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Machine learning techniques have been applied to enhance turbulence modeling in recent years. However, the "black box" nature of most machine learning techniques poses significant interpretability challenges in improving turbulence models.…

Fluid Dynamics · Physics 2025-08-22 Boqian Zhang , Juanmian Lei

In wall-modeled large-eddy simulations (WMLES), the near-wall model plays a significant role in predicting the skin friction, although the majority of the boundary layer is resolved by the outer large-eddy simulation (LES) solver. In this…

Fluid Dynamics · Physics 2020-10-09 Kevin Patrick Griffin , Lin Fu

Even though compressible plasma turbulence is encountered in many astrophysical phenomena, its effect is often not well understood. Furthermore, direct numerical simulations are typically not able to reach the extreme parameters of these…

Fluid Dynamics · Physics 2016-07-27 P. Grete , D. G. Vlaykov , W. Schmidt , D. R. G. Schleicher

Generalisability and the consistency of the a posteriori results are the most critical points of view regarding data-driven turbulence models. This study presents a progressive improvement of turbulence models using simulation-driven…

Fluid Dynamics · Physics 2025-03-26 M. J. Rincón , A. Amarloo , M. Reclari , X. I. A. Yang , M. Abkar

The Navier-Stokes equations describe the motion of viscous fluids. In order to predict turbulent flows with reasonable computational time and accuracy, these equations are spatially filtered according to the large-eddy simulation (LES)…

Fluid Dynamics · Physics 2018-07-02 Larissa B. Streher , Maurits H. Silvis , Roel Verstappen

We introduce a closure model for wall-modeled large-eddy simulation (WMLES), referred to as the Building-block Flow Model (BFM). The foundation of the model rests on the premise that a finite collection of simple flows encapsulates the…

Fluid Dynamics · Physics 2024-06-18 Gonzalo Arranz , Yuenong Ling , Sam Costa , Konrad Goc , Adrian Lozano-Duran

This article presents a formulation that extends the variational multiscale modelling for compressible large-eddy simulation to a vast family of compact nodal numerical methods represented by the high-order flux reconstruction scheme. The…

Computational Physics · Physics 2020-02-19 Farshad Navah , Marta de la Llave Plata , Vincent Couaillier

We study the sub-grid scale characteristics of a vorticity-transport-based approach for large-eddy simulations. In particular, we consider a multi-dimensional upwind scheme for the vorticity transport equations and establish its properties…

Fluid Dynamics · Physics 2021-02-05 Daniel Foti , Karthik Duraisamy

This work presents a converged framework of Machine-Learning Assisted Turbulence Modeling (MLATM). Our objective is to develop a turbulence model directly learning from high fidelity data (DNS/LES) with eddy-viscosity hypothesis induced.…

Fluid Dynamics · Physics 2019-07-09 Weishuo Liu , Jian Fang , Stefano Rolfo , Lipeng Lu

Vortex flows are ubiquitous in both natural processes and engineering applications, including phenomena such as typhoons, water currents, and aerospace fluid dynamics. The vortex particle method, a computational approach grounded in vortex…

Fluid Dynamics · Physics 2025-10-09 Ziqi Ji , Gang Du , Penghao Duan

Modelling sediment transport in environmental turbulent fluids is a challenge. This article develops a sound model of the lateral transport of suspended sediment in environmental fluid flows such as floods and tsunamis. The model is…

Dynamical Systems · Mathematics 2014-07-08 Meng Cao , A. J. Roberts

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…

Numerical Analysis · Mathematics 2025-10-20 T. Iliescu , P. Fischer

Unstable equilibrium solutions in a homogeneous shear flow with sinuous symmetry are numerically found in large-eddy simulations (LES) with no kinetic viscosity. The small-scale properties are determined by the mixing length scale $l_S$…

Fluid Dynamics · Physics 2017-10-11 Atsushi Sekimoto , Javier Jiménez

Potential flow theory remains a cornerstone of unsteady aerodynamics due to its computational efficiency in modeling complex flow phenomena. This study presents a significant advancement by integrating a viscous unsteady theory with…

Fluid Dynamics · Physics 2026-04-21 Rahul Kumar , Ramkumar Pathmanabhan

A sensitive porosity adjoint method (SPAM) for optimizing the topology of fluid machines has been proposed. A sensitivity function with respect to the porosity has been developed. In the first step of the optimization process, porous media…

Fluid Dynamics · Physics 2015-12-29 B. Philippi , Y. Jin

Despite well-known limitations of Reynolds-averaged Navier-Stokes (RANS) simulations, this methodology remains the most widely used tool for predicting many turbulent flows, due to computational efficiency. Machine learning is a promising…

Fluid Dynamics · Physics 2022-03-14 Ryley McConkey , Eugene Yee , Fue-Sang Lien

This paper studies the large-eddy simulation (LES) of isothermal turbulent channel flows. We investigate zero-equation algebraic models without wall function or wall model: functional models, structural models and mixed models. In addition…

Fluid Dynamics · Physics 2020-06-09 Dorian Dupuy , Adrien Toutant , Françoise Bataille

Computationally resolving turbulence remains a central challenge in fluid dynamics due to its multi-scale interactions. Fully resolving large-scale turbulence through direct numerical simulation (DNS) is computationally prohibitive,…

Machine Learning · Computer Science 2025-10-29 Yiheng Du , Aditi S. Krishnapriyan

Cavitation is a complex multiphase phenomenon characterised by vapour bubbles forming due to a sudden pressure drop and is often accompanied by increased hull vibrations, increased radiated noise and decrease in propeller and impeller…

Fluid Dynamics · Physics 2024-05-02 Dhruv Apte , Mingming Ge , Olivier Coutier-Delgosha

A semi-implicit, residual-based variational multiscale (VMS) formulation is developed for the incompressible Navier--Stokes equations. The approach linearizes convection using an extrapolated (Oseen-type) convecting velocity, producing a…

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