English
Related papers

Related papers: Local Characteristic Decomposition Based Central-U…

200 papers

This paper proposes a novel fault detection and isolation (FDI) scheme for distributed parameter systems modeled by a class of parabolic partial differential equations (PDEs) with nonlinear uncertain dynamics. A key feature of the proposed…

Systems and Control · Electrical Eng. & Systems 2022-03-31 Jingting Zhang , Chengzhi Yuan , Wei Zeng , Cong Wang

In this paper, a new family of implicit compact finite difference schemes for computation of unsteady convection-diffusion equation with variable convection coefficient is proposed. The schemes are fourth order accurate in space and second…

Mathematical Physics · Physics 2012-01-17 Shuvam Sen

A trademark of nonlinear, time-dependent, convection-dominated problems is the spontaneous formation of non-smooth macro-scale features, like shock discontinuities and non-differentiable kinks, which pose a challenge for high-resolution…

Numerical Analysis · Mathematics 2025-10-20 Eitan Tadmor

We present a nonlinear dynamical approximation method for time-dependent Partial Differential Equations (PDEs). The approach makes use of parametrized decoder functions, and provides a general, and principled way of understanding and…

Numerical Analysis · Mathematics 2025-05-20 Daan Bon , Benjamin Caris , Olga Mula

This article performs a unified convergence analysis of a variety of numerical methods for a model of the miscible displacement of one incompressible fluid by another through a porous medium. The unified analysis is enabled through the…

Numerical Analysis · Mathematics 2018-03-07 Jérôme Droniou , Robert Eymard , Alain Prignet , Kyle S. Talbot

We have proposed a new High Resolution Shock Capturing (HRSC) scheme for Special Relativistic Hydrodynamics (SRHD) based on the semidiscrete central Godunov-type schemes and a modified Weighted Essentially Non-oscillatory (WENO) data…

Astrophysics · Physics 2007-05-23 Tanvir Rahman , R. B. Moore

This paper presents a data-driven finite volume method for solving 1D and 2D hyperbolic partial differential equations. This work builds upon the prior research incorporating a data-driven finite-difference approximation of smooth solutions…

Numerical Analysis · Mathematics 2025-02-25 Guillaume de Romémont , Florent Renac , Jorge Nunez , Francisco Chinesta

We develop new dynamically orthogonal tensor methods to approximate multivariate functions and the solution of high-dimensional time-dependent nonlinear partial differential equations (PDEs). The key idea relies on a hierarchical…

Numerical Analysis · Mathematics 2020-01-29 Alec Dektor , Daniele Venturi

Partial differential equations (PDEs) that fit scientific data can represent physical laws with explainable mechanisms for various mathematically-oriented subjects, such as physics and finance. The data-driven discovery of PDEs from…

Machine Learning · Computer Science 2023-05-29 Yingtao Luo , Qiang Liu , Yuntian Chen , Wenbo Hu , Tian Tian , Jun Zhu

A local approach to the time integration of PDEs by exponential methods is proposed, motivated by theoretical estimates by A.Iserles on the decay of off-diagonal terms in the exponentials of sparse matrices. An overlapping domain…

Numerical Analysis · Mathematics 2015-05-12 Luca Bonaventura

The central-upwind flux is a widely used numerical flux function for local conservation laws. It has been investigated by Kurganov and Polizzi (2009) for a specific nonlocal conservation law and can be derived from a fully-discrete…

Numerical Analysis · Mathematics 2026-02-10 Jan Friedrich , Samala Rathan , Sanjibanee Sudha

This work presents the design of nonlinear stabilization techniques for the finite element discretization of Euler equations in both steady and transient form. Implicit time integration is used in the case of the transient form. A…

Numerical Analysis · Mathematics 2020-08-26 Santiago Badia , Jesús Bonilla , Sibusiso Mabuza , John N. Shadid

Parabolic partial differential equations (PDEs) appear in many disciplines to model the evolution of various mathematical objects, such as probability flows, value functions in control theory, and derivative prices in finance. It is often…

Machine Learning · Computer Science 2024-07-18 Xingzi Xu , Ali Hasan , Jie Ding , Vahid Tarokh

In this paper, we propose stochastic structure-preserving schemes to compute the effective diffusivity for particles moving in random flows. We first introduce the motion of particles using the Lagrangian formulation, which is modeled by…

Numerical Analysis · Mathematics 2020-08-24 Junlong Lyu , Zhongjian Wang , Jack Xin , Zhiwen Zhang

Two-level domain decomposition (DD) methods are very powerful techniques for the efficient numerical solution of partial differential equations (PDEs). A two-level domain decomposition method requires two main components: a one-level…

Numerical Analysis · Mathematics 2021-04-22 Gabriele Ciaramella , Tommaso Vanzan

Domain decomposition methods are used for approximate solving boundary problems for partial differential equations on parallel computing systems. Specific features of unsteady problems are taken into account in the most complete way in…

Numerical Analysis · Computer Science 2011-05-18 Petr N. Vabishchevich

We introduce a new class of numerical schemes which allow for low regularity approximations to the expectation $ \mathbb{E}(|u_{k}(\tau, v^{\eta})|^2)$, where $u_k$ denotes the $k$-th Fourier coefficient of the solution $u$ of the…

Probability · Mathematics 2026-01-27 Yvonne Alama Bronsard , Yvain Bruned , Katharina Schratz

We consider a hydrodynamic-type system of balance equations which is closed by the dynamic equation of state taking into account the effects of spatial nonlocality. Symmetry and local conservation laws of this system are studied. A system…

Pattern Formation and Solitons · Physics 2013-08-01 Vsevolod Vladimirov , Czesław Maczka , Artur Sergyeyev , Sergiy Skurativskyi

We propose a methodology that combines generative latent diffusion models with physics-informed machine learning to generate solutions of parametric partial differential equations (PDEs) conditioned on partial observations, which includes,…

Machine Learning · Computer Science 2026-02-11 Davide Gallon , Philippe von Wurstemberger , Patrick Cheridito , Arnulf Jentzen

We develop second-order path-conservative central-upwind (PCCU) schemes for the hyperbolic shallow water linearized moment equations (HSWLME), which are an extension of standard depth-averaged models for free-surface flows. The proposed…

Numerical Analysis · Mathematics 2025-05-30 Yangyang Cao , Qian Huang , Julian Koellermeier , Alexander Kurganov , Yongle Liu