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Efficient and scalable 3D surface reconstruction from range data remains a core challenge in computer graphics and vision, particularly in real-time and resource-constrained scenarios. Traditional volumetric methods based on…

图形学 · 计算机科学 2025-11-27 Lorenzo De Rebotti , Emanuele Giacomini , Giorgio Grisetti , Luca Di Giammarino

This work introduces a novel, fully robust and highly-scalable, $h$-adaptive aggregated unfitted finite element method for large-scale interface elliptic problems. The new method is based on a recent distributed-memory implementation of the…

数值分析 · 数学 2021-04-07 Eric Neiva , Santiago Badia

We describe an implementation of compressible inviscid fluid solvers with block-structured adaptive mesh refinement on Graphics Processing Units using NVIDIA's CUDA. We show that a class of high resolution shock capturing schemes can be…

宇宙学与河外天体物理 · 物理学 2014-11-20 Peng Wang , Tom Abel , Ralf Kaehler

We show feasibility and benefits of porting an adaptive multi-scale kinetic-fluid code to CPU-GPU systems. Challenges are due to the irregular data access for adaptive Cartesian mesh, vast difference of computational cost between kinetic…

计算物理 · 物理学 2015-07-23 Sergey Zabelok , Robert Arslanbekov , Vladimir Kolobov

High-order numerical methods for unstructured grids combine the superior accuracy of high-order spectral or finite difference methods with the geometric flexibility of low-order finite volume or finite element schemes. The Flux…

计算物理 · 物理学 2015-06-18 Freddie D Witherden , Antony M Farrington , Peter E Vincent

This paper presents a heterogeneous adaptive mesh refinement (AMR) framework for efficient simulation of moderately stiff reactive problems. This framework features an elaborate subcycling-in-time algorithm along with a specialized…

计算物理 · 物理学 2025-06-04 Yuqi Wang , Yadong Zeng , Ralf Deiterding , Jianhan Liang

This paper describes a direct solver algorithm for a sequence of finite element meshes that are h-refined towards one or several point singularities. For such a sequence of grids, the solver delivers linear computational cost O(N) in terms…

数值分析 · 计算机科学 2012-12-11 Maciej Paszynski , Victor Calo , David Pardo

Adaptive Mesh Refinement (AMR) enables efficient computation of flows by providing high resolution in critical regions while allowing for coarsening in areas where fine detail is unnecessary. While early AMR software packages relied solely…

计算物理 · 物理学 2025-02-26 Khodr Jaber , Ebenezer Essel , Pierre Sullivan

Adaptive finite elements combined with geometric multigrid solvers are one of the most efficient numerical methods for problems such as the instationary Navier-Stokes equations. Yet despite their efficiency, computations remain expensive…

数值分析 · 数学 2025-12-23 Manuel Liebchen , Robert Jendersie , Utku Kaya , Christian Lessig , Thomas Richter

Adaptive mesh refinement (AMR) reduces computational costs in CFD by concentrating resolution where needed, but efficiently embedding complex, non-aligned geometries on GPUs remains challenging. We present a GPU-native algorithm for…

计算工程、金融与科学 · 计算机科学 2026-04-28 Khodr Jaber , Ebenezer E. Essel , Pierre E. Sullivan

Structured Adaptive Mesh Refinement (SAMR) is a popular numerical technique to study processes with high spatial and temporal dynamic range. It reduces computational requirements by adapting the lattice on which the underlying differential…

天体物理仪器与方法 · 物理学 2015-06-12 Ralf Kaehler , Tom Abel

Solving the shallow water equations efficiently is critical to the study of natural hazards induced by tsunami and storm surge, since it provides more response time in an early warning system and allows more runs to be done for…

计算物理 · 物理学 2019-01-23 Xinsheng Qin , Randall LeVeque , Michael Motley

The moment-of-fluid (MOF) method is an extension of the volume-of-fluid method with piecewise linear interface construction (VOF-PLIC). By minimizing the least square error of the centroid of the cutting polyhedron, the MOF method…

数值分析 · 数学 2021-08-06 Zhouteng Ye , Mark Sussman , Yi Zhan , Xizeng Zhao

This paper presents a GPU-accelerated computational framework for reconstructing high resolution (HR) LF images under a mixed Gaussian-Impulse noise condition. The main focus is on developing a high-performance approach considering…

图像与视频处理 · 电气工程与系统科学 2022-06-13 Trung-Hieu Tran , Kaicong Sun , Sven Simon

In this work, we bridge standard adaptive mesh refinement and coarsening on scalable octree background meshes and robust unfitted finite element formulations for the automatic and efficient solution of large-scale nonlinear solid mechanics…

数值分析 · 数学 2021-09-01 Santiago Badia , Manuel Caicedo , Alberto F. Martín , Javier Principe

The present paper addresses the development and implementation of the first high-order Flux Reconstruction (FR) solver for high-speed flows within the open-source COOLFluiD (Computational Object-Oriented Libraries for Fluid Dynamics)…

计算物理 · 物理学 2019-07-24 Ray Vandenhoeck , Andrea Lani

Networks of interconnected resistors, springs and beams, or pores are standard models of studying scalar and vector transport processes in heterogeneous materials and media, such as fluid flow in porous media, and conduction, deformations,…

计算物理 · 物理学 2019-08-12 Hassan Dashtian , Muhammad Sahimi

The kd-tree is a fundamental tool in computer science. Among others, an application of the kd-tree search (oct-tree method) to fast evaluation of particle interactions and neighbor search is highly important since computational complexity…

天体物理仪器与方法 · 物理学 2009-09-04 N. Nakasato

A cut tree (or Gomory-Hu tree) of an undirected weighted graph G=(V,E) encodes a minimum s-t-cut for each vertex pair {s,t} \subseteq V and can be iteratively constructed by n-1 maximum flow computations. They solve the multiterminal…

数据结构与算法 · 计算机科学 2013-10-02 Tanja Hartmann , Dorothea Wagner

In this paper, we introduce a novel approach that combines multiresolution (MR) techniques with the flux reconstruction (FR) method to accurately and effciently simulate compressible flows. We achieve further enhancements in effciency…

流体动力学 · 物理学 2023-06-21 Yixuan Lian , Jinsheng Cai , Shucheng Pan
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