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相关论文: LES-informed resolvent-based estimation of turbule…

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Reynolds-Averaged Navier-Stokes (RANS) models are widely used for turbulent flow simulations due to their computational efficiency, but their accuracy strongly depends on the selected turbulence closure and may vary across the flow domain.…

数值分析 · 数学 2026-03-18 Piero Zappi , Anna Ivagnes , Niccolò Tonicello , Gianluigi Rozza

A procedure is presented to map from the spatial correlation parameters of a turbulent density field (the radial and binormal correlation lengths and wavenumbers, and the fluctuation amplitude) to correlation parameters that would be…

等离子体物理 · 物理学 2017-04-05 M. F. J. Fox , A. R. Field , F. van Wyk , Y. -c. Ghim , A. A. Schekochihin , the MAST Team

In this study, we conduct a parametric analysis to evaluate the sensitivities of wall-modeled large-eddy simulation (LES) with respect to subgrid-scale (SGS) models, mesh resolution, wall boundary conditions and mesh anisotropy. While such…

流体动力学 · 物理学 2024-03-26 Di Zhou , H. Jane Bae

SAM, a plant-level system analysis tool for advanced reactors (SFR, LFR, MSR/FHR) is under development at Argonne. As a modern system code, SAM aims to improve the predictions of 3D flows relevant to reactor safety during transient…

流体动力学 · 物理学 2020-05-04 Yangmo Zhu , Nam Dinh , Rui Hu , Adam Kraus

Traditional resolvent analysis is a powerful framework for identifying the most amplified input-output structures in fluid flows from a stationary base state. Extending this resolvent analysis to periodic base flows poses computational…

动力系统 · 数学 2026-03-18 Max Howell , Sicheng He

Two-way coupled DNS simulation of particle-laden turbulent Couette-flow [1], in the volume fraction regime $\phi>10^{-4}$, showed a discontinuous decrease of turbulence intensity beyond a critical volume fraction…

流体动力学 · 物理学 2022-04-04 Swagnik Ghosh , Partha Sarathi Goswami

We present direct numerical simulations (DNS) of laminar to turbulent transition in Herschel-Bulkley (HB) yield-stress fluids flowing through pipes and rectangular channels. The simulations employ a Herschel-Bulkley formulation that…

流体动力学 · 物理学 2026-03-13 Shivam Prajapati , Prasoon Suchandra , Vivek Kumar , Ardalan Javadi , Suhas Jain , Cyrus Aidun

In the last decade, progresses in additive manufacturing (AM) have paved the way for optimized heat exchangers, whose disruptive design will depend on predictive numerical simulations. Typical AM rough surfaces show limited resemblance to…

流体动力学 · 物理学 2023-05-10 Himani Garg , Lei Wang , Guillaume Sahut , Christer Fureby

The shock induced mixing of two gases separated by a perturbed interface is investigated through Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS). In a simulation, physical dissipation of the velocity field and species mass…

流体动力学 · 物理学 2015-06-18 Britton J. Olson , Jeffrey A. Greenough

Modeled Reynolds stress is a major source of model-form uncertainties in Reynolds-averaged Navier-Stokes (RANS) simulations. Recently, a physics-informed machine-learning (PIML) approach has been proposed for reconstructing the…

流体动力学 · 物理学 2021-07-23 Jian-Xun Wang , Junji Huang , Lian Duan , Heng Xiao

We have conducted a direct numerical simulation (DNS) study of dilute turbulent particulate flow in a vertical plane channel, considering thousands of finite-size rigid particles with resolved phase interfaces. The particle diameter…

流体动力学 · 物理学 2011-09-01 Markus Uhlmann

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

In fluid physics, data-driven models to enhance or accelerate solution methods are becoming increasingly popular for many application domains, such as alternatives to turbulence closures, system surrogates, or for new physics discovery. In…

Turbulent concentric coaxial (annular) pipe flow is numerically investigated using a stochastic one-dimensional turbulence (ODT) model as a stand-alone tool. The dimensionally reduced ODT domain enables fully resolved numerical simulations…

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

A wall model for large-eddy simulation (LES) is proposed by devising the flow as a combination of building blocks. The core assumption of the model is that a finite set of simple canonical flows contains the essential physics to predict the…

流体动力学 · 物理学 2023-06-07 Adrián Lozano-Durán , H. Jane Bae

Large-eddy simulation developments and validations are presented for an improved simulation of turbulent internal flows. Numerical methods are proposed according to two competing criteria: numerical qualities (precision and spectral…

流体动力学 · 物理学 2008-01-15 Jérôme Boudet , Joëlle Caro , L. Shao , Emmanuel Lévêque

We use Diffusing Wave Spectroscopy (DWS) to perform the first direct space- and time-resolved measurement of the dissipation rate~$\epsilon$ at the boundary of a turbulent flow. We have shown in a previous publication that this technique…

流体动力学 · 物理学 2025-11-06 Enzo Francisco , Julien Lambret , Sébastien Aumaître

Reynolds-averaged Navier-Stokes (RANS) equations are widely used in engineering turbulent flow simulations. However, RANS predictions may have large discrepancies due to the uncertainties in modeled Reynolds stresses. Recently, Wang et al.…

流体动力学 · 物理学 2018-09-11 Jin-Long Wu , Heng Xiao , Eric Paterson

Despite their well-known limitations, RANS models remain the most commonly employed tool for modeling turbulent flows in engineering practice. RANS models are predicated on the solution of the RANS equations, but these equations involve an…

流体动力学 · 物理学 2020-04-22 Eric L. Peters , Riccardo Balin , Kenneth E. Jansen , Alireza Doostan , John A. Evans

High-fidelity modeling of turbulent flows is one of the major challenges in computational physics, with diverse applications in engineering, earth sciences and astrophysics, among many others. The rising popularity of high-fidelity…

流体动力学 · 物理学 2019-03-06 Arvind Mohan , Don Daniel , Michael Chertkov , Daniel Livescu