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Use of appropriate initialization to warm-start Reynolds-averaged Navier-Stokes (RANS) simulations of turbulent flow can facilitate convergence and lead to efficient use of computational resources. In this work, a method to model downstream…

流体动力学 · 物理学 2025-01-27 Kazuko W. Fuchi , Eric M. Wolf , Christopher R. Schrock , Philip S. Beran

This work extends the framework of the partially-averaged Navier-Stokes (PANS) equations to variable-density flow, \text{i.e.}, multi-material and/or compressible mixing problems with density variations and production of turbulence kinetic…

流体动力学 · 物理学 2021-08-11 F. S. Pereira , F. F. Grinstein , D. M. Israel , R. Rauenzahn , S. S. Girimaji

In this paper, we propose normalizing flows (NF) as a novel probability density function (PDF) turbulence model (NF-PDF model) for the Reynolds-averaged Navier-Stokes (RANS) equations. We propose to use normalizing flows in two different…

流体动力学 · 物理学 2021-01-12 Deniz A. Bezgin , Nikolaus A. Adams

This study proposes a global similarity correction for Reynolds-averaged Navier--Stokes (RANS) modeling of buoyancy effects in unstably stratified flows. Conventional two-equation RANS models (e.g., the $k$-$\varepsilon$ model) lack a clear…

流体动力学 · 物理学 2025-03-14 Da-Sol Joo

Despite a cost-effective option in practical engineering, Reynolds-averaged Navier-Stokes simulations are facing the ever-growing demand for more accurate turbulence models. Recently, emerging machine learning techniques are making…

流体动力学 · 物理学 2021-05-04 Chao Jiang

A promising and cost-effective method for numerical simulation of high Re wall-bounded flows is wall-modeled large-eddy simulation. Most wall models are formulated from the Reynolds-averaged Navier-Stokes equations (RANS). These RANS-based…

流体动力学 · 物理学 2021-01-08 Ahmed Elnahhas , Adrián Lozano-Durán , Parviz Moin

Accurate and generalizable Reynolds-averaged Navier-Stokes (RANS) models for turbulent flows rely on effective closures, but currently available closures are notoriously unreliable. Kassinos et al. (J. Fluid Mechanics, 428, pp. 213-248,…

流体动力学 · 物理学 2026-03-02 Aaron Miller , Sahil Kommalapati , Robert Moser , Petros Koumoutsakos

Numerical simulations based on Reynolds-Averaged Navier--Stokes (RANS) equations are widely used in engineering design and analysis involving turbulent flows. However, RANS simulations are known to be unreliable in many flows of engineering…

流体动力学 · 物理学 2017-09-19 Jinlong Wu , Rui Sun , Sylvain Laizet , Heng Xiao

This paper presents a machine learning methodology to improve the predictions of traditional RANS turbulence models in channel flows subject to strong variations in their thermophysical properties. The developed formulation contains several…

流体动力学 · 物理学 2022-10-28 Rafael Diez Sanhueza , Stephan Smit , Jurriaan Peeters , Rene Pecnik

This paper presents numerical simulations of a bichromatic wave group propagating and breaking over a fixed breaker bar. The simulations are performed using a newly stabilized Reynolds-averaged Navier Stokes (RANS) two-equation turbulence…

流体动力学 · 物理学 2020-10-29 B. E. Larsen , D. A. van der A. , J. van der Zanden , G. Ruessink , D. R. Fuhrman

To fully evaluate a turbulent flow, Direct Numerical Simulation (DNS) is the most accurate method by far and requires considerable computational power and time; not optimum for industry standards. Developing an alternative model, providing…

流体动力学 · 物理学 2022-07-04 Indrajit Nandi , Saikat Saha , Sabir Subedi , Sumon Saha

The Reynolds-averaged Navier-Stokes (RANS) equations require accurate modeling of the anisotropic Reynolds stress tensor. Traditional closure models, while sophisticated, often only apply to restricted flow configurations. Researchers have…

流体动力学 · 物理学 2022-02-02 Haitz Sáez de Ocáriz Borde , David Sondak , Pavlos Protopapas

Fluid turbulence is an important problem for physics and engineering. Turbulence modeling deals with the development of simplified models that can act as surrogates for representing the effects of turbulence on flow evolution. Such models…

流体动力学 · 物理学 2021-11-16 J P Panda

Simulations based on Reynolds-Averaged Navier--Stokes (RANS) models have been used to support high-consequence decisions related to turbulent flows. Apart from the deterministic model predictions, the decision makers are often equally…

流体动力学 · 物理学 2017-01-25 Jian-Xun Wang , Jin-Long Wu , Heng Xiao

A multilevel Monte Carlo (MLMC) method for quantifying model-form uncertainties associated with the Reynolds-Averaged Navier-Stokes (RANS) simulations is presented. Two, high-dimensional, stochastic extensions of the RANS equations are…

计算物理 · 物理学 2018-11-05 Prashant Kumar , Martin Schmelzer , Richard P. Dwight

The article is devoted to the simulation of viscous incompressible turbulent fluid flow based on solving the Reynolds averaged Navier-Stokes (RANS) equations with different k-omega models. The isogeometrical approach is used for the…

Generalisability and the consistency of the a posteriori results are the most critical points of view regarding data-driven turbulence models. This study presents a progressive improvement of turbulence models using simulation-driven…

流体动力学 · 物理学 2025-03-26 M. J. Rincón , A. Amarloo , M. Reclari , X. I. A. Yang , M. Abkar

The volume of fluid (VOF) method is increasingly used in computational fluid dynamics (CFD) simulations of turbulent two-phase flows. The Reynolds-Averaged Navier-Stokes (RANS) approach is an economic and practical way for turbulent VOF…

计算物理 · 物理学 2019-11-25 Wenyuan Fan , Henryk Anglart

In order to achieve a virtual certification process and robust designs for turbomachinery, the uncertainty bounds for Computational Fluid Dynamics have to be known. The formulation of turbulence closure models implies a major source of the…

计算工程、金融与科学 · 计算机科学 2023-04-03 Marcel Matha , Karsten Kucharczyk , Christian Morsbach

There exists continuous demand of improved turbulence models for the closure of Reynolds Averaged Navier-Stokes (RANS) simulations. Machine Learning (ML) offers effective tools for establishing advanced empirical Reynolds stress closures on…

流体动力学 · 物理学 2021-04-01 Muyuan Liu , Yiren Yang , Hao Chen