Implicit difference scheme for the numerical resolution of the Charney-Obukhov equation with variable coefficients.
Implicit difference schemes for mixed problems related to parabolic functional differential equations
Solutions of initial boundary value problems for parabolic functional differential equations are approximated by solutions of implicit difference schemes. The existence and uniqueness of approximate solutions is proved. The proof of the stability is based on a comparison technique with nonlinear estimates of the Perron type for given operators. It is shown that the new methods are considerably better than the explicit difference schemes. Numerical examples are presented.
Implicit for local effects and explicit for nonlocal effects is unconditionally stable.
Implicit predictor-corrector iteration process for finitely many asymptotically (quasi-)nonexpansive mappings.
Implicit Runge- Kutta Methods for Second Kind Volterra Integral Equations.
Implicit Runge-Kutta methods for transferable differential-algebraic equations
The numerical solution of transferable differential-algebraic equations (DAE’s) by implicit Runge-Kutta methods (IRK) is studied. If the matrix of coefficients of an IRK is non-singular then the arising systems of nonlinear equations are uniquely solvable. These methods are proved to be stable if an additional contractivity condition is satisfied. For transferable DAE’s with smooth solution we get convergence of order , where is the classical order of the IRK and is the stage order. For transferable...
Implicit-explicit Runge–Kutta schemes and finite elements with symmetric stabilization for advection-diffusion equations
We analyze a two-stage implicit-explicit Runge–Kutta scheme for time discretization of advection-diffusion equations. Space discretization uses continuous, piecewise affine finite elements with interelement gradient jump penalty; discontinuous Galerkin methods can be considered as well. The advective and stabilization operators are treated explicitly, whereas the diffusion operator is treated implicitly. Our analysis hinges on L2-energy estimates on discrete functions in physical space. Our main...
Implicit-explicit Runge–Kutta schemes and finite elements with symmetric stabilization for advection-diffusion equations
We analyze a two-stage implicit-explicit Runge–Kutta scheme for time discretization of advection-diffusion equations. Space discretization uses continuous, piecewise affine finite elements with interelement gradient jump penalty; discontinuous Galerkin methods can be considered as well. The advective and stabilization operators are treated explicitly, whereas the diffusion operator is treated implicitly. Our analysis hinges on L2-energy estimates on discrete functions in physical space. Our main...
Implicit-explicit Runge–Kutta schemes and finite elements with symmetric stabilization for advection-diffusion equations
We analyze a two-stage implicit-explicit Runge–Kutta scheme for time discretization of advection-diffusion equations. Space discretization uses continuous, piecewise affine finite elements with interelement gradient jump penalty; discontinuous Galerkin methods can be considered as well. The advective and stabilization operators are treated explicitly, whereas the diffusion operator is treated implicitly. Our analysis hinges on L2-energy estimates on discrete functions in physical space. Our main...
Improved ball convergence of Newton's method under general conditions
We present ball convergence results for Newton's method in order to approximate a locally unique solution of a nonlinear operator equation in a Banach space setting. Our hypotheses involve very general majorants on the Fréchet derivatives of the operators involved. In the special case of convex majorants our results, compared with earlier ones, have at least as large radius of convergence, no less tight error bounds on the distances involved, and no less precise information on the uniqueness of...
Improved convergence bounds for smoothed aggregation method: linear dependence of the convergence rate on the number of levels
The smoothed aggregation method has became a widely used tool for solving the linear systems arising by the discretization of elliptic partial differential equations and their singular perturbations. The smoothed aggregation method is an algebraic multigrid technique where the prolongators are constructed in two steps. First, the tentative prolongator is constructed by the aggregation (or, the generalized aggregation) method. Then, the range of the tentative prolongator is smoothed by a sparse linear...
Improved convergence estimate for a multiply polynomially smoothed two-level method with an aggressive coarsening
A variational two-level method in the class of methods with an aggressive coarsening and a massive polynomial smoothing is proposed. The method is a modification of the method of Section 5 of Tezaur, Vaněk (2018). Compared to that method, a significantly sharper estimate is proved while requiring only slightly more computational work.
Improved Difference Schemes for the Dirichlet Problem of Poisson's Equation in the Neighbourhood of Corners.
Improved discrepancy bounds for hybrid sequences involving Halton sequences
Improved Estimates of Statistical Regularization Parameters in Fourier Differentiation and Smoothing.
Improved flux reconstructions in one dimension
We present an improvement to the direct flux reconstruction technique for equilibrated flux a posteriori error estimates for one-dimensional problems. The verification of the suggested reconstruction is provided by numerical experiments.
Improved initialization of the accelerated and robust QR-like polynomial root-finding.
Improved K-K algorithm for computing Lyapunov values
Improved least-squares error estimates for scalar hyperbolic problems.
Improved local convergence analysis of inexact Newton-like methods under the majorant condition
We present a local convergence analysis of inexact Newton-like methods for solving nonlinear equations. Using more precise majorant conditions than in earlier studies, we provide: a larger radius of convergence; tighter error estimates on the distances involved; and a clearer relationship between the majorant function and the associated least squares problem. Moreover, these advantages are obtained under the same computational cost.