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We show in this paper that third- and fourth-order low storage Runge-Kutta algorithms can be built specifically for quadratic nonlinear operators, at the expense of roughly doubling the time needed for evaluating the temporal derivatives.…

Fluid Dynamics · Physics 2008-08-14 Marc E. Brachet , Pablo D. Mininni , Duane L. Rosenberg , Annick Pouquet

Multiderivative time integrators have a long history of development for ordinary differential equations, and yet to date, only a small subset of these methods have been explored as a tool for solving partial differential equations (PDEs).…

Numerical Analysis · Mathematics 2013-10-01 David C. Seal , Yaman Güçlü , Andrew J. Christlieb

Applied to the master equation, the usual numerical integration methods, such as Runge-Kutta, become inefficient when the rates associated with various transitions differ by several orders of magnitude. We introduce an integration scheme…

Statistical Mechanics · Physics 2009-11-07 Ronald Dickman

First-order systems of hyperbolic partial differential equations (PDEs) occur ubiquitously throughout computational physics, commonly used in simulations of fluid turbulence, shock waves, electromagnetic interactions, and even general…

Logic in Computer Science · Computer Science 2025-03-19 Jonathan Gorard , Ammar Hakim

In this paper we consider stabilised finite element methods for hyperbolic transport equations without coercivity. Abstract conditions for the convergence of the methods are introduced and these conditions are shown to hold for three…

Numerical Analysis · Mathematics 2014-05-05 Erik Burman

We propose entropy-preserving and entropy-stable partitioned Runge--Kutta (RK) methods. In particular, we extend the explicit relaxation Runge--Kutta methods to IMEX--RK methods and a class of explicit second-order multirate methods for…

Numerical Analysis · Mathematics 2022-07-21 Shinhoo Kang , Emil M. Constantinescu

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…

Numerical Analysis · Mathematics 2026-04-29 John Driscoll , Sigal Gottlieb , Zachary J. Grant , César Herrera , Tej Sai Kakumanu , Monica Stephens

Finite differences and Runge-Kutta time stepping schemes used in Computational AeroAcoustics simulations are often optimized for low dispersion and dissipation (e.g. DRP or LDDRK schemes) when applied to linear problems in order to…

Numerical Analysis · Mathematics 2019-12-02 Aldaïr Petronilia , Edward James Brambley

This article extends the theory of dual-consistent summation-by-parts (SBP) and generalized SBP (GSBP) time-marching methods by showing that they are implicit Runge-Kutta schemes. Through this connection, the accuracy theory for the…

Numerical Analysis · Mathematics 2016-01-26 Pieter D. Boom , David W. Zingg

New time integration methods are proposed for simulating incompressible multiphase flow in pipelines described by the one-dimensional two-fluid model. The methodology is based on 'half-explicit' Runge-Kutta methods, being explicit for the…

Numerical Analysis · Mathematics 2019-02-19 Benjamin Sanderse , Arthur E. P. Veldman

In this paper a new Runge-Kutta type scheme is introduced for nonlinear stochastic partial differential equations (SPDEs) with multiplicative trace class noise. The proposed scheme converges with respect to the computational effort with a…

Numerical Analysis · Mathematics 2012-04-03 Xiaojie Wang , Siqing Gan

Next-generation exascale machines with extreme levels of parallelism will provide massive computing resources for large scale numerical simulations of complex physical systems at unprecedented parameter ranges. However, novel numerical…

Computational Physics · Physics 2023-02-08 Komal Kumari , Emmet Cleary , Swapnil Desai , Diego A. Donzis , Jacqueline H. Chen , Konduri Aditya

Complex dynamical networks appear in a wide range of physical, biological, and engineering systems. The coupling of subsystems with varying time scales often results in multirate behavior. During the simulation of highly integrated…

Numerical Analysis · Mathematics 2015-04-27 Stefan Klus

We present a new method for developing time step controllers based on a technique from the field of machine learning. This method is applicable to stable time integrators that have an embedded scheme, i.e., that have local error estimation…

Numerical Analysis · Mathematics 2025-12-23 Thomas Izgin , Hendrik Ranocha

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…

Numerical Analysis · Mathematics 2013-11-07 Dominique Küpper , Anne Kværnø , Andreas Rößler

We analyze the stability and accuracy (up to third order) of a new family of implicit-explicit Runge-Kutta (IMEX RK) methods. This analysis expedites development of methods with various balances in the number of explicit stages and implicit…

Numerical Analysis · Mathematics 2019-06-19 Andrew Steyer , Christopher J. Vogl , Mark Taylor , Oksana Guba

The use of high order fully implicit Runge-Kutta methods is of significant importance in the context of the numerical solution of transient partial differential equations, in particular when solving large scale problems due to fine space…

Numerical Analysis · Mathematics 2023-02-27 Ivo Dravins , Stefano Serra-Capizzano , Maya Neytcheva

Recently, an approach known as relaxation has been developed for preserving the correct evolution of a functional in the numerical solution of initial-value problems, using Runge-Kutta methods. We generalize this approach to multistep…

Numerical Analysis · Mathematics 2020-11-26 Hendrik Ranocha , Lajos Lóczi , David I. Ketcheson

A novel class of explicit high-order energy-preserving methods are proposed for general Hamiltonian partial differential equations with non-canonical structure matrix. When the energy is not quadratic, it is firstly done that the original…

Numerical Analysis · Mathematics 2020-06-02 Chaolong Jiang , Yushun Wang , Yuezheng Gong

We study spatially partitioned embedded Runge--Kutta (SPERK) schemes for partial differential equations (PDEs), in which each of the component schemes is applied over a different part of the spatial domain. Such methods may be convenient…

Numerical Analysis · Mathematics 2014-01-09 David I. Ketcheson , Colin B. Macdonald , Steven J. Ruuth