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A linear evolving surface partial differential equation is first discretized in space by an arbitrary Lagrangian Eulerian (ALE) evolving surface finite element method, and then in time either by a Runge-Kutta method, or by a backward…

Numerical Analysis · Mathematics 2015-01-14 Balázs Kovács , Christian Andreas Power Guerra

Stability and convergence of full discretizations of various surface evolution equations are studied in this paper. The proposed discretization combines a higher-order evolving-surface finite element method (ESFEM) for space discretization…

Numerical Analysis · Mathematics 2018-02-08 Balázs Kovács , Christian Lubich

Geophysical flows are typically composed of wave and mean motions with a wide range of overlapping temporal scales, making separation between the two types of motion in wave-resolving numerical simulations challenging. Lagrangian filtering…

Fluid Dynamics · Physics 2025-10-15 Lois E. Baker , Hossein A. Kafiabad , Cai Maitland-Davies , Jacques Vanneste

We present a novel deep learning framework for flow field predictions in irregular domains when the solution is a function of the geometry of either the domain or objects inside the domain. Grid vertices in a computational fluid dynamics…

Machine Learning · Computer Science 2021-09-20 Ali Kashefi , Davis Rempe , Leonidas J. Guibas

In this paper, we study numerical methods for the solution of partial differential equations on evolving surfaces. The evolving hypersurface in $\Bbb{R}^d$ defines a $d$-dimensional space-time manifold in the space-time continuum…

Numerical Analysis · Mathematics 2014-04-09 Maxim A. Olshanskii , Arnold Reusken , Xianmin Xu

A cell-centered implicit-explicit updated Lagrangian finite volume scheme on unstructured grids is proposed for a unified first order hyperbolic formulation of continuum fluid and solid mechanics. The scheme provably respects the stiff…

Numerical Analysis · Mathematics 2022-01-26 Walter Boscheri , Simone Chiocchetti , Ilya Peshkov

We present a machine learning framework that blends image super-resolution technologies with passive, scalar transport in the level-set method. Here, we investigate whether we can compute on-the-fly, data-driven corrections to minimize…

Machine Learning · Computer Science 2022-09-29 Luis Ángel Larios-Cárdenas , Frédéric Gibou

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

In this paper, we propose a mesh-free method to solve interface problems using the deep learning approach. Two interface problems are considered. The first one is an elliptic PDE with a discontinuous and high-contrast coefficient. While the…

Computational Physics · Physics 2024-12-20 Zhongjian Wang , Zhiwen Zhang

There are several approaches to describe flows with particles e.g. Lattice-Gas Automata (LGA), Lattice-Boltzmann method (LBM) or smoothed particle hydrodynamics (SPH). These approaches do not use fixed grids on which the Navier-Stokes…

Fluid Dynamics · Physics 2008-02-27 B. Ivancic

The Intrinsic Surface Finite Element Method (ISFEM) was recently proposed to solve Partial Differential Equations (PDEs) on surfaces. ISFEM proceeds by writing the PDE with respect to a local coordinate system anchored to the surface and…

Numerical Analysis · Mathematics 2024-10-08 Elena Bachini , Mario Putti

We present a position Langevin equation for overdamped particle motion on rough two-dimensional surfaces. A Brownian Dynamics algorithm is suggested to evolve this equation numerically, allowing for the prediction of effective (projected)…

Soft Condensed Matter · Physics 2009-11-13 Ali Naji , Frank L. H. Brown

We introduce a meshfree exterior calculus (MEEC) for learning structure-preserving descriptions of physics on point clouds, and use it to build MEEC-Net, a data-efficient surrogate that transfers across resolutions, geometries, and physical…

Machine Learning · Computer Science 2026-05-12 Benjamin D. Shaffer , Brooks Kinch , M. Ani Hsieh , Nathaniel Trask

We consider the problem of solving partial differential equations (PDEs) in domains with complex microparticle geometry that is impractical, or intractable, to model explicitly. Drawing inspiration from volume rendering, we propose tackling…

Graphics · Computer Science 2025-06-11 Bailey Miller , Rohan Sawhney , Keenan Crane , Ioannis Gkioulekas

A large number of powerful, high-quality, and open-source simulation packages exist to efficiently perform molecular dynamics simulations, and their prevalence has greatly accelerated discoveries across a wide range of scientific domains.…

Soft Condensed Matter · Physics 2024-05-01 Toler H. Webb , Daniel M. Sussman

With the advancement in 3D scanning technology, there has been a surge of interest in the use of point clouds in science and engineering. To facilitate the computations and analyses of point clouds, prior works have considered…

Computational Geometry · Computer Science 2021-12-22 Gary P. T. Choi , Yechen Liu , Lok Ming Lui

We present the numerical methods and GPU-accelerated implementation underlying a Total Lagrangian finite element framework for finite-deformation flexible multibody dynamics, introduced in the companion paper [1]. The framework supports…

Computational Engineering, Finance, and Science · Computer Science 2026-05-04 Zhenhao Zhou , Ruochun Zhang , Ganesh Arivoli , Dan Negrut

This paper proposes a Cartesian grid-based boundary integral method for efficiently and stably solving two representative moving interface problems, the Hele-Shaw flow and the Stefan problem. Elliptic and parabolic partial differential…

Numerical Analysis · Mathematics 2026-04-22 Han Zhou , Shuwang Li , Wenjun Ying

We present a structure-preserving Eulerian algorithm for solving $L^2$-gradient flows and a structure-preserving Lagrangian algorithm for solving generalized diffusions. Both algorithms employ neural networks as tools for spatial…

Numerical Analysis · Mathematics 2024-04-16 Ziqing Hu , Chun Liu , Yiwei Wang , Zhiliang Xu

In this paper, we extend the class of kernel methods, the so-called diffusion maps (DM) and ghost point diffusion maps (GPDM), to solve the time-dependent advection-diffusion PDE on unknown smooth manifolds without and with boundaries. The…

Numerical Analysis · Mathematics 2021-05-31 Qile Yan , Shixiao Willing Jiang , John Harlim
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