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Related papers: Patankar-Type Runge-Kutta Schemes for Linear PDEs

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Gamma distributed delay differential equations (DDEs) arise naturally in many modelling applications. However, appropriate numerical methods for generic Gamma distributed DDEs are not currently available. Accordingly, modellers often resort…

Numerical Analysis · Mathematics 2021-04-09 Tyler Cassidy , Peter Gillich , Antony R. Humphries , Christiaan H. van Dorp

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…

Numerical Analysis · Mathematics 2025-09-24 Zheng Tan , Tariq D. Aslam , Andrea L. Bertozzi

In this paper we define an efficient implementation of Runge-Kutta methods of Radau IIA type, which are commonly used when solving stiff ODE-IVPs problems. The proposed implementation relies on an alternative low-rank formulation of the…

Numerical Analysis · Mathematics 2024-07-18 L. Brugnano , F. Iavernaro , C. Magherini

The conditioning of implicit Runge-Kutta (RK) integration for linear finite element approximation of diffusion equations on general anisotropic meshes is investigated. Bounds are established for the condition number of the resulting linear…

Numerical Analysis · Mathematics 2021-01-13 Weizhang Huang , Lennard Kamenski , Jens Lang

The effects of kinetic-energy preservation errors due to Runge-Kutta (RK) temporal integrators have been analyzed for the case of large-eddy simulations of incompressible turbulent channel flow. Simulations have been run using the…

Fluid Dynamics · Physics 2024-09-16 Marco Artiano , Carlo De Michele , Francesco Capuano , Gennaro Coppola

Runge-Kutta methods are a popular class of numerical methods for solving ordinary differential equations. Every Runge-Kutta method is characterized by two basic parameters: its order, which measures the accuracy of the solution it produces,…

Numerical Analysis · Mathematics 2019-11-04 David K. Zhang

A new preconditioner based on a block $LDU$ factorization with algebraic multigrid subsolves for scalability is introduced for the large, structured systems appearing in implicit Runge-Kutta time integration of parabolic partial…

Numerical Analysis · Mathematics 2021-01-15 Md Masud Rana , Victoria E. Howle , Katharine Long , Ashley Meek , William Milestone

We propose a unified theoretical framework to examine the energy dissipation properties at all stages of explicit exponential Runge-Kutta (EERK) methods for gradient flow problems. The main part of the novel framework is to construct the…

Numerical Analysis · Mathematics 2024-10-10 Hong-lin Liao , Xuping Wang

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…

Numerical Analysis · Mathematics 2012-03-09 Friedrich Kupka , Natalie Happenhofer , Inmaculada Higueras , Othmar Koch

In this study, a novel semi-implicit second-order temporal scheme combined with the finite element method for space discretization is proposed to solve the coupled system of infiltration and solute transport in unsaturated porous media. The…

Numerical Analysis · Mathematics 2024-06-11 Nour-eddine Toutlini , Abdelaziz Beljadid , Azzeddine Soulaïmani

Typically when a semi-discrete approximation to a partial differential equation (PDE) is constructed a discretization of the spatial operator with a truncation error $\tau$ is derived. This discrete operator should be semi-bounded for the…

Numerical Analysis · Mathematics 2017-11-22 Adi Ditkowski

A numerical search approach is used to design high-order diagonally implicit Runge-Kutta (DIRK) schemes equipped with embedded error estimators, some of which have identical diagonal elements (SDIRK) and explicit first stage (ESDIRK). In…

Numerical Analysis · Mathematics 2023-09-12 Yousef Alamri , David I. Ketcheson

Simulation-based techniques such as variants of stochastic Runge-Kutta are the de facto approach for inference with stochastic differential equations (SDEs) in machine learning. These methods are general-purpose and used with parametric and…

Machine Learning · Computer Science 2021-11-01 Arno Solin , Ella Tamir , Prakhar Verma

This paper investigates the performance of a subclass of exponential integrators, specifically explicit exponential Runge--Kutta methods. It is well known that third-order methods can suffer from order reduction when applied to linearized…

Numerical Analysis · Mathematics 2024-12-30 Thi Tam Dang , Trung Hau Hoang

Most research on preconditioners for time-dependent PDEs has focused on implicit multi-step or diagonally-implicit multi-stage temporal discretizations. In this paper, we consider monolithic multigrid preconditioners for fully-implicit…

Numerical Analysis · Mathematics 2023-02-28 Razan Abu-Labdeh , Scott MacLachlan , Patrick E. Farrell

In recent years, many positivity-preserving schemes for initial value problems have been constructed by modifying a Runge--Kutta (RK) method by weighting the right-hand side of the system of differential equations with solution-dependent…

Numerical Analysis · Mathematics 2025-02-26 Thomas Izgin , David I. Ketcheson , Andreas Meister

Spatiotemporal prediction is important in solving natural problems and processing video frames, especially in weather forecasting and human action recognition. Recent advances attempt to incorporate prior physical knowledge into the deep…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Xuanle Zhao , Yue Sun , Ziyi Wang , Bo Xu , Tielin Zhang

Fully implicit timestepping methods have several potential advantages for atmosphere/ocean simulation. First, being unconditionally stable, they degrade more gracefully as the Courant number increases, typically requiring more solver…

Numerical Analysis · Mathematics 2025-10-16 Werner Bauer , Colin J. Cotter

Explicit Runge-Kutta (RK) integration of hyperbolic initial-boundary value problems with time-dependent Dirichlet data often displays order reduction: the observed convergence order falls below the nominal order because the stage structure…

Numerical Analysis · Mathematics 2026-04-13 Giorgio Maria Cavallazzi , Miguel Pérez Cuadrado , Alfredo Pinelli

There is a growing interest in investigating numerical approximations of the water wave equation in recent years, whereas the lack of rigorous analysis of its time discretization inhibits the design of more efficient algorithms. In this…

Numerical Analysis · Mathematics 2017-12-14 Lei Li , Jian-Guo Liu , Zibu Liu , Yi Yang , Zhennan Zhou