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Direct numerical simulation (DNS), mostly used in fundamental turbulence research, is limited to low turbulent intensities due the current and future computer resources. Standard turbulence models, like RaNS (Reynolds averaged…

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

In this paper we overcome a key problem in an otherwise highly potential approach to study turbulent flows, ODTLES (One-Dimensional Turbulence Large Eddy Simulation). From a methodological point of view, ODTLES is an approach in between…

流体动力学 · 物理学 2018-06-06 Christoph Glawe , Juan A. Medina M. , Heiko Schmidt

The rational large eddy simulation (RLES) model is applied to turbulent channel flows. This approximate deconvolution model is based on a rational (subdiagonal Pade') approximation of the Fourier transform of the Gaussian filter and is…

数值分析 · 数学 2025-10-20 T. Iliescu , P. Fischer

Direct numerical simulations (DNS) are one of the main ab initio tools to study turbulent flows. However, due to their considerable computational cost, DNS are primarily restricted to canonical flows at moderate Reynolds numbers, in which…

流体动力学 · 物理学 2024-09-17 Arnab Moitro , Sai Sandeep Dammati , Alexei Y. Poludnenko

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…

流体动力学 · 物理学 2017-10-20 Neil D. Sandham , Roderick Johnstone , Christian T. Jacobs

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…

流体动力学 · 物理学 2024-12-02 Stefan Heinz , Adeyemi Fagbade

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…

流体动力学 · 物理学 2021-05-19 Karthik Duraisamy

Direct numerical simulation (DNS) of turbulent flows is computationally expensive and cannot be applied to flows with large Reynolds numbers. Large eddy simulation (LES) is an alternative that is computationally less demanding, but is…

流体动力学 · 物理学 2021-09-09 Shengyu Chen , Shervin Sammak , Peyman Givi , Joseph P. Yurko1 , Xiaowei Jia

While direct numerical simulations (DNS) are the most accurate method for studying turbulence, their large computational cost restricts their use to idealized configurations and to Reynolds numbers well below those found in practical…

流体动力学 · 物理学 2025-12-09 Chang Hsin Chen , Arnab Moitro , Alexei Y. Poludnenko

One of the more promising recent approaches to turbulence modelling is the Variational Multiscale Large Eddy Simulation (VMS LES) method proposed by Hughes et al. [Comp. Visual. Sci., vol. 3, pp. 47-59, 2000]. This method avoids several…

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

Predictive simulation of many complex flows requires moving beyond Reynolds-averaged Navier-Stokes (RANS) based models to representations resolving at least some scales of turbulence in at least some regions of the flow. To resolve…

流体动力学 · 物理学 2018-12-11 Sigfried Haering , Todd A. Oliver , Robert D. Moser

The precise simulation of turbulent flows holds immense significance across various scientific and engineering domains, including climate science, freshwater science, and energy-efficient manufacturing. Within the realm of simulating…

流体动力学 · 物理学 2024-12-31 Shengyu Chen , Peyman Givi , Can Zheng , Xiaowei Jia

Reliably predictive simulation of complex flows requires a level of model sophistication and robustness exceeding the capabilities of current Reynolds-averaged Navier-Stokes (RANS) models. The necessary capability can often be provided by…

流体动力学 · 物理学 2022-01-20 Sigfried W. Haering , Todd A. Oliver , Robert D. Moser

Turbulent flow has been extensively studied using computational fluid dynamics (CFD) simulations since turbulent flow regime is so frequently encountered in both academic and engineering applications. The high-fidelity simulation of the…

流体动力学 · 物理学 2024-05-21 Minghan Chu

Wall-bounded turbulence is relevant for many engineering and natural science applications, yet there are still aspects of its underlying physics that are not fully understood, particularly at high Reynolds numbers. In this study, we…

流体动力学 · 物理学 2024-04-04 Himani Garg , Lei Wang , Martin Andersson , Christer Fureby

The interaction between turbulence and surface tension is studied numerically using the one-dimensional-turbulence (ODT) model. ODT is a stochastic model simulating turbulent flow evolution along a notional one-dimensional line of sight by…

流体动力学 · 物理学 2024-04-16 A. Movaghar , R. Chiodi , M. Oevermann , O. Desjardins , A. R. Kerstein

Large eddy simulation (LES) has become a central technique for simulating turbulent flows in engineering and applied sciences, offering a compromise between accuracy and computational cost by resolving large scale motions and modeling the…

流体动力学 · 物理学 2025-08-27 Rik Hoekstra , Wouter Edeling

Turbulent concentric coaxial pipe flows are numerically investigated as canonical problem addressing spanwise curvature effects on heat and momentum transfer that are encountered in various engineering applications. It is demonstrated that…

流体动力学 · 物理学 2026-02-04 Marten Klein , Pei-Yun Tsai , Heiko Schmidt

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…

流体动力学 · 物理学 2018-03-13 Fardin Khalili , Peshala P. T. Gamage , Hansen A. Mansy
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