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This paper investigates the competitiveness of semi-implicit Runge-Kutta (RK) and spectral deferred correction (SDC) time-integration methods up to order six for incompressible Navier-Stokes problems in conjunction with a high-order…

Numerical Analysis · Mathematics 2022-10-03 Montadhar Guesmi , Martina Grotteschi , Jörg Stiller

We consider Implicit-Explicit (IMEX) Runge-Kutta (R-K) schemes for hyperbolic systems with stiff relaxation in the so-called diffusion limit. In such regime the system relaxes towards a convection-diffusion equation. The first objective of…

Numerical Analysis · Mathematics 2015-05-30 S. Boscarino , L. Pareschi , G. Russo

In this paper, two novel classes of implicit exponential Runge-Kutta (ERK) methods are studied for solving highly oscillatory systems. First of all, we analyze the symplectic conditions of two kinds of exponential integrators, and present a…

Numerical Analysis · Mathematics 2023-12-05 Xianfa Hu , Wansheng Wang , Bin Wang , Yonglei Fang

Data-driven modeling of nonlinear dynamical systems is often hampered by measurement noise. We propose a denoising framework, called Runge-Kutta and Total Variation Based Implicit Neural Representation (RKTV-INR), that represents the state…

Machine Learning · Computer Science 2025-09-18 Jiaqi Yao , Lewis Mitchell , John Maclean , Hemanth Saratchandran

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

Conservation properties of iterative methods applied to implicit finite volume discretizations of nonlinear conservation laws are analyzed. It is shown that any consistent multistep or Runge-Kutta method is globally conservative. Further,…

Numerical Analysis · Mathematics 2021-06-21 Philipp Birken , Viktor Linders

We propose an experimental study of adaptive time-stepping methods for efficient modeling of the aggregation-fragmentation kinetics. Precise modeling of this phenomena usually requires utilization of the large systems of nonlinear ordinary…

Numerical Analysis · Mathematics 2025-01-20 Sergey A. Matveev , Viktor Zhilin , Alexander P. Smirnov

We randomize the implicit two-stage Runge-Kutta scheme in order to improve the rate of convergence (with respect to a deterministic scheme) and stability of the approximate solution (with respect to the solution generated by the explicit…

Numerical Analysis · Mathematics 2025-01-17 Tomasz Bochacik , Paweł Przybyłowicz

The integration of aerodynamic drag is a fundamental step in simulating dust dynamics in hydrodynamical simulations. We propose a novel integration scheme, designed to be compatible with Strang splitting techniques, which allows for the…

Instrumentation and Methods for Astrophysics · Physics 2025-11-12 Giovanni Tedeschi-Prades , Til Birnstiel , Klaus Dolag , Barbara Ercolano , Mark Hutchison

This work introduces a new class of Runge-Kutta methods for solving nonlinearly partitioned initial value problems. These new methods, named nonlinearly partitioned Runge-Kutta (NPRK), generalize existing additive and component-partitioned…

Numerical Analysis · Mathematics 2025-04-07 Tommaso Buvoli , Ben S. Southworth

In our recent work on iterative computation in hardware, we showed that arbitrary-precision solvers can perform more favorably than their traditional arithmetic equivalents when the latter's precisions are either under- or over-budgeted for…

Numerical Analysis · Mathematics 2020-10-20 He Li , Ian McInerney , James J. Davis , George A. Constantinides

Relaxation Runge-Kutta methods reproduce a fully discrete dissipation (or conservation) of entropy for entropy stable semi-discretizations of nonlinear conservation laws. In this paper, we derive the discrete adjoint of relaxation…

Numerical Analysis · Mathematics 2021-07-27 Mario J. Bencomo , Jesse Chan

This work introduces a general framework for constructing high-order, linearly stable, partitioned solvers for multiphysics problems from a monolithic implicit-explicit Runge-Kutta (IMEX-RK) discretization of the semi-discrete equations.…

Numerical Analysis · Mathematics 2019-02-20 Daniel Z. Huang , Per-Olof Persson , Matthew J. Zahr

Perturbed Runge--Kutta methods (also referred to as downwind Runge--Kutta methods) can guarantee monotonicity preservation under larger step sizes relative to their traditional Runge--Kutta counterparts. In this paper we study, the question…

Numerical Analysis · Mathematics 2018-02-16 Inmaculada Higueras , David I. Ketcheson , Tihamér A. Kocsis

We provide a note on continuous-stage Runge-Kutta methods (csRK) for solving initial value problems of first-order ordinary differential equations. Such methods, as an interesting and creative extension of traditional Runge-Kutta (RK)…

Numerical Analysis · Mathematics 2018-05-28 Wensheng Tang

This work presents algorithms for the efficient implementation of discontinuous Galerkin methods with explicit time stepping for acoustic wave propagation on unstructured meshes of quadrilaterals or hexahedra. A crucial step towards…

Numerical Analysis · Computer Science 2019-03-06 Svenja Schoeder , Katharina Kormann , Wolfgang Wall , Martin Kronbichler

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

In this work, an approximate family of implicit multiderivative Runge-Kutta (MDRK) time integrators for stiff initial value problems is presented. The approximation procedure is based on the recent Approximate Implicit Taylor method (Baeza…

Numerical Analysis · Mathematics 2023-02-07 Jeremy Chouchoulis , Jochen Schütz

Multirate time integration methods apply different step sizes to resolve different components of the system based on the local activity levels. This local selection of step sizes allows increased computational efficiency while achieving the…

Numerical Analysis · Computer Science 2021-12-22 Arash Sarshar , Steven Roberts , Adrian Sandu

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