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Computational fluid dynamics (CFD) is a useful tool for prediction of turbulence in aerodynamic and biomedical applications. The choice of appropriate turbulence models is key to reaching accurate predictions. The present investigation…

Fluid Dynamics · Physics 2018-03-13 Fardin Khalili , Peshala P. T. Gamage , Hansen A. Mansy

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…

Fluid Dynamics · Physics 2021-01-08 Ahmed Elnahhas , Adrián Lozano-Durán , Parviz Moin

This paper presents a Weakly Compressible Smoothed Particle Hydrodynamics (WCSPH) method for solving the two-equation Reynolds-Averaged Navier-Stokes (RANS) model. The turbulent wall-bounded flow with or without mild flow separation, a…

Fluid Dynamics · Physics 2025-01-31 Feng Wang , Zhongguo Sun , Xiangyu Hu

Shell models have found wide application in the study of hydrodynamic turbulence because they are easily solved numerically even at very large Reynolds numbers. Although bereft of spatial variation, they accurately reproduce the main…

Chaotic Dynamics · Physics 2021-08-11 Dario Vincenzi , John D. Gibbon

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…

Fluid Dynamics · Physics 2021-04-01 Muyuan Liu , Yiren Yang , Hao Chen

This study has presented a comprehensive computational fluid dynamics (CFD) analysis of combustion flow in a realistic can combustor, evaluating the influence of various turbulence models on flow, thermal, and species fields. The…

Fluid Dynamics · Physics 2026-05-20 Aishvarya Kumar , Ram Prakash Bharti

Turbulence models attempt to account for unresolved dynamics and diffusion in hydrodynamical simulations. We develop a common framework for two-equation Reynolds-Averaged Navier-Stokes (RANS) turbulence models, and we implement six models…

Astrophysics of Galaxies · Physics 2017-03-28 Matthew D. Goodson , Fabian Heitsch , Karl Eklund , Virginia A. Williams

Cavitation is a complex multiphase phenomenon characterised by vapour bubbles forming due to a sudden pressure drop and is often accompanied by increased hull vibrations, increased radiated noise and decrease in propeller and impeller…

Fluid Dynamics · Physics 2024-05-02 Dhruv Apte , Mingming Ge , Olivier Coutier-Delgosha

We study the Reynolds number scaling and the geometric self-similarity of a gain-based, low-rank approximation to turbulent channel flows, determined by the resolvent formulation of McKeon & Sharma (2010), in order to obtain a description…

Fluid Dynamics · Physics 2014-05-22 Rashad Moarref , Ati S. Sharma , Joel A. Tropp , Beverley J. McKeon

The main objective of this work is to develop a unified framework that can be used as a lens to quantitatively assess and augment a wide range of coarse-grained models of turbulence, viz. large eddy simulations (LES), hybrid…

Fluid Dynamics · Physics 2023-01-25 Aniruddhe Pradhan , Karthik Duraisamy

We introduce a novel approach to derive compressibility corrections for Reynolds-averaged Navier-Stokes (RANS) models. Using this approach, we derive variable-property corrections for wall-bounded flows that take into account the distinct…

Fluid Dynamics · Physics 2025-09-17 Asif Manzoor Hasan , Alex Jose Elias , Florian Menter , Rene Pecnik

A priori tests of turbulence models for the compressible Reynolds-Averaged Navier--Stokes (RANS) are performed by using Direct Numerical Simulations (DNS) data of zero-pressure-gradient flat-plate turbulent boundary layers. The DNS database…

Fluid Dynamics · Physics 2023-10-17 Sciacovelli L. , Cannici A. , Passiatore D. , Cinnella P

Computational fluid dynamics using the Reynolds-averaged Navier-Stokes (RANS) remains the most cost-effective approach to study wake flows and power losses in wind farms. The underlying assumptions associated with turbulence closures are…

Fluid Dynamics · Physics 2022-08-03 Ali Eidi , Navid Zehtabiyan-Rezaie , Reza Ghiassi , Xiang Yang , Mahdi Abkar

This paper presents a novel CFD-driven machine learning framework to develop Reynolds-averaged Navier-Stokes (RANS) models. The CFD-driven training is an extension of the gene expression programming method (Weatheritt and Sandberg, 2016),…

Wall-modeled large-eddy simulation (WMLES) is widely recognized as a useful method for simulation of turbulent flows at high Reynolds numbers. Nevertheless, a continual issue in different wall models is the shift of the mean velocity…

Fluid Dynamics · Physics 2024-11-20 Huan-Cong Liu , Chun-Xiao Xu , Wei-Xi Huang

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…

The effect of grid resolution on large eddy simulation (LES) of wall-bounded turbulent flow is investigated. A channel flow simulation campaign involving systematic variation of the streamwise ($\Delta x$) and spanwise ($\Delta z$) grid…

Fluid Dynamics · Physics 2018-05-23 Saleh Rezaeiravesh , Mattias Liefvendahl

We use laser-Doppler velocimetry (LDV) experiments and Reynolds-averaged Navier--Stokes (RANS) simulations to study the characteristic flow patterns downstream of a standardized clockwise swirl disturbance generator. After quantifying the…

Fluid Dynamics · Physics 2015-10-27 Diego del Olmo Díaz , Denis F. Hinz

Reynolds-averaged Navier-Stokes (RANS) turbulence models (such as k-\epsilon models) are still widely used for engineering applications because of their relatively simplicity and robustness. In fully developed plane channel flow (i.e. the…

Fluid Dynamics · Physics 2010-12-01 Najla El Gharbi , Rafik Absi , Ahmed Benzaoui

This work introduces a novel data-driven framework to formulate explicit algebraic Reynolds-averaged Navier-Stokes (RANS) turbulence closures. Recent years have witnessed a blossom in applying machine learning (ML) methods to revolutionize…

Fluid Dynamics · Physics 2023-01-24 Hongwei Tang , Yan Wang , Tongguang Wang , Linlin Tian