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We propose a better method to determine the stability region of an L-stable implicit-explicit Runge-Kutta scheme. This method always provides the correct result, while other methods sometimes give wrong result. It is useful in the analysis…

Numerical Analysis · Mathematics 2016-06-03 Shu-Chao Duan

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

We propose a new probabilistic scheme which combines deep learning techniques with high order schemes for backward stochastic differential equations belonging to the class of Runge-Kutta methods to solve high-dimensional semi-linear…

Numerical Analysis · Mathematics 2023-01-02 Jean-François Chassagneux , Junchao Chen , Noufel Frikha

We consider the solution of large stiff systems of ordinary differential equations with explicit exponential Runge--Kutta integrators. These problems arise from semi-discretized semi-linear parabolic partial differential equations on…

Numerical Analysis · Mathematics 2023-08-24 Kai Bergermann , Martin Stoll

We present an implicit-explicit (IMEX) scheme for semilinear wave equations with strong damping. By treating the nonlinear, nonstiff term explicitly and the linear, stiff part implicitly, we obtain a method which is not only unconditionally…

Numerical Analysis · Mathematics 2024-07-01 Daniel Eckhardt , Marlis Hochbruck , Barbara Verfürth

We note a fact that stiff systems or differential equations that have highly oscillatory solutions cannot be solved efficiently using conventional methods. In this paper, we study two new classes of exponential Runge-Kutta (ERK) integrators…

Numerical Analysis · Mathematics 2023-12-06 Bin Wang , Xianfa Hu , Xinyuan Wu

We study diagonally implicit Runge-Kutta (DIRK) schemes when applied to abstract evolution problems that fit into the Gelfand-triple framework. We introduce novel stability notions that are well-suited to this setting and provide simple,…

Numerical Analysis · Mathematics 2022-05-27 Abner J. Salgado , Ignacio Tomas

We prove first-order convergence of the semi-explicit Euler scheme combined with a finite element discretization in space for elliptic-parabolic problems which are weakly coupled. This setting includes poroelasticity, thermoelasticity, as…

Numerical Analysis · Mathematics 2019-09-10 Robert Altmann , Roland Maier , Benjamin Unger

Several different approaches are proposed for solving fully implicit discretizations of a simplified Boltzmann-Poisson system with a linear relaxation-type collision kernel. This system models the evolution of free electrons in…

Computational Physics · Physics 2020-07-15 M. Paul Laiu , Zheng Chen , Cory D. Hauck

The demand for substantial increases in the spatial resolution of global weather- and climate- prediction models makes it necessary to use numerically efficient and highly scalable algorithms to solve the equations of large scale…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-06-16 Eike H. Mueller , Robert Scheichl

In this article we present a novel and general methodology for building second order finite volume implicit-explicit (IMEX) numerical schemes for solving two dimensional financial parabolic PDEs with mixed derivatives. In particular,…

In this paper, we propose an efficient exponential integrator finite element method for solving a class of semilinear parabolic equations in rectangular domains. The proposed method first performs the spatial discretization of the model…

Numerical Analysis · Mathematics 2022-09-27 Jianguo Huang , Lili Ju , Yuejin Xu

In this paper, we propose linearly implicit and arbitrary high-order conservative numerical schemes for ordinary differential equations with a quadratic invariant. Many differential equations have invariants, and numerical schemes for…

Numerical Analysis · Mathematics 2022-03-03 Shun Sato , Yuto Miyatake , John C. Butcher

An additive Runge-Kutta method is used for the time stepping, which integrates the linear stiff terms by an explicit singly diagonally implicit Runge-Kutta (ESDIRK) method and the nonlinear terms by an explicit Runge-Kutta (ERK) method. In…

Numerical Analysis · Mathematics 2024-05-08 Ke Chen , Daniel Appelö , Tracy Babb , Per-Gunnar Martinsson

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

Deterministic solutions of the Boltzmann equation represent a real challenge due to the enormous computational effort which is required to produce such simulations and often stochastic methods such as Direct Simulation Monte Carlo (DSMC)…

Numerical Analysis · Mathematics 2021-07-26 Walter Boscheri , Giacomo Dimarco

In this article we design a finite volume semi-implicit IMEX scheme for the incompressible Navier-Stokes equations on evolving Chimera meshes. We employ a time discretization technique that separates explicit and implicit terms which…

Numerical Analysis · Mathematics 2023-08-08 Michele Giuliano Carlino , Walter Boscheri

We investigate several robust preconditioners for solving the saddle-point linear systems that arise from spatial discretization of unsteady and steady variable-coefficient Stokes equations on a uniform staggered grid. Building on the…

Numerical Analysis · Mathematics 2016-08-24 M. Cai , A. J. Nonaka , J. B. Bell , B. E. Griffith , A. Donev

We present unconditionally energy stable Runge-Kutta (RK) discontinuous Galerkin (DG) schemes for solving a class of fourth order gradient flows. Our algorithm is geared toward arbitrarily high order approximations in both space and time,…

Numerical Analysis · Mathematics 2021-01-05 Hailiang Liu , Peimeng Yin

We present a computational framework for obtaining multidimensional phase-space solutions of systems of non-linear coupled differential equations, using high-order implicit Runge-Kutta Physics- Informed Neural Networks (IRK-PINNs) schemes.…

Machine Learning · Computer Science 2024-09-26 Álvaro Fernández Corral , Nicolás Mendoza , Armin Iske , Andrey Yachmenev , Jochen Küpper