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A novel numerical approach to solving the shallow-water equations on the sphere using high-order numerical discretizations in both space and time is proposed. A space-time tensor formalism is used to express the equations of motion…

Numerical Analysis · Mathematics 2021-11-12 Stéphane Gaudreault , Martin Charron , Valentin Dallerit , Mayya Tokman

A numerical model and parallel software for 3D simulations of granular flows have been developed based on the Lagrangian particle (LP) method [R.Samulyak, X. Wang, H.-C. Chen, Lagrangian particle method for compressible fluid dynamics, J.…

Computational Physics · Physics 2022-06-29 Mario Zepeda , Roman Samulyak

The advantage of particle Lagrangian methods in computational fluid dynamics is that advection is accurately modeled. However, this complicates the calculation of space derivatives. If a mesh is employed, it must be updated at each time…

Fluid Dynamics · Physics 2017-01-27 Daniel Duque , Pep Español

A quasi-second order scheme is developed to obtain approximate solutions of the shallow water equationswith bathymetry. The scheme is based on a staggered finite volume scheme for the space discretization:the scalar unknowns are located in…

Numerical Analysis · Mathematics 2021-11-19 R Herbin , J. -C Latché , Y Nasseri , N Therme

This paper proposes a novel consistent {\delta}+- Updated Lagrangian Particle Hydrodynamics (ULPH) model. Although the Smoothed Particle Hydrodynamics (SPH) model has gained recognized achievements, it is afflicted by excessive numerical…

Fluid Dynamics · Physics 2025-11-13 Shi-Xian Wu , Peng-Nan Sun , Xiao-Ting Huang , Yu-Xiang Peng , Andrea Colagrossi

We present a numerical model for the dynamics of thin viscous threads based on a discrete, Lagrangian formulation of the smooth equations. The model makes use of a condensed set of coordinates, called the centerline/spin representation: the…

In this article, we investigate the artificial viscosity and hourglass control algorithms for high-order staggered Lagrangian hydrodynamics(SGH), as proposed in~\cite[Sun et al., 2025]{Sun2025High}. Inspired by the subzonal pressure method…

Numerical Analysis · Mathematics 2025-09-10 Zhiyuan Sun , Jun Liu , Pei Wang

We present an arbitrary updated Lagrangian Material Point Method (A-ULMPM) to alleviate issues, such as the cell-crossing instability and numerical fracture, that plague state of the art Eulerian formulations of MPM, while still allowing…

Graphics · Computer Science 2021-08-03 Haozhe Su , Tao Xue , Chengguizi Han , Mridul Aanjaneya

The Lagrangian formulation for the irrotational wave motion is straightforward and follows from a Lagrangian functional which is the difference between the kinetic and the potential energy of the system. In the case of fluid with constant…

Fluid Dynamics · Physics 2024-06-04 Conor T. Curtin , Rossen I. Ivanov

Accurate long-term predictions of large-scale flow features on planets are crucial for understanding global atmospheric and oceanic systems, necessitating the development of numerical methods that can preserve essential physical structures…

Fluid Dynamics · Physics 2024-09-10 Arnout Franken , Erwin Luesink , Sagy Ephrati , Bernard Geurts

In this work, we discuss some points relevant for stochastic modelling of one- and two-phase turbulent flows. In the framework of stochastic modelling, also referred to PDF approach, we propose a new Langevin model including all viscosity…

Fluid Dynamics · Physics 2010-09-14 Sergio Chibbaro , Jean-Pierre Minier

The one-dimensional shallow water equations in Eulerian and Lagrangian coordinates are considered. It is shown the relationship between symmetries and conservation laws in Lagrangian (potential) coordinates and symmetries and conservation…

Mathematical Physics · Physics 2020-06-24 V. A. Dorodnitsyn , E. I. Kaptsov

We present a semi-Lagrangian characteristic mapping method for the incompressible Euler equations on a rotating sphere. The numerical method uses a spatio-temporal discretization of the inverse flow map generated by the Eulerian velocity as…

Numerical Analysis · Mathematics 2023-10-20 Seth Taylor , Jean-Christophe Nave

Advective transport of scalar quantities through surfaces is of fundamental importance in many scientific applications. From the Eulerian perspective of the surface it can be quantified by the well-known integral of the flux density. The…

Chaotic Dynamics · Physics 2016-06-30 Daniel Karrasch

Smoothed particle hydrodynamics (SPH) is omnipresent in modern engineering and scientific disciplines. SPH is a class of Lagrangian schemes that discretize fluid dynamics via finite material points that are tracked through the evolving…

Accurate models of the world are built upon notions of its underlying symmetries. In physics, these symmetries correspond to conservation laws, such as for energy and momentum. Yet even though neural network models see increasing use in the…

Machine Learning · Computer Science 2020-07-31 Miles Cranmer , Sam Greydanus , Stephan Hoyer , Peter Battaglia , David Spergel , Shirley Ho

We present a suite of high-resolution simulations of an isolated dwarf galaxy using four different hydrodynamical codes: {\sc Gizmo}, {\sc Arepo}, {\sc Gadget}, and {\sc Ramses}. All codes adopt the same physical model which includes…

Atmospheric aerosols can consist of inorganic and organic substances, including surfactants at a significant concentration. Importantly, the latter can reduce the surface tension at the liquid-vapor surfaces, where they preferentially…

Fluid Dynamics · Physics 2022-10-21 Mateusz Denys , Piotr Deuar , Zhizhao Che , Panagiotis E. Theodorakis

We propose an extension of the discretization approaches for multilayer shallow water models, aimed at making them more flexible and efficient for realistic applications to coastal flows. A novel discretization approach is proposed, in…

Numerical Analysis · Mathematics 2018-04-18 Luca Bonaventura , Enrique D. Fernández-Nieto , José Garres-Díaz , Gladys Narbona-Reina

This paper presents a novel physics-inspired deep learning approach for point cloud processing motivated by the natural flow phenomena in fluid mechanics. Our learning architecture jointly defines data in an Eulerian world space, using a…

Computer Vision and Pattern Recognition · Computer Science 2020-06-26 Xingzhe He , Helen Lu Cao , Bo Zhu