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Deep learning (DL)-based Reynolds stress with its capability to leverage values of large data can be used to close Reynolds-averaged Navier-Stoke (RANS) equations. Type I and Type II machine learning (ML) frameworks are studied to…

Fluid Dynamics · Physics 2022-07-28 Chih-Wei Chang , Nam T. Dinh

This work extends a pressure-gradient sensor for boundary-layer separation originally developed for the $k-\omega$ shear-stress transport Reynolds-averaged Navier-Stokes (RANS) model (Griffin et al., 2025, J. Turb.) to the Improved Delayed…

Variable density flows occur in a variety of different systems with a wide range of scales, from astrophysics to atmospheric flows to inertial confinement fusion or reacting flows. Given the inherent limitations of RANS simulations, it is…

Fluid Dynamics · Physics 2020-01-01 Jan Felix Heyse , Zhu Huang , Gianluca Iaccarino

Buoyant shear layers are encountered in many engineering and environmental applications and have been studied by researchers in the context of experiments and modeling for decades. Often, these flows have high Reynolds and Richardson…

Fluid Dynamics · Physics 2021-07-27 Naman Jain , Hieu T. Pham , Xinyi Huang , Sutanu Sarkar , Xiang Yang , Robert Kunz

Most turbulence models used in Reynolds-averaged Navier-Stokes (RANS) simulations are partial differential equations (PDE) that describe the transport of turbulent quantities. Such quantities include turbulent kinetic energy for eddy…

Fluid Dynamics · Physics 2022-02-18 Ruiying Xu , Xu-Hui Zhou , Jiequn Han , Richard P. Dwight , Heng Xiao

The study presents wall-modeled large-eddy simulations (LES) characterizing the flow features of a neutral atmospheric boundary layer over two urban-like roughness geometries: an array of three-dimensional square prisms and the…

The rheology of surface granular flows is investigated by means of measurements of velocity and number density profiles in a quasi-two-dimensional rotating cylinder, half-filled with mono-disperse steel balls. The measurements are made at…

Soft Condensed Matter · Physics 2015-06-25 Ashish V. Orpe , D. V. Khakhar

This work presents a review and perspectives on recent developments in the use of machine learning (ML) to augment Reynolds-averaged Navier--Stokes (RANS) and Large Eddy Simulation (LES) models of turbulent flows. Different approaches of…

Fluid Dynamics · Physics 2021-05-19 Karthik Duraisamy

This study focuses on the numerical simulation of high Reynolds number separated flows and proposes a data-driven approach to improve the predictive capability of the SA turbulence model. First, data assimilation was performed on two…

Fluid Dynamics · Physics 2025-03-13 Xuxiang Sun , Xianglin Shan , Yilang Liu , Weiwei Zhang

Boundary layer transition triggered by a discrete roughness element generates a turbulent wedge that spreads laterally as it proceeds downstream. Historical literature reports the spreading half angle is approximately 6$^{\circ}$ in…

Fluid Dynamics · Physics 2024-07-19 Alexandre R. Berger , Edward B. White

Explicit quantification of uncertainty in engineering simulations is being increasingly used to inform robust and reliable design practices. In the aerospace industry, computationally-feasible analyses for design optimization purposes often…

Fluid Dynamics · Physics 2019-11-13 Jayant Mukhopadhaya , Brian T. Whitehead , John F. Quindlen , Juan J. Alonso

Large Eddy Simulations of a flow at a moderate Reynolds number over and around a three-dimensional hill have been performed. The main aim of the simulations was to study the effects of various inflow conditions (boundary layer thickness and…

Fluid Dynamics · Physics 2017-08-24 Manuel Garcia-Villalba , Jan G. Wissink , Wolfgang Rodi

The paper is devoted to two-phase flow simulations and investigates the ability of a diffusive interface Cahn-Hilliard Volume-of-Fluid model to capture the dynamics of the air-sea interface at geophysically relevant Reynolds numbers. It…

Airflow simulation results depend on a good prediction of near wall turbulence. In this paper a comparative study between different near wall treatments is presented. It is applied to two test cases: (1) the first concerns the fully…

Classical Physics · Physics 2010-11-30 Najla El Gharbi , Rafik Absi , Ahmed Benzaoui , E. H. Amara

We investigate eddy-viscosity distributions in pressure-driven wall turbulence for three canonical configurations: plane closed-channel flow, open-channel flow with a free-slip surface, and pipe flow. Using direct numerical simulation (DNS)…

Fluid Dynamics · Physics 2026-04-13 Ben-Rui Xu , Ao Xu

The dynamics of the Reynolds stress tensor for turbulent flows is described with an evolution equation coupling both geometric effects and turbulent source terms. The effects of the mean flow geometry are shown up when the source terms are…

Classical Physics · Physics 2017-08-23 Sergey L. Gavrilyuk , Henri Gouin

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…

Fluid Dynamics · Physics 2025-03-14 Da-Sol Joo

We investigate the error scaling and computational cost of wall-modeled large-eddy simulation (WMLES) for external aerodynamic applications. The NASA Juncture Flow is used as representative of an aircraft with trailing-edge smooth-body…

Fluid Dynamics · Physics 2021-07-06 Adrián Lozano-Durán , Sanjeeb T. Bose , Parviz Moin

We investigate the shock-induced flow through random particle arrays using particle-resolved Large Eddy Simulations for different incident shock wave Mach numbers, particle volume fractions and particle sizes. We analyze trends in mean flow…

Real-time and accurate prediction of aerodynamic flow fields around airfoils is crucial for flow control and aerodynamic optimization. However, achieving this remains challenging due to the high computational costs and the non-linear nature…

Fluid Dynamics · Physics 2025-10-23 Chunyang Wang , Biyue Pan , Zhibo Dai , Yudi Cai , Yuhao Ma , Hao Zheng , Dixia Fan , Hui Xiang