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Edge points on 3D point clouds can clearly convey 3D geometry and surface characteristics, therefore, edge detection is widely used in many vision applications with high industrial and commercial demands. However, the fine-grained edge…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Yifei Xie , Zhikun Tu , Tong Yang , Yuhe Zhang , Xinyu Zhou

This paper introduces a novel Lagrangian fluid solver based on covector flow maps. We aim to address the challenges of establishing a robust flow-map solver for incompressible fluids under complex boundary conditions. Our key idea is to use…

Graphics · Computer Science 2024-05-17 Zhiqi Li , Barnabás Börcsök , Duowen Chen , Yutong Sun , Bo Zhu , Greg Turk

This paper presents a new finite difference method, called {\varphi}-FD, inspired by the {\phi}-FEM approach for solving elliptic partial differential equations (PDEs) on general geometries. The proposed method uses Cartesian grids,…

Numerical Analysis · Mathematics 2025-05-28 Michel Duprez , Vanessa Lleras , Alexei Lozinski , Vincent Vigon , Killian Vuillemot

The diffuse-domain, or smoothed boundary, method is an attractive approach for solving partial differential equations in complex geometries because of its simplicity and flexibility. In this method the complex geometry is embedded into a…

Numerical Analysis · Mathematics 2019-12-02 Fei Yu , Zhenlin Guo , John Lowengrub

We present a numerical method for simulating rarefied gases that interact with moving boundaries and rigid bodies. The gas is described by the BGK equation in Lagrangian form and solved using an Arbitrary Lagrangian-Eulerian method, in…

Numerical Analysis · Mathematics 2026-04-28 Klaas Willems , Axel Klar , Giovanni Russo , Giovanni Samaey , Sudarshan Tiwari

This study introduces a novel point-wise diffusion model that processes spatio-temporal points independently to efficiently predict complex physical systems with shape variations. This methodological contribution lies in applying forward…

Computational Physics · Physics 2025-08-05 Jiyong Kim , Sunwoong Yang , Namwoo Kang

This work investigates the effects of the choice of momentum diffusion operator on the evolution of multiphase fluid systems resolved with Meshless Lagrangian Methods (MLM). Specifically, the effects of a non-zero viscosity gradient at…

Fluid Dynamics · Physics 2023-03-20 Johannes C. Joubert , Daniel N. Wilke , Patrick Pizette

In this work, we introduce a novel computational framework for solving the two-dimensional Hele-Shaw free boundary problem with surface tension. The moving boundary is represented by point clouds, eliminating the need for a global…

Numerical Analysis · Mathematics 2026-05-21 Zengyan Zhang , Wenrui Hao , John Harlim

We develop an invariant local theory of Lorentz surfaces in pseudo-Euclidean 4-space by use of a linear map of Weingarten type. We find a geometrically determined moving frame field at each point of the surface and obtain a system of…

Differential Geometry · Mathematics 2017-04-27 Yana Aleksieva , Georgi Ganchev , Velichka Milousheva

In this paper we analyze a space-time unfitted finite element method for the discretization of scalar surface partial differential equations on evolving surfaces. For higher order approximations of the evolving surface we use the technique…

Numerical Analysis · Mathematics 2024-11-26 Arnold Reusken , Hauke Sass

Triangulated meshes have become ubiquitous discrete-surface representations. In this paper we address the problem of how to maintain the manifold properties of a surface while it undergoes strong deformations that may cause topological…

Computer Vision and Pattern Recognition · Computer Science 2020-12-11 Andrei Zaharescu , Edmond Boyer , Radu Horaud

A surface moving mesh method is presented for general surfaces with or without explicit parameterization. The method can be viewed as a nontrivial extension of the moving mesh partial differential equation method that has been developed for…

Numerical Analysis · Mathematics 2024-12-20 Avary Kolasinski , Weizhang Huang

There has been an arising trend of adopting deep learning methods to study partial differential equations (PDEs). In this paper, we introduce a deep recurrent framework for solving time-dependent PDEs without generating large scale data…

Numerical Analysis · Mathematics 2021-04-21 Cheng Chang , Liu Liu , Tieyong Zeng

In this paper, we look at the pressure checkerboard problem that arises in an Eulerian meshless method that solves the incompressible Navier-Stokes equations using the generalized finite difference method (GFDM). Although, the checkerboard…

Numerical Analysis · Mathematics 2025-06-03 Anand S Bharadwaj

We present a computational framework for modeling large-scale particle-laden flows in complex domains with the goal of enabling simulations in medical-image derived patient specific geometries. The framework is based on a volume-filtered…

Fluid Dynamics · Physics 2023-11-28 Abhilash Reddy Malipeddi , C. Alberto Figueroa , Jesse Capecelatro

This paper considers flow problems in multiscale heterogeneous porous media. The multiscale nature of the modeled process significantly complicates numerical simulations due to the need to compute huge and ill-conditioned sparse matrices,…

Numerical Analysis · Mathematics 2024-10-16 Djulustan Nikiforov , Leonardo A. Poveda , Dmitry Ammosov , Yesy Sarmiento , Juan Galvis

Generalized Lagrangian mean theories are used to analyze the interactions between mean flows and fluctuations, where the decomposition is based on a Lagrangian description of the flow. A systematic geometric framework was recently developed…

Mathematical Physics · Physics 2019-09-11 Marcel Oliver , Sergiy Vasylkevych

We develop a structure-preserving computational framework for acoustic wave scattering by moving objects, comprising a new PML-domain-embedding model and a compatible numerical approximation. The model couples a perfectly matched layer…

Numerical Analysis · Mathematics 2026-05-28 Xuelong Gu , Qi Wang

Point clouds, as a form of Lagrangian representation, allow for powerful and flexible applications in a large number of computational disciplines. We propose a novel deep-learning method to learn stable and temporally coherent feature…

Computer Vision and Pattern Recognition · Computer Science 2020-01-30 Lukas Prantl , Nuttapong Chentanez , Stefan Jeschke , Nils Thuerey

We propose a novel Particle Flow Map (PFM) method to enable accurate long-range advection for incompressible fluid simulation. The foundation of our method is the observation that a particle trajectory generated in a forward simulation…

Graphics · Computer Science 2024-05-17 Junwei Zhou , Duowen Chen , Molin Deng , Yitong Deng , Yuchen Sun , Sinan Wang , Shiying Xiong , Bo Zhu