time discretizations preserve the monotonicity properties satisfied by the spatial discretization when coupled with the first order forward Euler, under a certain time-step restriction. The search for high order strong stability preserving time-stepping methods with high order and large allowable time-step has been an active area of research. It is known that implicit SSP Runge–Kutta methods exist only up to sixth order; however, if we restrict ourselves to solving only linear autonomous problems, the order conditions simplify and we can find implicit SSP Runge–Kutta methods of any linear order. In the current work we find implicit SSP Runge–Kutta methods with high linear order \(p_{lin} \le 9\) and nonlinear orders \(p=2,3,4\), that are optimal in terms of allowable SSP time-step. Next, we formulate a novel optimization problem for implicit–explicit (IMEX) SSP Runge–Kutta methods and find optimized IMEX SSP Runge–Kutta pairs that have high linear order \(p_{lin} \le 7\) and nonlinear orders up to \(p=4\). We also find implicit methods with large linear stability regions that pair with known explicit SSP Runge–Kutta methods. These methods are then tested on sample problems to demonstrate the sharpness of the SSP coefficient and the typical behavior of these methods on test problems.     

Strong Stability Preserving General Linear Methods with Runge–Kutta Stability

We investigate strong stability preserving (SSP) general linear methods (GLMs) for systems of ordinary differential equations. Such methods are obtained by the solution of the minimization problems with nonlinear inequality constrains, corresponding to the SSP property of these methods, and equality constrains, corresponding to order and stage order conditions. These minimization problems were solved by the sequential quadratic programming algorithm implemented in MATLAB\(^{\circledR }\) subroutine fmincon.m starting with many random guesses. Examples of transformed SSP GLMs of order \(p = 1, 2, 3\), and 4, and stage order \(q = p\) have been determined, and suitable starting and finishing procedures have been constructed. The numerical experiments performed on a set of test problems have shown that transformed SSP GLMs constructed in this paper are more accurate than transformed SSP DIMSIMs and SSP Runge–Kutta methods of the same order.     

Dense Output for Strong Stability Preserving Runge–Kutta Methods

We investigate dense output formulae (also known as continuous extensions) for strong stability preserving (SSP) Runge–Kutta methods. We require that the dense output formula also possess the SSP property, ideally under the same step-size restriction as the method itself. A general recipe for first-order SSP dense output formulae for SSP methods is given, and second-order dense output formulae for several optimal SSP methods are developed. It is shown that SSP dense output formulae of order three and higher do not exist, and that in any method possessing a second-order SSP dense output, the coefficient matrix A has a zero row.     

Optimal Strong-Stability-Preserving Runge–Kutta Time Discretizations for Discontinuous Galerkin Methods

Discontinuous Galerkin (DG) spatial discretizations are often used in a method-of-lines approach with explicit strong-stability-preserving (SSP) Runge–Kutta (RK) time steppers for the numerical solution of hyperbolic conservation laws. The time steps that are employed in this type of approach must satisfy Courant–Friedrichs–Lewy stability constraints that are dependent on both the region of absolute stability and the SSP coefficient of the RK method. While existing SSPRK methods have been optimized with respect to the latter, it is in fact the former that gives rise to stricter constraints on the time step in the case of RKDG stability. Therefore, in this work, we present the development of new “DG-optimized” SSPRK methods with stability regions that have been specifically designed to maximize the stable time step size for RKDG methods of a given order in one space dimension. These new methods represent the best available RKDG methods in terms of computational efficiency, with significant improvements over methods using existing SSPRK time steppers that have been optimized with respect to SSP coefficients. Second-, third-, and fourth-order methods with up to eight stages are presented, and their stability properties are verified through application to numerical test cases.     

Strong Stability for Runge–Kutta Schemes on a Class of Nonlinear Problems

In this paper we consider Strong Stability Preserving (SSP) properties for explicit Runge–Kutta (RK) methods applied to a class of nonlinear ordinary differential equations. We define new modified threshold factors that allow us to prove properties, provided that they hold for explicit Euler steps. For many methods, the stepsize restrictions obtained are sharper than the ones obtained in terms of the Kraaijevanger’s coefficient in the SSP theory. In particular, for the classical 4-stage fourth order method we get nontrivial stepsize restrictions. Furthermore, the order barrier $p\le 4$ for explicit SSP RK methods is not obtained. An open question is the existence of explicit RK schemes with order $p\ge 5$ and nontrivial modified threshold factor. The numerical experiments done illustrate the results obtained.     

$$L_2$$ 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.     

On a Class of Implicit–Explicit Runge–Kutta Schemes for Stiff Kinetic Equations Preserving the Navier–Stokes Limit

Implicit–explicit (IMEX) Runge–Kutta (RK) schemes are popular high order time discretization methods for solving stiff kinetic equations. As opposed to the compressible Euler limit (leading order asymptotics of the Boltzmann equation as the Knudsen number \(\varepsilon \) goes to zero), their asymptotic behavior at the Navier–Stokes (NS) level (next order asymptotics) was rarely studied. In this paper, we analyze a class of existing IMEX RK schemes and show that, under suitable initial conditions, they can capture the NS limit without resolving the small parameter \(\varepsilon \), i.e., \(\varepsilon =o(\Delta t)\), \(\Delta t^m=o(\varepsilon )\), where m is the order of the explicit RK part in the IMEX scheme. Extensive numerical tests for BGK and ES-BGK models are performed to verify our theoretical results.     

Stability and Neimark–Sacker bifurcation in Runge–Kutta methods for a predator–prey system

We investigate the discretization of a predator–prey system with two delays under the general Runge–Kutta methods. It is shown that if the exact solution undergoes a Hopf bifurcation at τ=τ*, then the numerical solution undergoes a Neimark–Sacker bifurcation at τ(h)=τ*+O(h ^p ) for sufficiently small step size h, where p≥1 is the order of the Runge–Kutta method applied. The direction of Neimark–Sacker bifurcation and stability of bifurcating invariant curve are the same as that of delay differential equation.     

Accurate Implicit–Explicit General Linear Methods with Inherent Runge–Kutta Stability

We investigate implicit–explicit (IMEX) general linear methods (GLMs) with inherent Runge–Kutta stability (IRKS) for differential systems with non-stiff and stiff processes. The construction of such formulas starts with implicit GLMs with IRKS which are A- and L-stable, and then we ‘remove’ implicitness in non-stiff terms by extrapolating unknown stage derivatives by stage derivatives which are already computed by the method. Then we search for IMEX schemes with large regions of absolute stability of the ‘explicit part’ of the method assuming that the ‘implicit part’ of the scheme is \(A(\alpha )\)-stable for some \(\alpha \in (0,\pi /2]\). Examples of highly stable IMEX GLMs are provided of order \(1\le p\le 4\). Numerical examples are also given which illustrate good performance of these schemes.     

Stability of two-step Runge–Kutta methods for neutral delay differential-algebraic equations

This paper develops the two-step Runge–Kutta methods (TSRKs) for the neutral delay differential-algebraic equations (NDDAEs) and proves that the TSRKs are asymptotically stable for linear NDDAEs under the assumption that the coefficient matrices are all upper triangular, which is necessary to formulate the stability result. The discussions are supported by the numerical experiments.     

Computation of the Interval of Stability of Runge–Kutta–Nyström Methods

We present a Mathematica package to compute the interval of stability of Runge–Kutta–Nystrom methods fory">=f(t,y).     

Stability analysis of Runge–Kutta methods for differential equations with piecewise continuous arguments of mixed type

This paper deals with the stability analysis of the Runge–Kutta methods for a differential equation with piecewise continuous arguments of mixed type. The stability regions of the analytical solution are given. The necessary and sufficient conditions under which the numerical solution is asymptotically stable are discussed. The conditions under which the analytical stability region is contained in the numerical stability region are obtained and some numerical experiments are given.     

On implicit Runge–Kutta methods obtained as a result of the inversion of explicit methods

We consider methods that are the inverse of the explicit Runge–Kutta methods. Such methods have some advantages, while their disadvantage is the low (first) stage order. This reduces the accuracy and the real order in solving stiff and differential-algebraic equations. New methods possessing properties of methods of a higher stage order are proposed. The results of the numerical experiments show that the proposed methods allow us to avoid reducing the order.     

Numerical Comparison of WENO Finite Volume and Runge–Kutta Discontinuous Galerkin Methods

High order WENO (weighted essentially non-oscillatory) schemes and discontinuous Galerkin methods are two classes of high order, high resolution methods suitable for convection dominated simulations with possible discontinuous or sharp gradient solutions. In this paper we first review these two classes of methods, pointing out their similarities and differences in algorithm formulation, theoretical properties, implementation issues, applicability, and relative advantages. We then present some quantitative comparisons of the third order finite volume WENO methods and discontinuous Galerkin methods for a series of test problems to assess their relative merits in accuracy and CPU timing.     

Stability investigation of Runge–Kutta schemes with artificial dissipator on curvilinear grids for the Euler equations

By using the Fourier method we study the stability of a three-stage finite volume Runge–Kutta time stepping scheme approximating the 2D Euler equations on curvilinear grids. By combining the analytic and numeric stability investigation results we obtain an analytic formula for stability condition. The results of numerical solution of a number of internal and external fluid dynamics problems are presented, which confirm the correctness of the obtained stability condition. It is shown that the incorporation of the artificial dissipation terms into the Runge–Kutta scheme does not impose additional restrictions on time step in cases of smooth flows or flows with weak shocks. In cases of strong shocks, the use of artificial viscosity leads to the reduction of the maximum time step allowed by stability in comparison with the case of the absence of artificial viscosity.     

Symmetric and symplectic exponentially fitted Runge–Kutta–Nyström methods for Hamiltonian problems

The construction of symmetric and symplectic exponentially fitted modified Runge–Kutta–Nyström (SSEFRKN) methods is considered. Based on the symmetry, symplecticity, and exponentially fitted conditions, new explicit modified RKN integrators with FSAL property are obtained. The new integrators integrate exactly differential systems whose solutions can be expressed as linear combinations of functions from the set { exp(± iωt)}, ω > 0, i² = −1, or equivalently from the set { cos(ωt), sin(ωt)}. The phase properties of the new integrators are examined and their periodicity regions are obtained. Numerical experiments are accompanied to show the high efficiency and competence of the new SSEFRKN methods compared with some highly efficient nonsymmetric symplecti EFRKN methods in the literature.