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Incompressibility is a fundamental condition in most fluid models. Accumulation of simulation errors violates it and causes volume loss. Past work suggested correction methods to battle it. These methods, however, are imperfect and in some…

图形学 · 计算机科学 2026-01-21 Zohar Levi

The Poisson equation is commonly encountered in engineering, for instance in computational fluid dynamics (CFD) where it is needed to compute corrections to the pressure field to ensure the incompressibility of the velocity field. In the…

In this paper, the high-order compact gas-kinetic scheme (CGKS) on three-dimensional hybrid unstructured mesh is further developed with the p-multigrid technique for steady-state solution acceleration. The p-multigrid strategy is a…

计算物理 · 物理学 2021-09-22 Xing Ji , Wei Shyy , Kun Xu

Potential flow has many applications, including the modelling of unsteady flows in aerodynamics. For these models to work efficiently, it is best to avoid Biot-Savart interactions. This work presents a grid-based treatment of potential…

流体动力学 · 物理学 2022-05-11 Diederik Beckers , Jeff D. Eldredge

We propose to augment standard grid-based fluid solvers with pointwise divergence-free velocity interpolation, thereby ensuring exact incompressibility down to the sub-cell level. Our method takes as input a discretely divergence-free…

图形学 · 计算机科学 2023-11-28 Jumyung Chang , Ruben Partono , Vinicius C. Azevedo , Christopher Batty

Aims. Our aim is to derive a fast and accurate method for computing the gravitational potential of astrophysical objects with high contrasts in density, for which nested or adaptive meshes are required. Methods. We present an extension of…

太阳与恒星天体物理 · 物理学 2023-03-15 Eduard Vorobyov , James McKevitt , Igor Kulikov , Vardan Elbakyan

Projected Gradient Descent (PGD) under the $L_\infty$ ball has become one of the defacto methods used in adversarial robustness evaluation for computer vision (CV) due to its reliability and efficacy, making a strong and easy-to-implement…

计算机视觉与模式识别 · 计算机科学 2025-03-26 Philip Doldo , Derek Everett , Amol Khanna , Andre T Nguyen , Edward Raff

We introduce and study conic geometric programs (CGPs), which are convex optimization problems that unify geometric programs (GPs) and conic optimization problems such as semidefinite programs (SDPs). A CGP consists of a linear objective…

最优化与控制 · 数学 2013-10-14 Venkat Chandrasekaran , Parikshit Shah

Efficient simulation of nonlinear and dispersive free-surface flows governed by the incompressible Navier-Stokes equations remains a central challenge in ocean and coastal engineering. The computational bottleneck arises from solving a…

A computational method based on the non-linear Gaussian process (GP), known as deep Gaussian processes (deep GPs) for uncertainty quantification & propagation in modelling of flow through heterogeneous porous media is presented. The method…

机器学习 · 统计学 2020-11-06 A. Daneshkhah , O. Chatrabgoun , M. Esmaeilbeigi , T. Sedighi , S. Abolfathi

The general pressure equation (GPE) is a new method proposed recently by Toutant (J. Comput. Phys., 374:822-842 (2018)) for incompressible flow simulation. It circumvents the Poisson equation for the pressure and performs better than the…

流体动力学 · 物理学 2020-11-03 Jun-Jie Huang

Learning control policies for real-world robotic tasks often involve challenges such as multimodality, local discontinuities, and the need for computational efficiency. These challenges arise from the complexity of robotic environments,…

机器人学 · 计算机科学 2025-02-05 Shu-yuan Wang , Hikaru Sasaki , Takamitsu Matsubara

We present the theory, algorithms and implementation of a parallel finite-volume algorithm for the solution of the incompressible magnetohydrodynamic (MHD) equations using unstructured grids that are applicable for a wide variety of…

流体动力学 · 物理学 2016-01-11 S. Vantieghem , A. Sheyko , A. Jackson

The periodic Gaussian process (PGP) has been increasingly used to model periodic data due to its high accuracy. Yet, computing the likelihood of PGP has a high computational complexity of $\mathcal{O}\left(n^{3}\right)$ ($n$ is the data…

统计方法学 · 统计学 2023-02-10 Yongxiang Li , Yuting Pu , Changming Cheng , Qian Xiao

Gaussian process (GP) regression is a powerful probabilistic modeling technique with built-in uncertainty quantification. When one has access to multiple correlated simulations (tasks), it is common to fit a multitask GP (MTGP) surrogate…

统计计算 · 统计学 2026-03-18 Aleksei G. Sorokin , Pieterjan Robbe , Fred J. Hickernell

This paper presents a novel particle method to compute strongly coupled incompressible fluid and rigid bodies. The method adopts a velocity-based formulation and utilizes the linear complementarity problem for the incompressibility…

流体动力学 · 物理学 2023-03-01 Shugo Miyamoto , Seiichi Koshizuka

The two promising methods for capturing high-speed flows are local artificial diffusivity (LAD) and centralised gradient-based reconstruction (C-GBR), the former being computationally economical and the latter being more robust and stable…

流体动力学 · 物理学 2025-11-25 R. R. Kumar , S. Saini , N. R. Vadlamani , A. S. Chamarthi

A novel fifth-order compact gas-kinetic scheme is developed for high-resolution simulation of compressible flows on structured meshes. Its accuracy relies on a new multidimensional fifth-order compact reconstruction that uses line-averaged…

数值分析 · 数学 2025-08-13 Yaqing Yang , Fengxiang Zhao , Kun Xu

This paper proposes a mode multigrid (MMG) method, and applies it to accelerate the convergence of the steady state flow on unstructured grids. The dynamic mode decomposition (DMD) technique is used to analyze the convergence process of…

计算物理 · 物理学 2018-02-27 Yilang Liu , Weiwei Zhang , Jiaqing Kou

We evaluate an efficient overset grid method for two-dimensional and three-dimensional particulate flows for small numbers of particles at finite Reynolds number. The rigid particles are discretised using moving overset grids overlaid on a…

计算物理 · 物理学 2017-05-24 A. R. Koblitz , S. Lovett , N. Nikiforakis , W. D. Henshaw