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We report the first high-order eddy-resolving simulation of flow over a marine propeller using a recently developed high-order sliding-mesh method. This method employs the flux reconstruction framework and a new dynamic curved mortar…

流体动力学 · 物理学 2021-06-07 Bin Zhang , Chi Ding , Chunlei Liang

To bridge the gap between high and low fidelity numerical modeling tools for vertical-axis (or cross-flow) turbines (VATs or CFTs), an actuator line model (ALM) was developed and validated for both a high and a medium solidity vertical-axis…

流体动力学 · 物理学 2018-09-25 Peter Bachant , Anders Goude , Martin Wosnik

We study turbulent flows in pressure-driven ducts with square cross-section through direct numerical simulation in a wide enough range of Reynolds number to reach flow conditions which are representative of fully developed turbulence.…

流体动力学 · 物理学 2018-03-14 S. Pirozzoli , D. Modesti , P. Orlandi , F. Grasso

The Eulerian-Lagrangian approach based on Large-Eddy Simulation (LES) is one of the most promising and viable numerical tools to study turbulent dispersed flows when the computational cost of Direct Numerical Simulation (DNS) becomes too…

流体动力学 · 物理学 2017-06-02 Alessio Innocenti , Cristian Marchioli , Sergio Chibbaro

This article provides a reduced-order modelling framework for turbulent compressible flows discretized by the use of finite volume approaches. The basic idea behind this work is the construction of a reduced-order model capable of providing…

流体动力学 · 物理学 2024-05-31 Matteo Zancanaro , Valentin Nkana Ngan , Giovanni Stabile , Gianluigi Rozza

Hypersonic flow conditions pose exceptional challenges for Reynolds-Averaged Navier-Stokes (RANS) turbulence modeling. Critical phenomena include compressibility effects, shock/turbulent boundary layer interactions, turbulence-chemistry…

流体动力学 · 物理学 2025-04-30 Pratikkumar Raje , Eric Parish , Jean-Pierre Hickey , Paola Cinnella , Karthik Duraisamy

In the present paper a new data-driven model is proposed to close and increase accuracy of RANS equations. The divergence of the Reynolds Stress Tensor (RST) is obtained through a Neural Network (NN) whose architecture and input choice…

流体动力学 · 物理学 2022-10-19 Stefano Berrone , Davide Oberto

Although Reynolds-Averaged Navier-Stokes (RANS) equations are still the dominant tool for engineering design and analysis applications involving turbulent flows, standard RANS models are known to be unreliable in many flows of engineering…

计算物理 · 物理学 2018-09-11 Jin-Long Wu , Jian-Xun Wang , Heng Xiao , Julia Ling

Complex turbulent flow simulations are an integral aspect of the engineering design process. The mainstay of these simulations is represented by eddy viscosity based turbulence models. Eddy viscosity models are computationally cheap due to…

流体动力学 · 物理学 2024-08-14 Minghan Chu , Weicheng Qian

The explicit filtering method for large eddy simulation (LES,) which comprises integration of the governing equations without any added terms for sub-grid-scale modeling, and the application of a low-pass filter to transported fields, is…

流体动力学 · 物理学 2017-10-06 Joseph Mathew

One of the main challenges in simulating high Reynolds number ($Re$) turbulent boundary layers (TBLs) is the long streamwise distance required for large-scale outer-layer structures to develop, making such simulations prohibitively…

流体动力学 · 物理学 2025-12-12 Ronith Stanly , Timofey Mukha , Martin Karp , Stefano Markidis , Philipp Schlatter

Large Eddy Simulation (LES) of turbulent non-Newtonian flows involves two additional closures, namely the Non-Newtonian SubGrid-Scale (NNSGS) stress tensor and filtered viscosity. Here, dynamic closures are proposed for NNSGS, eliminating…

流体动力学 · 物理学 2025-11-14 E. Amani , A. Ahmadpour , M. J. Aghajari

Turbulence in fluids, gases, and plasmas remains an open problem of both practical and fundamental importance. Its irreducible complexity usually cannot be tackled computationally in a brute-force style. Here, we combine Large Eddy…

计算物理 · 物理学 2023-09-29 Robin Greif , Frank Jenko , Nils Thuerey

The application machine learning (ML) algorithms to turbulence modeling has shown promise over the last few years, but their application has been restricted to eddy viscosity based closure approaches. In this article we discuss rationale…

流体动力学 · 物理学 2021-05-31 J. P. Panda , H. V. Warrior

We construct a new subgrid scale (SGS) stress model for representing the small scale effects in large eddy simulation (LES) of incompressible flows. We use the covariance tensor for representing the Reynolds stress and include Clark's model…

流体动力学 · 物理学 2016-01-14 Rukiye Kara , Mine Caglar

In this review, the methodology of large eddy simulations (LES) is introduced and applications in astrophysics are discussed. As theoretical framework, the scale decomposition of the dynamical equations for compressible neutral fluids by…

星系天体物理 · 物理学 2025-09-09 Wolfram Schmidt-Brückner

In the context of many applications of turbulent multi-phase flows, knowledge of the dispersed phase size distribution and its evolution is critical to predicting important macroscopic features. We use a population dynamics model for…

流体动力学 · 物理学 2021-04-19 Aditya Aiyer , Di Yang , Marcelo Chamecki , Charles Meneveau

A new computational methodology, termed "PeleLM-FDF" is developed and utilized for high fidelity large eddy simulation (LES) of complex turbulent combustion systems. This methodology is constructed via a hybrid scheme combining the Eulerian…

流体动力学 · 物理学 2023-01-11 Aidyn Aitzhan , Shervin Sammak , Peyman Givi , Arash G. Nouri

The analysis of the Reynolds Stress Transport Equation (RSTE) provides fundamental physical insights that are essential for the development and validation of advanced turbulence models. However, a comprehensive and validated tool for…

流体动力学 · 物理学 2025-11-07 Mario J. Rincón , Christoffer Hansen , Martino Reclari , Mahdi Abkar

We conducted direct numerical simulations of turbulent open channel flow (OCF) and closed channel flow (CCF) of friction Reynolds numbers up to $\mathrm{Re}_\tau \approx 900$ in large computational domains up to $L_x\times L_z=12\pi h…

流体动力学 · 物理学 2023-10-30 Christian Bauer , Yoshiyuki Sakai , Markus Uhlmann
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