English
Related papers

Related papers: Strong-stability-preserving additive linear multis…

200 papers

Strong stability preserving (SSP) methods are designed primarily for time integration of nonlinear hyperbolic PDEs, for which the permissible SSP step size varies from one step to the next. We develop the first SSP linear multistep methods…

Numerical Analysis · Mathematics 2022-04-05 Yiannis Hadjimichael , David Ketcheson , Lajos Lóczi , Adrián Németh

High-order spatial discretizations with strong stability properties (such as monotonicity) are desirable for the solution of hyperbolic PDEs. Methods may be compared in terms of the strong stability preserving (SSP) time-step. We prove an…

Numerical Analysis · Mathematics 2014-01-30 Christopher Bresten , Sigal Gottlieb , Zachary Grant , Daniel Higgs , David I. Ketcheson , Adrian Németh

Strong stability preserving (SSP) integrators for initial value ODEs preserve temporal monotonicity solution properties in arbitrary norms. All existing SSP methods, including implicit methods, either require small step sizes or achieve…

Numerical Analysis · Mathematics 2012-03-27 David I. Ketcheson

When evolving in time the solution of a hyperbolic partial differential equation, it is often desirable to use high order strong stability preserving (SSP) time discretizations. These time discretizations preserve the monotonicity…

Numerical Analysis · Mathematics 2017-08-02 Sidafa Conde , Sigal Gottlieb , Zachary J. Grant , John N. Shadid

Strong stability preserving (SSP) coefficients govern the maximally allowable step-size at which positivity or contractivity preservation of integration methods for initial value problems is guaranteed. In this paper, we show that the task…

Numerical Analysis · Mathematics 2020-11-17 Rachid Ait-Haddou

This paper extends deterministic notions of Strong Stability Preservation (SSP) to the stochastic setting, enabling nonlinearly stable numerical solutions to stochastic differential equations (SDEs) and stochastic partial differential…

Numerical Analysis · Mathematics 2024-12-10 James Woodfield

High order strong stability preserving (SSP) time discretizations are often needed to ensure the nonlinear (and sometimes non-inner-product) strong stability properties of spatial discretizations specially designed for the solution of…

Numerical Analysis · Mathematics 2018-10-22 Zachary Grant , Sigal Gottlieb , David C Seal

We prove the existence of explicit linear multistep methods of any order with positive coefficients. Our approach is based on formulating a linear programming problem and establishing infeasibility of the dual problem. This yields a number…

Numerical Analysis · Mathematics 2016-04-07 Adrián Németh , David Ketcheson

High order spatial discretizations with monotonicity properties are often desirable for the solution of hyperbolic PDEs. These methods can advantageously be coupled with high order strong stability preserving time discretizations. The…

Numerical Analysis · Mathematics 2014-03-27 Sigal Gottlieb , Zachary J. Grant , Daniel Higgs

Linear multistep methods (LMMs) applied to approximate the solution of initial value problems---typically arising from method-of-lines semidiscretizations of partial differential equations---are often required to have certain monotonicity…

Numerical Analysis · Mathematics 2017-05-30 Lajos Lóczi

High order strong stability preserving (SSP) time discretizations are advantageous for use with spatial discretizations with nonlinear stability properties for the solution of hyperbolic PDEs. The search for high order strong stability…

Numerical Analysis · Mathematics 2016-03-24 Andrew J. Christieb , Sigal Gottlieb , Zachary J. Grant , David C. Seal

Strong Stability Preserving (SSP) time integration schemes maintain stability of the forward Euler method for any initial value problem. However, only a small subset of Runge-Kutta (RK) methods are SSP, and many efficient high-order time…

Numerical Analysis · Mathematics 2026-01-28 Mohammad R. Najafian , Brian C. Vermeire

We present a theoretical analysis of stochastic optimization methods in terms of their sensitivity with respect to the step size. We identify a key quantity that, for each method, describes how the performance degrades as the step size…

Optimization and Control · Mathematics 2026-05-27 Fabian Schaipp , Robert M. Gower , Adrien Taylor

High order strong stability preserving (SSP) time discretizations ensure the nonlinear non-inner-product strong stability properties of spatial discretizations suited for the stable simulation of hyperbolic PDEs. Over the past decade…

Numerical Analysis · Mathematics 2024-12-20 Sigal Gottlieb , Zachary J. Grant

We construct a family of embedded pairs for optimal strong stability preserving explicit Runge-Kutta methods of order $2 \leq p \leq 4$ to be used to obtain numerical solution of spatially discretized hyperbolic PDEs. In this construction,…

Numerical Analysis · Mathematics 2022-05-17 Sidafa Conde , Imre Fekete , John N. Shadid

Strong stability preserving (SSP) Runge-Kutta methods are often desired when evolving in time problems that have two components that have very different time scales. Where the SSP property is needed, it has been shown that implicit and…

Numerical Analysis · Mathematics 2018-08-15 Sigal Gottlieb , Zachary J. Grant , Leah Isherwood

Problems that feature significantly different time scales, where the stiff time-step restriction comes from a linear component, implicit-explicit (IMEX) methods alleviate this restriction if the concern is linear stability. However, where…

Numerical Analysis · Mathematics 2019-04-16 Leah Isherwood , Zachary J. Grant , Sigal Gottlieb

In this paper, nonstandard multistep methods are considered. It is shown that under some (sufficient and necessary) conditions, these methods attain the same order as their standard counterparts - to prove this statement, a nonstandard…

Numerical Analysis · Mathematics 2026-01-19 Bálint Takács

We report on recent work on adaptive timestep control for weakly instationary gas flows [16, 18, 17] carried out within SFB 401, TPA3. The method which we implement and extend is a space-time splitting of adjoint error representations for…

Numerical Analysis · Mathematics 2014-05-22 Sebastian Noelle , Christina Steiner

In this paper we continue our work on adaptive timestep control for weakly non- stationary problems. The core of the method is a space-time splitting of adjoint error representations for target functionals due to S\"uli and Hartmann. The…

Numerical Analysis · Mathematics 2014-06-19 Christina Steiner , Siegfried Müller , Sebastian Noelle
‹ Prev 1 2 3 10 Next ›