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相关论文: A reduced-order model of three-dimensional unstead…

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A new approach to model order reduction of the Navier-Stokes equations at high Reynolds number is proposed. Unlike traditional approaches, this method does not rely on empirical turbulence modeling or modification of the Navier-Stokes…

流体动力学 · 物理学 2013-09-11 Maciej Balajewicz , Earl Dowell , Bernd Noack

Reduced-order modeling has a long tradition in computational fluid dynamics. The ever-increasing significance of data for the synthesis of low-order models is well reflected in the recent successes of data-driven approaches such as Dynamic…

动力系统 · 数学 2020-12-09 Peter Benner , Pawan Goyal , Jan Heiland , Igor Pontes Duff

This article provides a reduced-order modelling framework for turbulent compressible flows discretized by the use of finite volume approaches. The basic idea behind this work is the construction of a reduced-order model capable of providing…

流体动力学 · 物理学 2024-05-31 Matteo Zancanaro , Valentin Nkana Ngan , Giovanni Stabile , Gianluigi Rozza

We consider model order reduction based on proper orthogonal decomposition (POD) for unsteady incompressible Navier-Stokes problems, assuming that the snapshots are given by spatially adapted finite element solutions. We propose two…

数值分析 · 数学 2019-08-02 Carmen Gräßle , Michael Hinze , Jens Lang , Sebastian Ullmann

In the present study, the efficiency of preconditioners for solving linear systems associated with the discretized variable-density incompressible Navier-Stokes equations with semiimplicit second-order accuracy in time and spectral accuracy…

流体动力学 · 物理学 2024-03-12 L. Reynier , Bastien Di Pierro , Frédéric Alizard , Anne Cadiou , Lionel Le Penven , Marc Buffat

We present a component-based model order reduction procedure to efficiently and accurately solve parameterized incompressible flows governed by the Navier-Stokes equations. Our approach leverages a non-overlapping optimization-based domain…

数值分析 · 数学 2023-11-01 Tommaso Taddei , Xuejun Xu , Lei Zhang

We present an optimization-based method to efficiently calculate accurate nonlinear models of Taylor vortex flow. We use the resolvent formulation of McKeon & Sharma (2010) to model these Taylor vortex solutions by treating the nonlinearity…

流体动力学 · 物理学 2021-09-01 Benedikt Barthel , Xiaojue Zhu , Beverley J. McKeon

Many unsteady flows exhibiting complex dynamics are nevertheless characterized by emergent large-scale coherence in space and time. Reduced-order models based on Galerkin projection of the governing equations onto an orthogonal modal basis…

流体动力学 · 物理学 2022-06-28 Jared L. Callaham , Jean-Christophe Loiseau , Steven L. Brunton

A major goal for reduced-order models of unsteady fluid flows is to uncover and exploit latent low-dimensional structure. Proper orthogonal decomposition (POD) provides an energy-optimal linear basis to represent the flow kinematics, but…

流体动力学 · 物理学 2022-03-23 Jared L. Callaham , Steven L. Brunton , Jean-Christophe Loiseau

We introduce a widely applicable tensor network-based framework for developing reduced order models describing wall-bounded fluid flows. As a paradigmatic example, we consider the incompressible Navier-Stokes equations and the lid-driven…

流体动力学 · 物理学 2024-10-10 Martin Kiffner , Dieter Jaksch

We study mathematical and physical properties of a family of recently introduced, reduced-order approximate deconvolution models. We first show a connection between these models and the NS-Voigt model, and that NS-Voigt can be re-derived in…

偏微分方程分析 · 数学 2015-04-21 L. C. Berselli , T. -Y. Kim , L. G. Rebholz

Scaling up new scientific technologies from laboratory to industry often involves demonstrating performance on a larger scale. Computer simulations can accelerate design and predictions in the deployment process, though traditional…

This paper extends a low-rank tensor decomposition (LRTD) reduced order model (ROM) methodology to simulate viscous flows and in particular to predict a smooth branch of solutions for the incompressible Navier-Stokes equations.…

流体动力学 · 物理学 2024-05-08 Maxim A. Olshanskii , Leo G. Rebholz

We develop a method to estimate space-time flow statistics from a limited set of known data. While previous work has focused on modeling spatial or temporal statistics independently, space-time statistics carry fundamental information about…

流体动力学 · 物理学 2020-01-08 Aaron Towne , Adrian Lozano-Duran , Xiang Yang

In fluid mechanics, a lot of authors have been executing their researches to obtain the analytical solutions of Navier-Stokes equations, even for 3D case of compressible gas flow or 3D case of non-stationary flow of incompressible fluid.…

偏微分方程分析 · 数学 2015-12-07 Sergey V. Ershkov

Reduced-order models were derived for plane Couette flow using Galerkin projection, with orthonormal basis functions taken as the leading controllability modes of the linearised Navier-Stokes system for a few low wavenumbers. Resulting…

流体动力学 · 物理学 2022-07-15 André V. G. Cavalieri , Petrônio A. S. Nogueira

This paper presents a reduced order approach for transient modeling of multiple moving objects in nonlinear crossflows. The Proper Orthogonal Decomposition method and the Galerkin projection are used to construct a reduced version of the…

流体动力学 · 物理学 2021-06-07 My Ha Dao

We consider the Navier-Stokes system with Oseen and rotational terms describing the stationary flow of a viscous incompressible fluid around a rigid body moving at a constant velocity and rotating at a constant angular velocity. In a…

偏微分方程分析 · 数学 2015-11-13 Paul Deuring , Stanislav Kracmar , Sarka Necasova

Computational fluid dynamics (CFD) simulations play an important role in engineering science and applications, however, it is not applicable for problems requiring a large number of repeated calculations. Accordingly, many reduced-order…

流体动力学 · 物理学 2026-05-28 Shan Ding , Yongfu Tian , Rui Yang

A method is proposed to estimate the velocity field of an unsteady flow using a limited number of flow measurements. The method is based on a non-linear low-dimensional model of the flow and on expanding the velocity field in terms of…

最优化与控制 · 数学 2009-11-13 Marcelo Buffoni , Simone Camarri , Angelo Iollo , Edoardo Lombardi , Maria-Vittoria Salvetti
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