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In this paper, we develop new high-order numerical methods for hyperbolic systems of nonlinear partial differential equations (PDEs) with uncertainties. The new approach is realized in the semi-discrete finite-volume framework and is based…

In this paper we extensively study the stochastic Galerkin scheme for uncertain systems of conservation laws, which appears to produce oscillations already for a simple example of the linear advection equation with Riemann initial data.…

Numerical Analysis · Mathematics 2020-08-26 Louisa Schlachter , Florian Schneider , Oliver Kolb

This paper presents a numerical framework for the low-rank approximation of the solution to three-dimensional parabolic problems. The key contribution of this work is the tensorization process based on a tensor-train reformulation of the…

Numerical Analysis · Mathematics 2025-09-15 Gianmarco Manzini , Tommaso Sorgente

In this paper, A new sixth-order weighted essentially non-oscillatory (WENO) scheme, refered as the WENO-6, is proposed in the finite volume framework for the hyperbolic conservation laws. Instead of selecting one stencil for each cell in…

Numerical Analysis · Mathematics 2017-01-24 Fengxiang Zhao , Liang Pan , Zheng Li , Shuanghu Wang

In this paper, a maximum-principle-satisfying finite volume compact scheme is proposed for solving scalar hyperbolic conservation laws. The scheme combines WENO schemes (Weighted Essentially Non-Oscillatory) with a class of compact schemes…

Numerical Analysis · Mathematics 2014-05-09 Yan Guo , Tao Xiong , Yufeng Shi

In this paper, we propose a high order residual distribution conservative finite difference scheme for solving steady state conservation laws. A new type of WENO (weighted essentially non-oscillatory) termed as WENO-ZQ integration is used…

Numerical Analysis · Mathematics 2018-10-17 Jianfang Lin , Rémi Abgrall , Jianxian Qiu

We present a neural network-based method for learning scalar hyperbolic conservation laws. Our method replaces the traditional numerical flux in finite volume schemes with a trainable neural network while preserving the conservative…

This work aims to extend the well-known high-order WENO finite-difference methods for systems of conservation laws to nonconservative hyperbolic systems. The main difficulty of these systems both from the theoretical and the numerical…

Numerical Analysis · Mathematics 2025-03-04 B. Ren , C. Parés

High-dimensional partial differential equations (PDEs) are ubiquitous in economics, science and engineering. However, their numerical treatment poses formidable challenges since traditional grid-based methods tend to be frustrated by the…

Machine Learning · Statistics 2021-07-20 Lorenz Richter , Leon Sallandt , Nikolas Nüsken

We introduce (U)NFV, a modular neural network architecture that generalizes classical finite volume (FV) methods for solving hyperbolic conservation laws. Hyperbolic partial differential equations (PDEs) are challenging to solve,…

In this paper, a fifth-order Hermite weighted essentially non-oscillatory (HWENO) scheme with artificial linear weights is proposed for one and two dimensional hyperbolic conservation laws, where the zeroth-order and the first-order moments…

Numerical Analysis · Mathematics 2020-07-15 Zhuang Zhao , Jianxian Qiu

This paper is concerned with generalized polynomial chaos (gPC) approximation for a general system of quasilinear hyperbolic conservation laws with uncertainty. The one-dimensional (1D) hyperbolic system is first symmetrized with the aid of…

Numerical Analysis · Mathematics 2019-02-12 Kailiang Wu , Huazhong Tang , Dongbin Xiu

Finite volume methods are popular tools for solving time-dependent partial differential equations, especially hyperbolic conservation laws. Over the past 40 years a popular way of enlarging their robustness was the enforcement of global or…

Numerical Analysis · Mathematics 2023-02-20 Simon-Christian Klein , Thomas Sonar

In the mechanics of inviscid conservative fluids, it is classical to generate the equations of dynamics by formulating with adequate variables, that the pressure integral calculated in the time-space domain corresponding to the motion of…

Classical Physics · Physics 2008-07-23 Henri Gouin , Jean-François Debieve

Stochastic spectral methods have become a popular technique to quantify the uncertainties of nano-scale devices and circuits. They are much more efficient than Monte Carlo for certain design cases with a small number of random parameters.…

Computational Engineering, Finance, and Science · Computer Science 2016-03-22 Zheng Zhang , Tsui-Wei Weng , Luca Daniel

High-order reconstruction schemes for the solution of hyperbolic conservation laws in orthogonal curvilinear coordinates are revised in the finite volume approach. The formulation employs a piecewise polynomial approximation to the…

Computational Physics · Physics 2015-06-19 A. Mignone

This paper presents a highly robust third-order accurate finite volume weighted essentially non-oscillatory (WENO) method for special relativistic hydrodynamics on unstructured triangular meshes. We rigorously prove that the proposed method…

Numerical Analysis · Mathematics 2022-07-20 Yaping Chen , Kailiang Wu

A novel hybrid spectral difference/embedded finite volume method is introduced in order to apply a discontinuous high-order method for large scale engineering applications involving discontinuities in the flows with complex geometries. In…

Numerical Analysis · Mathematics 2015-05-20 Jung J. Choi

Recently, the targeted ENO (TENO) schemes give a novel framework to keep optimal high-order spatial reconstruction wherever discontinuity is deemed to be vanished, including at smooth critical points, and to avoid oscillations by completely…

Computational Physics · Physics 2018-11-07 Fan Zhang , Jun Liu , Huaibao Zhang , Chunguang Xu

We illustrate that numerical solutions of high order finite volume Hermite weighted essentially non-oscillatory (HWENO) scheme for some nonconvex conservation laws perform poorly or converge to the entropy solution in a slow speed. The…

Numerical Analysis · Mathematics 2017-09-18 Xiaofeng Cai , Jianxian Qiu , Jing-Mei Qiu