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相关论文: General-domain FC-based shock-dynamics solver II: …

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This contribution, Part I in a two-part article series, presents a general-domain version of the FC-SDNN (Fourier Continuation Shock-detecting Neural Network) spectral scheme for the numerical solution of nonlinear conservation laws, which…

数值分析 · 数学 2025-06-23 Oscar P. Bruno , Daniel V. Leibovici

This paper presents a spectral scheme for the numerical solution of nonlinear conservation laws in non-periodic domains under arbitrary boundary conditions. The approach relies on the use of the Fourier Continuation (FC) method for spectral…

数值分析 · 数学 2021-11-03 Oscar P. Bruno , Jan S. Hesthaven , Daniel V. Leibovici

This is the second part to our companion paper [18]. Herein, we generalize to two space dimensions the C-method developed in [20,18] for adding localized, space-time smooth artificial viscosity to nonlinear systems of conservation laws that…

计算物理 · 物理学 2019-03-04 Raaghav Ramani , Jon Reisner , Steve Shkoller

Pseudospectral schemes are a class of numerical methods capable of solving smooth problems with high accuracy thanks to their exponential convergence to the true solution. When applied to discontinuous problems, such as fluid shocks and…

数值分析 · 数学 2019-10-03 Joanna Piotrowska , Jonah M. Miller

This work aims to predict blood flow with non-Newtonian viscosity in stenosed arteries using convolutional neural network (CNN) surrogate models. An alternating Schwarz domain decomposition method is proposed which uses CNN-based subdomain…

Due to the limited cell resolution in the representation of flow variables, a piecewise continuous initial reconstruction with discontinuous jump at a cell interface is usually used in modern computational fluid dynamics methods. Starting…

数学物理 · 物理学 2010-09-23 Kun Xu , Quanhua Sun , Pubing Yu

The goal of this work is to develop a new universal high order subroutine for shock boundary layer interaction. First, an effective shock/discontinuity detector has been developed.The detector has two steps.The first step is to check the…

计算物理 · 物理学 2014-02-25 M. Oliveria , P. Lu , X. Liu , C. Liu

A new penalty-free neural network method, PFNN-2, is presented for solving partial differential equations, which is a subsequent improvement of our previously proposed PFNN method [1]. PFNN-2 inherits all advantages of PFNN in handling the…

数值分析 · 数学 2022-05-03 Hailong Sheng , Chao Yang

We propose a decoupled divergence-free neural networks basis (Decoupled-DFNN) method for solving incompressible flow problems, including the Stokes and Navier-Stokes equations. To ensure the divergence free property exactly, the velocity…

数值分析 · 数学 2026-03-19 Jinbao Cheng , Jianguo Huang , Haoqin Wang , Tao Zhou

In this work, using a unified framework consisting of third-order accurate discontinuous Galerkin schemes, we perform a comparison between five different numerical approaches to the free-surface shallow flow simulation on bottom steps.…

计算物理 · 物理学 2019-12-17 Valerio Caleffi , Alessandro Valiani , Gang Li

In this first part of two papers, we extend the C-method developed in [40] for adding localized, space-time smooth artificial viscosity to nonlinear systems of conservation laws that propagate shock waves, rarefaction waves, and contact…

计算物理 · 物理学 2019-05-01 Raaghav Ramani , Jon Reisner , Steve Shkoller

We prove that for the two-dimensional steady complete compressible Euler system, with given uniform upcoming supersonic flows, the following three fundamental flow patterns (special solutions) in gas dynamics involving transonic shocks are…

偏微分方程分析 · 数学 2010-04-13 Beixiang Fang , Li Liu , Hairong Yuan

We present a hybrid filter that is only applied to the approximation at the final time and allows for reducing errors away from a shock as well as near a shock. It is designed for discontinuous Galerkin approximations to PDEs and combines a…

数值分析 · 数学 2025-03-17 Soraya Terrab , Samy Wu Fung , Jennifer K. Ryan

Simulating discontinuities is a long standing problem especially for shock waves with strong nonlinear feather. Despite being a promising method, the recently developed physics-informed neural network (PINN) is still weak for calculating…

流体动力学 · 物理学 2025-06-24 Li Liu , Shengping Liu , Hui Xie , Fansheng Xiong , Tengchao Yu , Mengjuan Xiao , Lufeng Liu , Heng Yong

Deep Neural Networks (DNNs) are powerful tools that have shown extraordinary results in many scenarios, ranging from pattern recognition to complex robotic problems. However, their intricate designs and lack of transparency raise safety…

人工智能 · 计算机科学 2023-12-12 Luca Marzari , Gabriele Roncolato , Alessandro Farinelli

This paper presents a fast "two-dimensional Fourier Continuation" (2D-FC) method for the construction of biperiodic extensions of smooth, non-periodic functions defined over general two-dimensional (2D) domains, including domains with…

数值分析 · 数学 2026-04-27 Oscar P. Bruno , Allen Yang

We present fast, spatially dispersionless and unconditionally stable high-order solvers for Partial Differential Equations (PDEs) with variable coefficients in general smooth domains. Our solvers, which are based on (i) A certain "Fourier…

数值分析 · 数学 2012-09-05 O. P. Bruno , A. Prieto

A fundamental question in fluid dynamics concerns the formation of discontinuous shock waves from smooth initial data. We prove that from smooth initial data, smooth solutions to the 2d Euler equations in azimuthal symmetry form a first…

偏微分方程分析 · 数学 2021-07-01 Tristan Buckmaster , Theodore D. Drivas , Steve Shkoller , Vlad Vicol

The stable and accurate approximation of discontinuities such as shocks on a finite computational mesh is a challenging task. Detection of shocks or strong discontinuities in the flow solution is typically achieved through a priori troubled…

数值分析 · 数学 2020-10-28 Andrea D. Beck , Jonas Zeifang , Anna Schwarz , David G. Flad

We introduce a new methodology for adding localized, space-time smooth, artificial viscosity to nonlinear systems of conservation laws which propagate shock waves, rarefactions, and contact discontinuities, which we call the $C$-method. We…

计算物理 · 物理学 2015-06-04 Jon Reisner , Jonathan Serencsa , Steve Shkoller
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