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Turbulence modeling within the RANS equations' framework is essential in engineering due to its high efficiency. Field inversion and machine learning (FIML) techniques have improved RANS models' predictive capabilities for separated flows.…

Fluid Dynamics · Physics 2023-08-29 Chenyu Wu , Yufei Zhang

In the present paper, an aerodynamic investigation of a high-speed train is performed. In the first section of this article, a generic high-speed train against a turbulent flow is simulated, numerically. The Reynolds-Averaged Navier-Stokes…

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

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),…

Predicting the behavior of turbulent flows using large-eddy simulation requires modeling of the subgrid-scale stress tensor. This tensor can be approximated using mixed models, which combine the dissipative nature of functional models with…

Fluid Dynamics · Physics 2021-01-11 L. B. Streher , M. H. Silvis , P. Cifani , R. W. C. P. Verstappen

This article utilizes the Large-Eddy Simulation (LES) paradigm with a physics-based turbulence modeling approach, including a dynamic subgrid-scale model and an equilibrium wall model, to examine the flow over the NASA transonic Common…

Fluid Dynamics · Physics 2024-07-11 Konrad A. Goc , Rahul Agrawal , Sanjeeb T. Bose , Parviz Moin

It has previously been shown that by increasing the Reynolds number across a channel by spatially varying the viscosity does not cause an immediate change in the size of turbulent structures and a delay is in fact observed in both wall…

Fluid Dynamics · Physics 2021-06-11 Victor Coppo Leite , Elia Merzari

Reynolds-averaged Navier-Stokes (RANS) is one of the most cost-efficient approaches to simulate wind-farm-atmosphere interactions. However, the applicability of RANS-based methods is always limited by the accuracy of turbulence closure…

Fluid Dynamics · Physics 2021-12-08 Ali Eidi , Reza Ghiassi , Xiang Yang , Mahdi Abkar

To reduce the time-to-market of future aircraft, it is crucial to predict the flight envelope accurately before building prototypes for flight tests. The High-Lift Prediction Workshop (HLPW) series aims to assess the numerical prediction…

A new approach to turbulence simulation, based on a combination of large-eddy simulation (LES) for the whole flow and an array of non-space-filling quasi-direct numerical simulations (QDNS), which sample the response of near-wall turbulence…

Fluid Dynamics · Physics 2017-10-20 Neil D. Sandham , Roderick Johnstone , Christian T. Jacobs

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

A recently developed so-called explicit algebraic Reynolds-stress (EARS) model is applied to a transitioning atmospheric boundary layer (ABL). The simulation describes a diurnal cycle with a deep convective ABL during daytime and an…

Fluid Dynamics · Physics 2021-08-16 Velibor Želi , Stefan Wallin , Arne V. Johansson , Geert Brethouwer

Serrations are commonly employed to mitigate the turbulent boundary layer trailing-edge noise. However, significant discrepancies persist between model predictions and experimental observations. In this paper, we show that this results from…

Fluid Dynamics · Physics 2023-12-27 Haopeng Tian , Benshuai Lyu

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…

Fluid Dynamics · Physics 2025-01-27 Kazuko W. Fuchi , Eric M. Wolf , Christopher R. Schrock , Philip S. Beran

The simulation of high Reynolds number (Re) separated turbulent flows faces significant problems for decades: large eddy simulation (LES) is computationally too expensive, and Reynolds-averaged Navier-Stokes (RANS) methods and hybrid…

Fluid Dynamics · Physics 2024-12-02 Stefan Heinz , Adeyemi Fagbade

The paper examines the impact of different modelling choices in second-moment closures by assessing model performance in predicting 3-D duct flows. The test-cases (developing flow in a square duct [Gessner F.B., Emery A.F.: {\em ASME J.…

Fluid Dynamics · Physics 2016-02-17 G. A. Gerolymos , I. Vallet

We employ a resolvent-based methodology to estimate velocity and pressure fluctuations within turbulent channel flows at friction Reynolds numbers of approximately 180, 550 and 1000 using measurements of shear stress and pressure at the…

Fluid Dynamics · Physics 2021-10-04 Filipe R. Amaral , André V. G. Cavalieri , Eduardo Martini , Peter Jordan , Aaron Towne

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…

Steady-state RANS simulations are reported for 2D flow around an ellipse and a von-K\'arm\'an-Trefftz airfoil at seven different angles of attack and two different Reynolds numbers, computed using the $k \omega SST$ turbulence model in…

Fluid Dynamics · Physics 2026-04-13 Christian Bak Winther , Peter Ammundsen , Fynn Jerome Aschmoneit

The limitations of turbulence closure models in the context of Reynolds-averaged NavierStokes (RANS) simulations play a significant part in contributing to the uncertainty of Computational Fluid Dynamics (CFD). Perturbing the spectral…

Computational Engineering, Finance, and Science · Computer Science 2023-06-21 Marcel Matha , Christian Morsbach
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