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We discuss a unified flow theory which in a single system of hyperbolic partial differential equations (PDEs) can describe the two main branches of continuum mechanics, fluid dynamics, and solid dynamics. The fundamental difference from the…

流体动力学 · 物理学 2018-11-19 Ilya Peshkov , Evgeniy Romenski , Michael Dumbser

Navier-Stokes equations are significant partial differential equations that describe the motion of fluids such as liquids and air. Due to the importance of Navier-Stokes equations, the development on efficient numerical schemes is important…

流体动力学 · 物理学 2022-07-21 Rui Zhang , Peiyan Hu , Qi Meng , Yue Wang , Rongchan Zhu , Bingguang Chen , Zhi-Ming Ma , Tie-Yan Liu

An in-house large eddy simulation tool is developed in order to reproduce high fidelity results of compressible jet flows. The large eddy simulation formulation is written using the finite difference approach, with an explicit time…

流体动力学 · 物理学 2023-01-04 Carlos Junqueira-Junior , Joao Luiz F. Azevedo , Sami Yamouni , William Wolf

Combining machine learning (ML) with computational fluid dynamics (CFD) opens many possibilities for improving simulations of technical and natural systems. However, CFD+ML algorithms require exchange of data, synchronization, and…

机器学习 · 计算机科学 2024-06-25 Tomislav Maric , Mohammed Elwardi Fadeli , Alessandro Rigazzi , Andrew Shao , Andre Weiner

This article is an updated version of the article that was published in the Electronic Journal of Differential Equations on 10. July 2010. Two footnotes have been added. One corrects a minor error not influencing the proof, the second is…

综合数学 · 数学 2012-12-04 Jorma Jormakka

The aim of this article is to present a comprehensive methodology for the verification of computational fluid dynamics (CFD) solvers with a special attention to aspects pertinent to discretizations with orders of accuracy (OOAs) higher than…

计算物理 · 物理学 2018-09-11 Farshad Navah , Siva Nadarajah

We present an efficient solver for massively-parallel direct numerical simulations of incompressible turbulent flows. The method uses a second-order, finite-volume pressure-correction scheme, where the pressure Poisson equation is solved…

流体动力学 · 物理学 2019-09-13 Pedro Costa

Data-driven methods demonstrate considerable potential for accelerating the inherently expensive computational fluid dynamics (CFD) solvers. Nevertheless, pure machine-learning surrogate models face challenges in ensuring physical…

流体动力学 · 物理学 2024-09-12 Clément Caron , Philippe Lauret , Alain Bastide

In this paper the physics- (or PDE-) integrated machine learning (ML) framework is investigated. The Navier-Stokes (NS) equations are solved using Tensorflow library for Python via Chorin's projection method. The methodology for the…

计算物理 · 物理学 2021-05-31 Arsen S. Iskhakov , Nam T. Dinh

Computational Fluid Dynamics (CFD) has become an indispensable tool in the optimization design, and evaluation of aircraft aerodynamics. However, solving the Navier-Stokes (NS) equations is a time-consuming, memory demanding and…

流体动力学 · 物理学 2023-12-08 Kuijun Zuo , Zhengyin Ye , Shuhui Bu , Xianxu Yuan , Weiwei Zhang

This paper sums up some recent validations of an immersed boundary method for compressible flow simulations. It has been already shown that this method is able to provide accurate results without meshing effort around more or less complex…

流体动力学 · 物理学 2019-02-19 Thomas Renaud , Christophe Benoit , Stephanie Péron , Ivan Mary , Nicolas Alferez

Understanding and solving fluid dynamics equations efficiently remains a fundamental challenge in computational physics. Traditional numerical solvers and physics-informed neural networks struggle to capture the full range of frequency…

The Navier-Stokes equations describe the motion of viscous fluids. In order to predict turbulent flows with reasonable computational time and accuracy, these equations are spatially filtered according to the large-eddy simulation (LES)…

流体动力学 · 物理学 2018-07-02 Larissa B. Streher , Maurits H. Silvis , Roel Verstappen

Physical systems whose dynamics are governed by partial differential equations (PDEs) find applications in numerous fields, from engineering design to weather forecasting. The process of obtaining the solution from such PDEs may be…

机器学习 · 计算机科学 2022-09-21 Pratyush Bhatt , Yash Kumar , Azzeddine Soulaimani

The paper extends a stabilized fictitious domain finite element method initially developed for the Stokes problem to the incompressible Navier-Stokes equations coupled with a moving solid. This method presents the advantage to predict an…

数值分析 · 数学 2017-07-12 Sébastien Court , Michel Fournié

A new flow solver scalable on multiple Graphics Processing Units (GPUs) for direct numerical simulation of wall-bounded incompressible flow is presented. This solver utilizes a previously reported work (J. Comp. Physics, vol. 352 (2018),…

计算物理 · 物理学 2018-12-05 Sanghyun Ha , Junshin Park , Donghyun You

MFC is an open-source tool for solving multi-component, multi-phase, and bubbly compressible flows. It is capable of efficiently solving a wide range of flows, including droplet atomization, shock-bubble interaction, and gas bubble…

Integrating computational fluid dynamics (CFD) software into optimization and machine-learning frameworks is hampered by the rigidity of classic computational languages and the slow performance of more flexible high-level languages.…

流体动力学 · 物理学 2023-04-18 Gabriel D. Weymouth , Bernat Font

The existence and dynamical role of particular unstable Navier-Stokes solutions (exact coherent structures) is revealed in laboratory studies of weak turbulence in a thin, electromagnetically-driven fluid layer. We find that the dynamics…

混沌动力学 · 物理学 2018-08-01 Balachandra Suri , Jeffrey Tithof , Roman O. Grigoriev , Michael F. Schatz

Fluid simulation is an important research topic in computer graphics (CG) and animation in video games. Traditional methods based on Navier-Stokes equations are computationally expensive. In this paper, we treat fluid motion as point cloud…

计算机视觉与模式识别 · 计算机科学 2025-01-07 Yu Chen , Shuai Zheng , Nianyi Wang , Menglong Jin , Yan Chang