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Direct numerical simulations of the incompressible Navier-Stokes equations are not feasible yet for most practical turbulent flows. Therefore, dynamically less complex mathematical formulations are necessary for coarse-grained simulations.…

流体动力学 · 物理学 2017-12-04 F. X. Trias , A. Gorobets , M. H. Silvis , R. W. C. P. Verstappen , A. Oliva

Traditional large eddy simulation is based on Kolmogrov's hypothesis, and done in the inertial range. In inertial range the LES model coefficient is scale-invariant. In many cases, such as computing in the boundary layer, the filter scale…

流体动力学 · 物理学 2014-08-18 Changping Yu

We present a wall model for large-eddy simulation that incorporates surface-roughness effects and is applicable across low- and high-speed flows, for both transitional and fully rough conditions. The model, implemented using an artificial…

流体动力学 · 物理学 2026-01-29 Rong Ma , Adrian Lozano-Duran

We present a framework based on the generalized lattice-Boltzmann equation using multiple relaxation times with forcing term for eddy capturing simulation of wall bounded turbulent flows. Due to its flexibility in using disparate relaxation…

计算物理 · 物理学 2009-11-13 Kannan N. Premnath , Martin J. Pattison , Sanjoy Banerjee

We present a data-driven approach to Reynolds-averaged Navier-Stokes turbulence closure modelling in magnetohydrodynamic (MHD) flows. In these flows the magnetic field interacting with the conductive fluid induces unconventional turbulence…

The prediction of aircraft aerodynamic quantities of interest remains among the most pressing challenges for computational fluid dynamics. The aircraft aerodynamics are inherently turbulent with mean-flow three-dimensionality, often…

流体动力学 · 物理学 2021-05-25 Adrián Lozano-Durán , Hyunji Jane Bae

Direct Numerical Simulations (DNSs) are one of the most powerful tools for studying turbulent flows. Even if achievable Reynolds numbers are lower than those obtained with experimental means, there is a clear advantage since the entire…

流体动力学 · 物理学 2024-06-03 Sergio Hoyas , Ricardo Vinuesa , Peter Schmid , Hassan Nagib

Hybrid Reynolds-averaged Navier Stokes large eddy simulation (RANS LES) methods have become popular for simulation of massively separated flows at high Reynolds numbers due to their reduced computational cost and good accuracy. The current…

流体动力学 · 物理学 2021-02-19 Gaurav Kumar , Ashoke De , Harish Gopalan

In large eddy simulations, the Reynolds averages of nonlinear terms are not directly computable in terms of the resolved variables and require a closure hypothesis or model, known as a subgrid scale term. Inspired by the renormalization…

流体动力学 · 物理学 2013-09-26 J. Glimm , B. Plohr , D. Sharp

Euler-Lagrange (EL) point-particle simulations rely on hydrodynamic force closure models to accurately predict particle dynamics in flows. The closure models currently employed for dilute particle-laden flows require the undisturbed fluid…

流体动力学 · 物理学 2025-03-06 Akshay Chandran , Fabien Evrard , Berend van Wachem

Despite the increasing availability of high-performance computational resources, Reynolds-Averaged Navier-Stokes (RANS) simulations remain the workhorse for the analysis of turbulent flows in real-world applications. Linear eddy viscosity…

流体动力学 · 物理学 2023-11-27 Leon Riccius , Atul Agrawal , Phaedon-Stelios Koutsourelakis

Despite well-known limitations of Reynolds-averaged Navier-Stokes (RANS) simulations, this methodology remains the most widely used tool for predicting many turbulent flows, due to computational efficiency. Machine learning is a promising…

流体动力学 · 物理学 2022-03-14 Ryley McConkey , Eugene Yee , Fue-Sang Lien

This article presents a formulation that extends the variational multiscale modelling for compressible large-eddy simulation to a vast family of compact nodal numerical methods represented by the high-order flux reconstruction scheme. The…

计算物理 · 物理学 2020-02-19 Farshad Navah , Marta de la Llave Plata , Vincent Couaillier

In turbulence research and flow applications, turbulence models like RaNS (Reynolds averaged Navier-Stokes) models and LES (Large Eddy Simulation) are used. Both models filter the governing flow equations. Thus a scale separation approach…

流体动力学 · 物理学 2015-06-17 Christoph Glawe , Heiko Schmidt , Alan R. Kerstein , Rupert Klein

Accurate prediction of mixing transition induced by interfacial instabilities is vital for engineering applications, but has remained a great challenge for decades. For engineering practices, Reynolds-averaged Navier-Stokes simulation…

流体动力学 · 物理学 2023-10-02 Hansong Xie , Mengjuan Xiao , Yousheng Zhang , Yaomin Zhao

We provide analytical and numerical results concerning multi-scale correlations between the resolved velocity field and the subgrid-scale (SGS) stress-tensor in large eddy simulations (LES). Following previous studies for Navier-Stokes…

流体动力学 · 物理学 2018-05-08 Moritz Linkmann , Michele Buzzicotti , Luca Biferale

Natural ventilation is gaining popularity in response to an increasing demand for a sustainable and healthy built environment, but the design of a naturally ventilated building can be challenging due to the inherent variability in the…

流体动力学 · 物理学 2023-02-09 Yunjae Hwang , Catherine Gorlé

In large eddy simulation of atmospheric boundary layer flows over wind farms, wall-layer models are generally imposed for the surface fluxes without considering the spatial variability of the surface roughness. In this study, we consider…

流体动力学 · 物理学 2022-05-03 Jagdeep Singh , Jahrul Alam

Aerodynamic prediction of glaze ice accretion on airfoils and wing is studied using the Reynolds-averaged Navier-Stokes method. Two separation fixed turbulence models are developed considering the nonequilibrium characteristics of…

流体动力学 · 物理学 2021-05-27 Haoran Li , Yufei Zhang , Haixin Chen

We develop an enrichment wall-model within the spectral element method (SEM) framework for large-eddy simulations of wall-bounded flows. The method augments the polynomial solution in the wall-adjacent elements with an analytical…

流体动力学 · 物理学 2024-11-22 Steven R. Brill , Pinaki Pal , Muhsin Ameen , Chao Xu , Matthias Ihme