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The complex small-scale statistics of turbulence are a result of the combined cascading dynamics through all scales of the flow. Predicting these statistics using fully resolved simulations at the high Reynolds numbers that typically occur…

流体动力学 · 物理学 2025-07-01 Lukas Bentkamp , Michael Wilczek

Data-driven techniques have improved the accuracy of Reynolds-averaged Navier-Stokes (RANS) models in fluid dynamics. However, modeling separated flows remains challenging due to their complex physics and sensitivity to local conditions.…

流体动力学 · 物理学 2025-11-19 Ali Eidi , Tyler Buchanan , Letian Jiang , Richard P. Dwight

Data-driven turbulence modeling is a newly emerged research area in thermal hydraulics simulation of nuclear power plant (NPP). The most common CFD method used in NPP thermal hydraulics simulation is Reynolds-averaged Navier-Stokes (RANS)…

流体动力学 · 物理学 2020-05-04 Yangmo Zhu , Nam Dinh

This work proposes a new stabilized $P_1\times P_0$ finite element method for solving the incompressible Navier--Stokes equations. The numerical scheme is based on a reduced Bernardi--Raugel element with statically condensed face bubbles…

数值分析 · 数学 2023-04-06 Yuwen Li , Ludmil Zikatanov

This study proposes an algorithm for modeling compressible flows in spherical shells in nearly incompressible and weakly compressible regimes based on an implicit direction splitting approach. The method retains theoretically expected…

数值分析 · 数学 2021-04-21 Roman Frolov , Peter Minev , Aziz Takhirov

Traditional Reynolds-averaged Navier-Stokes (RANS) closures, based on the Boussinesq eddy viscosity hypothesis and calibrated on canonical flows, often yield inaccurate predictions of both mean flow and turbulence statistics. Here, we…

We investigate relationships between statistics obtained from filtering and from ensemble or Reynolds-averaging turbulence flow fields as a function of length scale. Generalized central moments in the filtering approach are expressed as…

流体动力学 · 物理学 2021-03-17 J. A. Saenz , D. Aslangil , D. Livescu

A local artificial neural network (LANN) framework is developed for turbulence modeling. The Reynolds-averaged Navier-Stokes (RANS) unclosed terms are reconstructed by artificial neural network (ANN) based on the local coordinate system…

流体动力学 · 物理学 2021-09-08 Chenyue Xie , Xiangming Xiong , Jianchun Wang

Models for solving the Reynolds-averaged Navier-Stokes equations are popular tools for predicting complex turbulent flows due to their computational affordability and ability to provide or estimate quantities of engineering interest.…

流体动力学 · 物理学 2024-09-10 Ty Homan , Omkar B. Shende , Ali Mani

Traditional computational fluid dynamics and physics-informed neural networks (PINNs) often suffer from high computational cost, mesh sensitivity, and reduced accuracy for strongly nonlinear and time-dependent flows. To address these…

流体动力学 · 物理学 2026-05-21 Biswanath Barman , Debdeep Chatterjee , Rajendra K. Ray

The applicability of computational fluid dynamics (CFD) based design tools depend on the accuracy and complexity of the physical models, for example turbulence models, which remains an unsolved problem in physics, and rotor models that…

流体动力学 · 物理学 2023-05-09 Shanti Bhushan , Greg W Burgreen , Joshua L Bowman , Ian D Dettwiller , Wesley Brewer

We introduce a residual-based stabilized formulation for incompressible Navier-Stokes flow that maintains discrete (and, for divergence-conforming methods, strong) mass conservation for inf-sup stable spaces with $H^1$-conforming pressure…

数值分析 · 数学 2019-11-07 John A. Evans , David Kamensky , Yuri Bazilevs

This article focusses on the analysis of a conforming finite element method for the time-dependent incompressible Navier-Stokes equations. For divergence-free approximations, in a semi-discrete formulation, we prove error estimates for the…

数值分析 · 数学 2018-03-20 Philipp W. Schroeder , Gert Lube

Computational fluid dynamics (CFD) solvers employing two-equation eddy viscosity models are the industry standard for simulating turbulent flows using the Reynolds-averaged Navier-Stokes (RANS) formulation. While these methods are…

机器学习 · 计算机科学 2024-10-25 Shinjan Ghosh , Amit Chakraborty , Georgia Olympia Brikis , Biswadip Dey

By analogy with the kinetic theory of gases, most turbulence modeling strate- gies rely on an eddy viscosity to model the unresolved turbulent fluctuations. How- ever, the ratio of unresolved to resolved scales - very much like a degree of…

流体动力学 · 物理学 2016-08-24 Marcello Righi

The oscillatory flow around a spherical object lying on a rough bottom is investigated by means of direct numerical simulations of continuity and Navier-Stokes equations. The rough bottom is simulated by a layer/multiple layers of spherical…

流体动力学 · 物理学 2017-06-28 Marco Mazzuoli , Paolo Blondeaux , Julian Simeonov , Joseph Calantoni

We use parsimonious diffusion maps (PDMs) to discover the latent dynamics of high-fidelity Navier-Stokes simulations with a focus on the 2D fluidic pinball problem. By varying the Reynolds number, different flow regimes emerge, ranging from…

流体动力学 · 物理学 2024-11-05 Alessandro Della Pia , Dimitris Patsatzis , Lucia Russo , Constantinos Siettos

The paper considers a system of equations that models a lateral flow of a Boussinesq--Scriven fluid on a passively evolving surface embedded in $\mathbb{R}^3$. For the resulting Navier-Stokes type system, posed on a smooth closed…

偏微分方程分析 · 数学 2022-03-04 Maxim A. Olshanskii , Arnold Reusken , Alexander Zhiliakov

We consider a Leray model with a nonlinear differential low-pass filter for the simulation of incompressible fluid flow at moderately large Reynolds number (in the range of a few thousands) with under-refined meshes. For the implementation…

数值分析 · 数学 2024-12-20 Michele Girfoglio , Annalisa Quaini , Gianluigi Rozza

This paper introduces a Variational Multiscale Stabilization (VMS) formulation of the incompressible Navier--Stokes equations that utilizes the Finite Element Exterior Calculus (FEEC) framework. The FEEC framework preserves the geometric…

数值分析 · 数学 2025-12-17 Kevin Dijkstra , Deepesh Toshniwal