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相关论文: Enforcing strong stability of explicit Runge--Kutt…

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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…

数值分析 · 数学 2018-08-15 Sigal Gottlieb , Zachary J. Grant , Leah Isherwood

Many important initial value problems have the property that energy is non-increasing in time. Energy stable methods, also referred to as strongly stable methods, guarantee the same property discretely. We investigate requirements for…

数值分析 · 数学 2020-11-26 Hendrik Ranocha , David I. Ketcheson

This paper presents a systematic theoretical framework to derive the energy identities of general implicit and explicit Runge--Kutta (RK) methods for linear seminegative systems. It generalizes the stability analysis of explicit RK methods…

数值分析 · 数学 2022-01-19 Zheng Sun , Yuanzhe Wei , Kailiang Wu

Many time-dependent partial differential equations (PDEs) can be transformed into an ordinary differential equations (ODEs) containing moderately stiff and non-stiff terms after spatial semi-discretization. In the present paper, we…

数值分析 · 数学 2025-09-23 Xiao Tang , Junwei Huang

A mixed accuracy framework for Runge--Kutta methods presented in [Grant, JSC 2022] has been shown to speed up the computation in diagonally implicit Runge--Kutta (DIRK) methods by using less expensive low accuracy approaches for the…

Strong stability preserving (SSP) Runge-Kutta methods are desirable when evolving in time problems that have discontinuities or sharp gradients and require nonlinear non-inner-product stability properties to be satisfied. Unlike the case…

数值分析 · 数学 2018-10-12 Leah Isherwood , Zachary J. Grant , Sigal Gottlieb

It is difficult to design high order numerical schemes which could preserve both the maximum bound property (MBP) and energy dissipation law for certain phase field equations. Strong stability preserving (SSP) Runge-Kutta methods have been…

数值分析 · 数学 2022-03-10 Zhaohui Fu , Tao Tang , Jiang Yang

We explore a novel way to numerically resolve the scaling behavior of finite-time singularities in solutions of nonlinear parabolic PDEs. The Runge--Kutta--Legendre (RKL) and Runge--Kutta--Gegenbauer (RKG) super-time-stepping methods were…

数值分析 · 数学 2025-09-24 Zheng Tan , Tariq D. Aslam , Andrea L. Bertozzi

Stabilized methods (also called Chebyshev methods) are explicit methods with extended stability domains along the negative real axis. These methods are intended for large mildly stiff problems, originating mainly from parabolic PDEs. In…

数值分析 · 数学 2023-03-30 Andrew Moisa , Boris Faleichik

We propose a quantitative direct method to prove the local stability of a stationary solution for a rough differential equation and its regular discretization scheme. Using Doss-Sussmann technique and stopping time analysis, we provide…

动力系统 · 数学 2025-09-24 Luu Hoang Duc , Phan Thanh Hong , Nguyen Dinh Cong

The work deals with two major topics concerning the numerical analysis of Runge-Kutta-like (RK-like) methods, namely their stability and order of convergence. RK-like methods differ from additive RK methods in that their coefficients are…

数值分析 · 数学 2025-06-26 Thomas Izgin

Many control, optimization, and learning algorithms rely on discretizations of continuous-time contracting systems, where preservation of contractivity under numerical integration is key for stability, robustness, and reliable fixed-point…

系统与控制 · 电气工程与系统科学 2026-03-13 Yu Kawano , Francesco Bullo

A novel optimization procedure for the generation of stability polynomials of stabilized explicit Runge-Kutta methods is devised. Intended for semidiscretizations of hyperbolic partial differential equations, the herein developed approach…

数值分析 · 数学 2024-03-19 Daniel Doehring , Gregor J. Gassner , Manuel Torrilhon

Deep neural networks have achieved state-of-the-art performance in a variety of fields. Recent works observe that a class of widely used neural networks can be viewed as the Euler method of numerical discretization. From the numerical…

计算机视觉与模式识别 · 计算机科学 2020-10-21 Byungjoo Kim , Bryce Chudomelka , Jinyoung Park , Jaewoo Kang , Youngjoon Hong , Hyunwoo J. Kim

In this study, we investigate the Shallow Water Equations incorporating source terms accounting for Manning friction and a non-flat bottom topology. Our primary focus is on developing and validating numerical schemes that serve a dual…

数值分析 · 数学 2023-10-24 Guanlan Huang , Sebastiano Boscarino , Tao Xiong

We put forward the use of total-variation-diminishing (or more generally, strong stability preserving) implicit-explicit Runge-Kutta methods for the time integration of the equations of motion associated with the semiconvection problem in…

数值分析 · 数学 2012-03-09 Friedrich Kupka , Natalie Happenhofer , Inmaculada Higueras , Othmar Koch

The problem of solving stochastic differential-algebraic equations (SDAEs) of index one with a scalar driving Brownian motion is considered. Recently, the authors proposed a class of stiffly accurate stochastic Runge-Kutta (SRK) methods…

数值分析 · 数学 2013-11-07 Dominique Küpper , Anne Kværnø , Andreas Rößler

Explicit stabilized methods are an efficient alternative to implicit schemes for the time integration of stiff systems of differential equations in large dimension. In this paper, we derive explicit stabilized integrators of orders one and…

数值分析 · 数学 2023-06-09 Ibrahim Almuslimani , Gilles Vilmart

Strong stability is a property of time integration schemes for ODEs that preserve temporal monotonicity of solutions in arbitrary (inner product) norms. It is proved that explicit Runge--Kutta schemes of order $p\in 4\mathbb{N}$ with $s=p$…

数值分析 · 数学 2023-08-11 Franz Achleitner , Anton Arnold , Ansgar Jüngel

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…

数值分析 · 数学 2024-01-15 Abhinav Jha , Ondřej Pártl , Naveed Ahmed , Dmitri Kuzmin