Strong Stability Preserving Runge-Kutta Methods Research Articles

A fast explicit time-splitting spectral scheme for the viscous Cahn-Hilliard equation with nonlocal diffusion operator

The viscous Cahn-Hilliard equation (VCH) is a parameter-dependent model encapsulated Cahn-Hilliard (CH) model and constrained Allen-Cahn (CAC) model. In this paper, we propose a fast explicit time-splitting spectral scheme for the VCH with nonlocal diffusion operator. The numerical scheme is constructed based on the second-order symmetric time-splitting method, which results in a splitting of the original problem into nonlocal linear part and nonlinear part, respectively. The nonlocal linear subproblem can be solved exactly by applying the Fourier spectral discretization in space and thus has no stability restriction on the time-step size. The nonlinear subproblem is solved via a second-order strong stability preserving Runge–Kutta method. The new scheme is time symmetric, fully explicit and conserves the discrete mass exactly. Theoretical analysis shows that the stability of the scheme depends on both the viscosity coefficient and the range of nonlocal interactions. In addition, a rigorously convergence analysis of the scheme is established, and the convergence rate is proved to be second-order in time and spectral-order in space, respectively. Four numerical experiments are performed to demonstrate the effectiveness of the proposed scheme.

Explicit strong stability preserving second derivative multistep methods for the Euler and Navier–Stokes equations

In this paper, we develop the explicit second derivative multistep methods (SDMMs) for the Euler and Navier–Stokes equations. The SDMMs use the calculated results from the previous steps, which can improve computational efficiency. The third-order and fourth-order SDMMs temporal discretization methods are constructed based on the order conditions. Additionally, the strong stability preserving (SSP) condition for the SDMMs is proposed, which provides the corresponding parameters for optimal SSP SDMMs. For numerical experiments, the SDMMs can achieve the order of accuracy as designed on the smooth regions, and the optimal SSP coefficient for the SDMMs is shown to be roughly the same in theory as in the numerical results. Moreover, the SDMMs have approximately twice the computational efficiency compared with the third-order and fourth-order two-derivative Runge–Kutta methods, and the SDMMs are also more efficient than the classical three-stage third-order SSP Runge–Kutta method.

A new type of improved third order WENO scheme with finite difference framework

In this paper, we present a novel variety of third order finite difference weighted essentially non-oscillatory (WENO) scheme based on WENO-ZQ scheme to approximate the computational solutions of one- and two-dimensional non-linear hyperbolic conservation laws. The new reconstruction process of fluxes is the convex combination of a second degree polynomial and two linear polynomials. We apply a new modified global smoothness indicator into the non-linear weights. We also use the power parameter ‘p’ to balance the accuracy of the proposed scheme. This novel third order WENO scheme applies three points data {xi−1,xi,xi+1} same as WENO-JS3 and WENO-Z3 schemes. In the proposed scheme, the main advantages are that the associated linear weights can be taken as any positive numbers on condition their summation is one. Also, it is easy to be used in multi-dimensional engineering problems. We implement the time discretization by using third order accurate strong stability preserving Runge–Kutta method. The extensive computational experiments of a collection of benchmark test problems are provided to demonstrate high resolution, robustness and absolute truncation errors in L1 and L∞ norms. We observe from the results that the new scheme contains better capability in performance than WENO-PZ3 scheme.

A well‐balanced and entropy stable scheme for a reduced blood flow model

AbstractA well‐known reduced model of the flow of blood in arteries can be formulated as a strictly hyperbolic system of two scalar balance laws in one space dimension where the unknowns are the cross‐sectional area of the artery and the average blood flow velocity as functions of the axial coordinate and time. This system is endowed with an entropy pair such that solutions of the balance equations satisfy an entropy inequality in the distributional sense. It is demonstrated that this property can be utilized to construct an entropy stable finite difference scheme for the blood flow model based on the general framework by Tadmor (E. Tadmor, Math. Comput., 49 (1987), 91–103). Furthermore, a fourth‐order extension of the resulting entropy conservative flux and a fourth‐order sign‐preserving reconstruction of the scaled entropy variables are employed as well as a second‐order strong stability preserving Runge–Kutta method for time discretization. The result is a computationally inexpensive and easy‐to‐implement explicit entropy stable scheme for the blood flow model. It is proven that the scheme is well‐balanced (i.e., preserves certain steady solutions of the model) and numerical examples are presented.

Strong Stability Preserving Runge–Kutta and Linear Multistep Methods

This paper reviews strong stability preserving discrete variable methods for differential systems. The strong stability preserving Runge–Kutta methods have been usually investigated in the literature on the subject, using the so-called Shu–Osher representation of these methods, as a convex combination of first-order steps by forward Euler method. In this paper, we revisit the analysis of strong stability preserving Runge–Kutta methods by reformulating these methods as a subclass of general linear methods for ordinary differential equations, and then using a characterization of monotone general linear methods, which was derived by Spijker in his seminal paper (SIAM J Numer Anal 45:1226–1245, 2007). Using this new approach, explicit and implicit strong stability preserving Runge–Kutta methods up to the order four are derived. These methods are equivalent to explicit and implicit RK methods obtained using Shu–Osher or generalized Shu–Osher representation. We also investigate strong stability preserving linear multistep methods using again monotonicity theory of Spijker.

Totally volume integral of fluxes for discontinuous Galerkin method-two dimensional Euler equations

In this paper, the scheme of constructing high-order accurate totally volume discontinuous finite element method for the numerical solution of the 1D Euler equations is extended to 2D Euler equations on Cartesian meshes. In the present work, the boundary integral fluxes are transformed into volume integral by applying divergence theorem to the boundary integral of the Riemann fluxes. Therefore, the totally volume discontinuous finite element is independent on the boundary integral fluxes at the element boundaries as opposed to the classical discontinuous Galerkin method. The accuracy is obtained by applying high-order polynomial approximations within elements using the tensor product of Lagrange polynomial. For temporal integration, strong stability preserving Runge-Kutta method SSPRK (3, 3) is applied. The scheme is stabilized by using Streamline Upwind Petrov Galerkin (SUPG) stabilization technique. For the spatial discretization, the polynomial of order 1and 2 are used, the shape function is constructed for the master (computational) element after applying the coordinate transformation for the physical domain, the transformation for the governing equations is performed to get it in the function of computational Cartesian, then the governing equations are put in conservative form. The numerical results of applying totally volume integral discontinuous Galerkin method for two-dimensional Euler equations presented in this paper show that the scheme is very accurate, fast, and effective even with shock appearance.

Monolithic parabolic regularization of the MHD equations and entropy principles

We show at the PDE level that the monolithic parabolic regularization of the equations of ideal magnetohydrodynamics (MHD) is compatible with all the generalized entropies, fulfills the minimum entropy principle, and preserves the positivity of density and internal energy. We then numerically investigate this regularization for the MHD equations using continuous finite elements in space and explicit strong stability preserving Runge–Kutta methods in time. The artificial viscosity coefficient of the regularization term is constructed to be proportional to the entropy residual of MHD. It is shown that the method has a high order of accuracy for smooth problems and captures strong shocks and discontinuities accurately for non-smooth problems.

Embedded pairs for optimal explicit strong stability preserving Runge–Kutta methods

We construct a family of embedded pairs for optimal explicit strong stability preserving Runge–Kutta methods of order 2≤p≤4 to be used to obtain numerical solution of spatially discretized hyperbolic PDEs. In this construction, the goals include non-defective property, large stability region, and small error values as defined in Dekker and Verwer (1984) and Kennedy et al. (2000). The new family of embedded pairs offer the ability for strong stability preserving (SSP) methods to adapt by varying the step-size. Through several numerical experiments, we assess the overall effectiveness in terms of work versus precision while also taking into consideration accuracy and stability.

An assessment of solvers for algebraically stabilized discretizations of convection–diffusion–reaction equations

Abstract We consider flux-corrected finite element discretizations of 3D convection-dominated transport problems and assess the computational efficiency of algorithms based on such approximations. The methods under investigation include flux-corrected transport schemes and monolithic limiters. We discretize in space using a continuous Galerkin method and ℙ1 or ℚ1 finite elements. Time integration is performed using the Crank–Nicolson method or an explicit strong stability preserving Runge–Kutta method. Nonlinear systems are solved using a fixed-point iteration method, which requires solution of large linear systems at each iteration or time step. The great variety of options in the choice of discretization methods and solver components calls for a dedicated comparative study of existing approaches. To perform such a study, we define new 3D test problems for time dependent and stationary convection–diffusion–reaction equations. The results of our numerical experiments illustrate how the limiting technique, time discretization and solver impact on the overall performance.

Strong Stability Preserving Runge-Kutta Methods Applied to Water Hammer Problem

The characteristic method of lines is the most used numerical method applied to the water hammer problem. It transforms a system of partial differential equations involving the independent variables time and space in two ordinary differential equations along the characteristics curves and then solve it numerically. This approach, although showing great stability and quick execution time, creates ∆x-∆t dependency to properly model the phenomenon. In this article we test a different approach, using the method of lines in the usual form, without the characteristics curves and then applying strong stability preserving Runge-Kutta Methods aiming to get stability with greater ∆t.

A high-order partitioned fluid-structure interaction framework for vortex-induced vibration simulation

Vortex-induced vibration (VIV) is a highly nonlinear fluid-structure interaction (FSI) phenomenon, and its accurate prediction remains challenging. In this study, we developed a high-order partitioned FSI framework towards accurate simulation of the VIV phenomenon. The focus is on simulating the two-way coupled interaction between a flexibly mounted rigid body and its surrounding fluids. In the FSI framework, a high-order computational fluid dynamics method, i.e., flux reconstruction/correction procedure via reconstruction, is utilized to simulate the unsteady compressible Navier–Stokes equations in the arbitrary Lagrangian Eulerian format on unstructured moving grids. A linearized fluid-solid Riemann solver is employed to weakly couple fluid dynamics and rigid-body dynamics on the fluid-solid interface, which can effectively mitigate the so-called added-mass instability. Time marching is conducted through either the linearly implicit Rosenbrock–Wanner method or the explicit strong stability preserving Runge–Kutta method. The high-order FSI framework is verified with a challenging VIV phenomenon, i.e., VIV of a zero-mass cylinder in viscous flows, and has been used to study two VIV-related problems, namely, the nonlinear energy sink and oscillating foil based energy harvesting mechanism.

Two different temporal domain integration schemes combined with compact finite difference method to solve modified Burgers’ equation

The modified Burgers’ equation has application in various fields such as explosions and sonic boom theory, propagation of torsional waves in thin circular viscoelastic rod, acoustic waves produced by laser radiations, etc. A sixth-order compact finite difference scheme has been used for the space integration. Two different approaches have been followed for time integration. One is the Crank-Nicolson scheme in which the nonlinear term is handled with a quasilinearization process. Another is the strong stability preserving Runge-Kutta method of four stage, third-order convergence (SSP-RK43), in which no linearization is required. The stability analysis for both the schemes has been presented and is shown to be stable. Few test problems have been solved, demonstrating the performance of the proposed techniques. The L2 and L∞ error norms are calculated and are compared with the previous work. The aim of the paper is to solve such an important equation with better accuracy and less computational efforts.

Numerical Approximation of Generalized Burger’s-Fisher and Generalized Burger’s-Huxley Equation by Compact Finite Difference Method

In this work, computational analysis of generalized Burger’s-Fisher and generalized Burger’s-Huxley equation is carried out using the sixth-order compact finite difference method. This technique deals with the nonstandard discretization of the spatial derivatives and optimized time integration using the strong stability-preserving Runge-Kutta method. This scheme inculcates four stages and third-order accuracy in the time domain. The stability analysis is discussed using eigenvalues of the coefficient matrix. Several examples are discussed for their approximate solution, and comparisons are made to show the efficiency and accuracy of CFDM6 with the results available in the literature. It is found that the present method is easy to implement with less computational effort and is highly accurate also.

Stability and Error Estimate of the Operator Splitting Method for the Phase Field Crystal Equation

In this paper, we propose a second-order fast explicit operator splitting method for the phase field crystal equation. The basic idea lied in our method is to split the original problem into linear and nonlinear parts. The linear subproblem is numerically solved using the Fourier spectral method, which is based on the exact solution and thus has no stability restriction on the time-step size. The nonlinear one is solved via second-order strong stability preserving Runge–Kutta method. The stability and convergence are discussed in $$L^2$$ -norm. Numerical experiments are performed to validate the accuracy and efficiency of the proposed method. Moreover, energy degradation and mass conservation are also verified.

A bound-preserving high order scheme for variable density incompressible Navier-Stokes equations

For numerical schemes to the incompressible Navier-Stokes equations with variable density, it is a critical property to preserve the bounds of density. A bound-preserving high order accurate scheme can be constructed by using high order discontinuous Galerkin (DG) methods or finite volume methods with a bound-preserving limiter for the density evolution equation, with any popular numerical method for the momentum evolution. In this paper, we consider a combination of a continuous finite element method for momentum evolution and a bound-preserving DG method for density evolution. Fully explicit and explicit-implicit strong stability preserving Runge-Kutta methods can be used for the time discretization for the sake of bound-preserving. Numerical tests on representative examples are shown to demonstrate the performance of the proposed scheme.

A spectral multidomain penalty method solver for the numerical simulation of granular avalanches

This work presents a high-order element-based numerical simulation of an experimental granular avalanche, in order to assess the potential of these spectral techniques to handle conservation laws in geophysics. The spatial discretization of these equations was developed via the spectral multidomain penalty method (SMPM). The temporal terms were discretized using a strong-stability preserving Runge-Kutta method. Stability of the numerical scheme is ensured with the use of a spectral filter and a constant or regularized lateral earth pressure coefficient. The test case is a granular avalanche that is generated in a small-scale rectangular flume with topographical gradient. A grid independence test was performed to clarify the order of the error in the mass conservation produced by the treatments here implemented. The numerical predictions of the granular avalanches are compared with experimental measurements performed by Denlinger & Iverson (2001). Furthermore, the boundary conditions and parameters such as lateral earth pressure coefficients and the momentum correction factor were analyzed to observe the incidence of these features when solving the granular flow equations. This work identifies the benefits and weaknesses of the SMPM to solve this set of equations and, it is possible to conclude that the SMPM provides an appropriate solution of the granular flow equations proposed by Iverson & Denlinger (2001). Besides, it produces comparable predictions to experimental data and numerical results given by other schemes.

Extended Fisher-Kolmogorov Denklemini Çözmek İçin Kuartik B-Spline Diferansiyel Kuadratur Metot

Some numerical solutions of the extended Fisher-Kolmogorov(EFK) equation have been obtained via quartic B-spline differential quadrature method(DQM). 2ndorder weighting coefficients are obtained directly by quartic B-splines. Since the 4thorder derivatives of quartic B-splines do not exist, the 4thorder weighting coefficients have been obtained by matrix multiplication approach. After the discretization of the eFK equation via DQM, ordinary differential equation systems have been obtained and strong stability preserving Runge-Kutta method has been used for time integration. To be able to control the accuracy of the method three test problems have been solved and error norms L2and L∞are calculated.

Modeling Three‐Dimensional Wave Propagation in Anelastic Models With Surface Topography by the Optimal Strong Stability Preserving Runge‐Kutta Method

AbstractAccurate and efficient forward modeling methods are important for simulation of seismic wave propagation in 3D realistic Earth models and crucial for high‐resolution full waveform inversion. In the presence of attenuation, wavefield simulation could be inaccurate or unstable over time if not well treated, indicating the importance of the implementation of a strong stability preserving time discretization scheme. In this study, to solve the anelastic wave equation, we choose the optimal strong stability preserving Runge‐Kutta (SSPRK) method for the temporal discretization and apply the fourth‐order MacCormack scheme for the spatial discretization. We approximate the rheological behaviors of the Earth by using the generalized Maxwell body model and use an optimization procedure to calculate the anelastic coefficients determined by the Q(ω) law. This optimization constrains positivity of the anelastic coefficients and ensures the decay of total energy with time, resulting in a stable viscoelastic system even in the presence of strong attenuation. Moreover, we perform theoretical and numerical analyses of the SSPRK method, including the stability criteria and the numerical dispersion. Compared with the traditional fourth‐order Runge‐Kutta method, the SSPRK has a larger stability condition number and can better suppress numerical dispersion. We use the complex‐frequency‐shifted perfectly matched layer for the absorbing boundary conditions based on the auxiliary difference equation and employ the traction image method for the free‐surface boundary condition on curvilinear grids representing the surface topography. Finally, we perform several numerical experiments to demonstrate the accuracy of our anelastic modeling in the presence of surface topography.

Strong stability preserving transformed DIMSIMs

In this paper we investigate the strong stability preserving (SSP) property of transformed diagonally implicit multistage integration methods (DIMSIMs). Within this class, examples of SSP methods of order p = 1 , 2 , 3 and 4 and stage order q = p have been determined, and also suitable starting and finishing procedure have been constructed. The numerical experiments performed on a set of test problems have shown that SSP transformed DIMSIMs can be more accurate and competitive with SSP Runge–Kutta methods of the same order.

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.