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Related papers: A discretization-convergent Level-Set-DEM

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This paper is concerned with the nonconforming finite element discretization of geometric partial differential equations. In specific, we construct a surface Crouzeix-Raviart element on the linear approximated surface, analogous to a flat…

Numerical Analysis · Mathematics 2022-08-12 Hailong Guo

Decentralized optimization has become a fundamental tool for large-scale learning systems; however, most existing methods rely on the classical Lipschitz smoothness assumption, which is often violated in problems with rapidly varying…

Optimization and Control · Mathematics 2026-01-08 Yanan Bo , Yongqiang Wang

We address the problem of inferring self-supervised dense semantic correspondences between objects in multi-object scenes. The method introduces learning of class-aware dense object descriptors by providing either unsupervised discrete…

Robotics · Computer Science 2021-10-06 Denis Hadjivelichkov , Dimitrios Kanoulas

Recent work has shown that convolutional networks can be substantially deeper, more accurate, and efficient to train if they contain shorter connections between layers close to the input and those close to the output. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2018-01-30 Gao Huang , Zhuang Liu , Laurens van der Maaten , Kilian Q. Weinberger

Concentration gradients play a critical role in embryogenesis, bacterial locomotion, as well as the motility of active particles. Particles develop concentration profiles around them by dissolution, adsorption, or the reactivity of surface…

We present a new approach to discretizing shape optimization problems that generalizes standard moving mesh methods to higher-order mesh deformations and that is naturally compatible with higher-order finite element discretizations of…

Numerical Analysis · Mathematics 2017-06-13 A. Paganini , F. Wechsung , P. E. Farrell

We consider variational problems that model the bending behavior of curves that are constrained to belong to given hypersurfaces. Finite element discretizations of corresponding functionals are justified rigorously via Gamma-convergence.…

Numerical Analysis · Mathematics 2020-04-24 Sören Bartels

The aim of this paper is to propose a novel methodology to deal with micro-structural boundary conditions for the analysis of granular materials. The response of the granular assembly is modelled through the discrete element method (DEM),…

Soft Condensed Matter · Physics 2017-02-27 J. Liu , E. Bosco , A. S. J. Suiker

For a singular integral equation on an interval of the real line, we study the behavior of the error of a delta-delta discretization. We show that the convergence is non-uniform, between order $O(h^{2})$ in the interior of the interval and…

Numerical Analysis · Mathematics 2023-11-14 Martin Costabel

We present a fully Lagrangian particle level-set method based on high-order polynomial regression. This enables closest-point redistancing without requiring a regular Cartesian mesh, relaxing the need for particle-mesh interpolation.…

Computational Engineering, Finance, and Science · Computer Science 2024-11-05 Lennart J. Schulze , Sachin K. T. Veettill , Ivo F. Sbalzarini

In this paper, a novel varying order NURBS discretization method is proposed to enhance the performance of isogeometric analysis within the framework of computational contact mechanics. The method makes use of higher-order NURBS for contact…

Numerical Analysis · Computer Science 2020-06-03 Vishal Agrawal , Sachin S. Gautam

The dynamics of solid-liquid interfaces controlled by solute precipitation and/or dissolution due to the chemical reaction at the interface were computed in two dimensions using a phase field models. Sharp-interface asymptotic analysis…

Computational Physics · Physics 2018-08-30 Zhijie Xu , Hai Huang , Xiaoyi Li , Paul Meakin

In engineering applications snow often undergoes large and fast deformations. During these deformations the snow transforms from a sintered porous material into a granular material. In order to capture the fundamental mechanical behavior of…

Geophysics · Physics 2020-07-06 Thiemo Theile , Denes Szabo , Carolin Willibald , Martin Schneebeli

We present a differentiable formulation of rigid-body contact dynamics for objects and robots represented as compositions of convex primitives. Existing optimization-based approaches simulating contact between convex primitives rely on a…

Finite element simulations of frictional multi-body contact problems via conformal meshes can be challenging and computationally demanding. To render geometrical features, unstructured meshes must be used and this unavoidably increases the…

Computational Engineering, Finance, and Science · Computer Science 2020-11-03 Chuanqi Liu , Waiching Sun

With the maturation of differentiable physics, its role in various downstream applications: such as model predictive control, robotic design optimization, and neural PDE solvers, has become increasingly important. However, the derivative…

Robotics · Computer Science 2025-09-26 Xiaohan Ye , Kui Wu , Zherong Pan , Taku Komura

We investigate a finite element discretization of an elastic bending-plate model with an effective prestrain. The model has been obtained via homogenization and dimension reduction by B\"onlein at al. (2023). Its energy functional is the…

Numerical Analysis · Mathematics 2025-10-13 Klaus Böhnlein , Stefan Neukamm , Oliver Sander

Computational fluid dynamics and discrete element method (CFD-DEM) coupling is an efficient and powerful tool to simulate particle-fluid systems. However, current volume-averaged CFD-DEM relying on direct grid-based mapping between the…

Fluid Dynamics · Physics 2025-06-12 Yuxiang Liu , Lu Jing , Xudong Fu , Huabin Shi

When a fluid surface adheres to a substrate, the location of the contact line adjusts in order to minimize the overall energy. This adhesion balance implies boundary conditions which depend on the characteristic surface deformation…

Soft Condensed Matter · Physics 2011-11-09 Markus Deserno , Martin M. Mueller , Jemal Guven

$L^1$ based optimization is widely used in image denoising, machine learning and related applications. One of the main features of such approach is that it naturally provide a sparse structure in the numerical solutions. In this paper, we…

Numerical Analysis · Mathematics 2023-02-13 Weifeng Qiu , Jin Ren , Ke Shi , Yuesheng Xu
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