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An a priori reduced order method based on the proper generalised decomposition (PGD) is proposed to compute parametric solutions involving turbulent incompressible flows of interest in an industrial context, using OpenFOAM. The PGD…

计算物理 · 物理学 2021-11-16 Vasileios Tsiolakis , Matteo Giacomini , Ruben Sevilla , Carsten Othmer , Antonio Huerta

Streamwise and quasi-streamwise elongated structures have been shown to play a significant role in turbulent shear flows. We model the mean behavior of fully turbulent plane Couette flow using a streamwise constant projection of the Navier…

流体动力学 · 物理学 2010-11-29 D. F. Gayme , B. J. McKeon , A. Papachristodoulou , B. Bamieh , J. C. Doyle

The aim of this work is to study the Navier-Stokes-Voigt equations that govern flows with non-negative density of incompressible fluids with elastic properties. For the associated non-linear initial-and boundary-value problem, we prove the…

偏微分方程分析 · 数学 2023-09-04 Hermenegildo Borges de Oliveira , Khonatbek Khompysh , Aidos Ganizhanuly Shakir

We present an efficient deep learning technique for the model reduction of the Navier-Stokes equations for unsteady flow problems. The proposed technique relies on the Convolutional Neural Network (CNN) and the stochastic gradient descent…

流体动力学 · 物理学 2018-08-16 Tharindu P. Miyanawala , Rajeev K. Jaiman

Navier-Stokes turbulence subject to solid-body rotation is studied by high-resolution direct numerical simulations (DNS) of freely decaying and stationary flows. Setups characterized by different Rossby numbers are considered. In agreement…

流体动力学 · 物理学 2015-05-13 M. Thiele , W. -C. Müller

The Navier-Stokes-Voigt equations are a regularization of the Navier-Stokes equations that share some of its asymptotic and statistical properties and have been used in direct numerical simulations of the latter. In this article we…

偏微分方程分析 · 数学 2015-07-27 Cesar J. Niche

Reduced-order models have been widely adopted in fluid mechanics, particularly in the context of Newtonian fluid flows. These models offer the ability to predict complex dynamics, such as instabilities and oscillations, at a considerably…

流体动力学 · 物理学 2023-12-05 Cassio M. Oishi , Alan A. Kaptanoglu , J. Nathan Kutz , Steven L. Brunton

In this paper, we present a new computational framework to approximate a Cahn-Hilliard-Navier-Stokes model with variable density and degenerate mobility that preserves the mass of the mixture, the pointwise bounds of the density and the…

Direct numerical simulations, performed with a high-order spectral-element method, are used to study coherent structures in turbulent pipe flow at friction Reynolds numbers $Re_{\tau} = 180$ and $550$. The database was analysed using…

流体动力学 · 物理学 2023-07-19 Leandra Abreu , André Cavalieri , Philipp Schlatter , Ricardo Vinuesa , Dan Henningson

The Navier-Stokes-Voigt model of viscoelastic incompressible fluid has been recently proposed as a regularization of the three-dimensional Navier-Stokes equations for the purpose of direct numerical simulations. Besides the kinematic…

数学物理 · 物理学 2009-10-09 Fabio Ramos , Edriss S. Titi

In this paper, we consider dynamics defined by the Navier-Stokes equations in the Oberbeck-Boussinesq approximation in a two dimensional domain. This model of fluid dynamics involve fundamental physical effects: convection, and diffusion.…

数学物理 · 物理学 2019-01-08 Sergey Vakulenko

This article is concerned with the problem of determining an unknown source of non-potential, external time-dependent perturbations of an incompressible fluid from large-scale observations on the flow field. A relaxation-based approach is…

偏微分方程分析 · 数学 2024-02-26 Vincent R. Martinez

Approximate deconvolution forms a mathematical framework for the structural modeling of turbulence. The sub-filter scale flow quantities are typically recovered by using the Van Cittert iterative procedure. In this paper, however, we put…

流体动力学 · 物理学 2017-07-31 Omer San , Prakash Vedula

This work focuses on steady and unsteady Navier-Stokes equations in a reduced order modeling framework. The methodology proposed is based on a Proper Orthogonal Decomposition within a levelset geometry description and the problems of…

数值分析 · 数学 2023-08-08 Efthymios N. Karatzas , Monica Nonino , Francesco Ballarin , Gianluigi Rozza

Model reduction for fluid flow simulation continues to be of great interest across a number of scientific and engineering fields. Here, we explore the use of Neural Ordinary Differential Equations, a recently introduced family of…

机器学习 · 计算机科学 2021-04-30 Sourav Dutta , Peter Rivera-Casillas , Matthew W. Farthing

Any model order reduced dynamical system that evolves a modal decomposition to approximate the discretized solution of a stochastic PDE can be related to a vector field tangent to the manifold of fixed rank matrices. The Dynamically…

动力系统 · 数学 2018-04-04 Florian Feppon , Pierre F. J. Lermusiaux

Resolvent analysis of the linearized Navier-Stokes equations provides useful insight into the dynamics of transitional and turbulent flows and can provide a model for the dominant coherent structures within the flow, particularly for flows…

流体动力学 · 物理学 2021-07-01 Eduardo Martini , Daniel Rodríguez , Aaron Towne , André V. G. Cavalieri

Blood flow imaging provides important information for hemodynamic behavior within the vascular system and plays an essential role in medical diagnosis and treatment planning. However, obtaining high-quality flow images remains a significant…

数值分析 · 数学 2026-04-02 Han Zhang , Xue-Cheng Tai , Jean-Michel Morel , Raymond H. Chan

We formalise the concept of near resonance for the rotating Navier-Stokes equations, based on which we propose a novel way to approximate the original PDE. The spatial domain is a three-dimensional flat torus of arbitrary aspect ratios. We…

偏微分方程分析 · 数学 2021-10-12 Bin Cheng , Zisis N. Sakellaris

We have found an infinite dimensional manifold of exact solutions of the Navier-Stokes loop equation for the Wilson loop in decaying Turbulence in arbitrary dimension $d >2$. This solution family is equivalent to a fractal curve in complex…

流体动力学 · 物理学 2023-10-26 Alexander Migdal