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Solving time-dependent partial differential equations (PDEs) that exhibit sharp gradients or local singularities is computationally demanding, as traditional physics-informed neural networks (PINNs) often suffer from inefficient point…

Numerical Analysis · Mathematics 2026-01-27 Beining Xu , Haijun Yu , Jiayu Zhai , Kejun Tang , Xiaoliang Wan

The splitting method is a powerful method for solving partial differential equations. Various splitting methods have been designed to separate different physics, nonlinearities, and so on. Recently, a new splitting approach has been…

Numerical Analysis · Mathematics 2023-03-22 Yalchin Efendiev , Wing Tat Leung , Wenyuan Li , Zecheng Zhang

We present an adaptive finite element method for the incompressible Navier--Stokes equations based on a standard splitting scheme (the incremental pressure correction scheme). The presented method combines the efficiency and simplicity of a…

Numerical Analysis · Mathematics 2012-05-15 Kristoffer Selim , Anders Logg , Mats G. Larson

We present a parametric family of semi-implicit second order accurate numerical methods for non-conservative and conservative advection equation for which the numerical solutions can be obtained in a fixed number of forward and backward…

Numerical Analysis · Mathematics 2023-12-01 Peter Frolkovič , Svetlana Krišková , Michaela Rohová , Michal Žeravý

We present a new strategy for solving stiff ODEs with explicit methods. By adaptively taking a small number of stabilizing small explicit time steps when necessary, a stiff ODE system can be stabilized enough to allow for time steps much…

Numerical Analysis · Mathematics 2012-05-15 Kenneth Eriksson , Claes Johnson , Anders Logg

In this paper, we present and analyze a linear fully discrete second order scheme with variable time steps for the phase field crystal equation. More precisely, we construct a linear adaptive time stepping scheme based on the second order…

Numerical Analysis · Mathematics 2023-05-30 Dianming Hou , Zhonghua Qiao

This paper proposes an adaptive time-stepping mothods for stochastic diffusion systems whose drift and diffusion coefficients are locally Lipschitz continuous and may exhibit polynomial growth. By controlling the growth of both the drift…

Numerical Analysis · Mathematics 2026-02-09 Xueqi Wen , Guozhen Li , Yuanping Cui , Xiaoyue Li

For conventional smoothed particle hydrodynamics (SPH), obtaining the static solution of a problem is time-consuming. To address this drawback, we propose an efficient dynamic relaxation method by adding large artificial-viscosity-based…

Computational Engineering, Finance, and Science · Computer Science 2021-03-17 Yujie Zhu , Chi Zhang , Xiangyu Hu

In this paper we construct a third order method for solving additively split autonomous stiff systems of ordinary differential equations. The constructed additive method is L-stable with respect to the implicit part and allows to use an…

Numerical Analysis · Mathematics 2009-02-24 Evgeny Novikov , Anton Tuzov

Numerical solutions of hyperbolic partial differential equations(PDEs) are ubiquitous in science and engineering. Method of lines is a popular approach to discretize PDEs defined in spacetime, where space and time are discretized…

Mathematical Software · Computer Science 2020-11-24 Milinda Fernando , Hari Sundar

We consider high-order splitting schemes for large-scale differential Riccati equations. Such equations arise in many different areas and are especially important within the field of optimal control. In the large-scale case, it is critical…

Optimization and Control · Mathematics 2018-08-14 Tony Stillfjord

Implicit time-stepping for advection is applied locally in space and time where Courant numbers are large, but standard explicit time-stepping is used for the remaining solution which is typically the majority. This adaptively implicit…

Fluid Dynamics · Physics 2024-06-14 Hilary Weller , Christian Kuehnlein , Piotr K. Smolarkiewicz

We consider the use of adaptive timestepping to allow a strong explicit Euler-Maruyama discretisation to reproduce dynamical properties of a class of nonlinear stochastic differential equations with a unique equilibrium solution and…

Numerical Analysis · Mathematics 2017-06-13 Cónall Kelly , Alexandra Rodkina , Eeva Maria Rapoo

In recent years, SPDEs have become a well-studied field in mathematics. With their increase in popularity, it becomes important to efficiently approximate their solutions. Thus, our goal is a contribution towards the development of…

Numerical Analysis · Mathematics 2024-01-17 Evelyn Buckwar , Ana Djurdjevac , Monika Eisenmann

We consider systems of ordinary differential equations with multiple scales in time. In general, we are interested in the long time horizon of a slow variable that is coupled to solution components that act on a fast scale. Although the…

Numerical Analysis · Mathematics 2021-04-28 Leopold Lautsch , Thomas Richter

We propose in this paper efficient first/second-order time-stepping schemes for the evolutional Navier-Stokes-Nernst-Planck-Poisson equations. The proposed schemes are constructed using an auxiliary variable reformulation and sophisticated…

Numerical Analysis · Mathematics 2023-05-17 Xiaolan Zhou , Chuanju Xu

In this paper, we propose and analyze an adaptive time-stepping fully discrete scheme which possesses the optimal strong convergence order for the stochastic nonlinear Schr\"odinger equation with multiplicative noise. Based on the splitting…

Numerical Analysis · Mathematics 2022-12-06 Chuchu Chen , Tonghe Dang , Jialin Hong

We consider the construction of semi-implicit linear multistep methods which can be applied to time dependent PDEs where the separation of scales in additive form, typically used in implicit-explicit (IMEX) methods, is not possible. As…

Numerical Analysis · Mathematics 2020-01-14 Giacomo Albi , Lorenzo Pareschi

A time-fractional Allen-Cahn equation with volume constraint is first proposed by introducing a nonlocal time-dependent Lagrange multiplier. Adaptive linear second-order energy stable schemes are developed for the proposed model by…

Numerical Analysis · Mathematics 2020-12-23 Bingquan Ji , Hong-lin Liao , Yuezheng Gong , Luming Zhang

Solving partial differential equations (PDEs) within the framework of probabilistic numerics offers a principled approach to quantifying epistemic uncertainty arising from discretization. By leveraging Gaussian process regression and…

Machine Learning · Statistics 2025-08-18 Akshay Thakur , Sawan Kumar , Matthew Zahr , Souvik Chakraborty