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The paper proposes a second-order accurate direct Eulerian generalized Riemann problem (GRP) scheme for the radiation hydrodynamical equations (RHE) in the zero diffusion limit. The difficulty comes from no explicit expression of the flux…

Numerical Analysis · Mathematics 2017-04-03 Yangyu Kuang , Huazhong Tang

This paper proposes a second-order accurate direct Eulerian generalized Riemann problem (GRP) scheme for the ten-moment Gaussian closure equations with source terms. The generalized Riemann invariants associated with the rarefaction waves,…

Numerical Analysis · Mathematics 2024-07-08 Jiangfu Wang , Huazhong Tang

The paper proposes a second-order accurate direct Eulerian generalized Riemann problem (GRP) scheme for the spherically symmetric general relativistic hydrodynamical (RHD) equations and a second-order accurate discretization for the…

Numerical Analysis · Mathematics 2016-07-29 Kailiang Wu , Huazhong Tang

In this paper, a second-order generalized Riemann problem (GRP) solver is developed for a two-layer thin film model. Extending the first-order Godunov approach, the solver is used to construct a temporal-spatial coupled second-order…

Numerical Analysis · Mathematics 2025-05-27 Rahul Barthwal , Christian Rohde , Yue Wang

The Generalized Riemann Problems (GRP) for nonlinear hyperbolic systems of balance laws in one space dimension are now well-known and can be formulated as follows: Given initial-data which are smooth on two sides of a discontinuity,…

Numerical Analysis · Mathematics 2013-03-13 Jianzhen Qian , Jiequan Li , Shuanghu Wang

A second-order accurate and robust numerical scheme is developed for the Kapila model to simulate compressible multiphase flows. The scheme is formulated within the finite volume framework with the generalized Riemann problem (GRP) solver…

Numerical Analysis · Mathematics 2025-06-10 Tuowei Chen , Zhifang Du

In this paper we study the convergence of a second order finite volume approximation of the scalar conservation law. This scheme is based on the generalized Riemann problem (GRP) solver. We firstly investigate the stability of the GRP…

Numerical Analysis · Mathematics 2024-01-09 Maria Lukacova-Medvidova , Yuhuan Yuan

This work focuses on the Riemann problem of Euler equations with global constant initial conditions and a single-point heating source, which comes from the physical problem of heating one-dimensional inviscid compressible constant flow. In…

Analysis of PDEs · Mathematics 2022-05-25 Changsheng Yu , Chengliang Feng , Zhiqiang Zeng , Tiegang Liu

In the finite volume framework, a Lax-Wendrof type second-order flux solver for the compressible Navier-Stokes equations is proposed by utilizing a hyperbolic relaxation model. The flux solver is developed by applying the generalized…

Numerical Analysis · Mathematics 2025-03-03 Tuowei Chen , Zhifang Du

A Gaussian process (GP)-based methodology is proposed to emulate complex dynamical computer models (or simulators). The method relies on emulating the numerical flow map of the system over an initial (short) time step, where the flow map is…

Methodology · Statistics 2024-11-26 Hossein Mohammadi , Peter Challenor , Marc Goodfellow

We study an Eulerian droplet model which can be seen as the pressureless gas system with a source term, a subsystem of this model and the inviscid Burgers equation with source term. The condition for loss of regularity of a solution to…

Analysis of PDEs · Mathematics 2018-09-17 Sana Keita , Yves Bourgault

The Riemann problem, and the associated generalized Riemann problem, are increasingly seen as the important building blocks for modern higher order Godunov-type schemes. In the past, building a generalized Riemann problem solver was seen as…

Numerical Analysis · Mathematics 2018-10-17 Dinshaw S. Balsara , Jiequan Li , Gino I. Montecinos

We propose Riemannian Flow Matching (RFM), a simple yet powerful framework for training continuous normalizing flows on manifolds. Existing methods for generative modeling on manifolds either require expensive simulation, are inherently…

Machine Learning · Computer Science 2024-02-27 Ricky T. Q. Chen , Yaron Lipman

One-dimensional (1D) blood flow simulations are extensively used in cardiovascular research due to their computational efficiency and effectiveness in analyzing pulse wave dynamics. Despite their versatility and simplicity, there is a lack…

Quantitative Methods · Quantitative Biology 2025-08-27 Daehyun Kim , Jeffrey Tithof

This paper addresses the problems of spline interpolation on smooth Riemannian manifolds, with or without the inclusion of least-squares fitting. Our unified approach utilizes gradient flows for successively connected curves or networks,…

Optimization and Control · Mathematics 2025-10-29 Chun-Chi Lin , Dung The Tran

We are interested in a reduced order method for the efficient simulation of blood flow in arteries. The blood dynamics is modeled by means of the incompressible Navier-Stokes equations. Our algorithm is based on an approximated…

Numerical Analysis · Mathematics 2021-04-07 Luca Pegolotti , Martin Pfaller , Alison Marsden , Simone Deparis

In this paper, we propose a simple acceleration scheme for Riemannian gradient methods by extrapolating iterates on manifolds. We show when the iterates are generated from Riemannian gradient descent method, the accelerated scheme achieves…

Optimization and Control · Mathematics 2022-08-16 Andi Han , Bamdev Mishra , Pratik Jawanpuria , Junbin Gao

We introduce a generalization of Glimm's random choice method, which provides us with an approximation of entropy solutions to quasilinear hyperbolic system of balance laws. The flux-function and the source term of the equations may depend…

Analysis of PDEs · Mathematics 2007-05-23 John M. Hong , Philippe G. LeFloch

This paper proposes a new non-oscillatory {\em energy-splitting} conservative algorithm for computing multi-fluid flows in the Eulerian framework. In comparison with existing multi-fluid algorithms in literatures, it is shown that the mass…

Fluid Dynamics · Physics 2018-04-04 Xin Lei , Jiequan Li

In the Euclidean setting, the proximal gradient method and its accelerated variants are a class of efficient algorithms for optimization problems with decomposable objective. In this paper, we develop a Riemannian proximal gradient method…

Optimization and Control · Mathematics 2021-06-01 Wen Huang , Ke Wei
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