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Explicit filtering in large eddy simulation (LES) of a turbulent barotropic flow on the sphere in spectral space is studied and compared to implicit filtering. Here, a smooth filter is applied to the nondivergent barotropic vorticity…

Fluid Dynamics · Physics 2014-04-08 Leila N. Azadani , Anne E. Staples

Most sub-grid scale (SGS) models employed in LES (large eddy simulation) formulations were originally developed for incompressible, single phase, inert flows and assume transfer of energy based on the classical energy cascade mechanism.…

Fluid Dynamics · Physics 2023-09-13 Jhon Cordova , Cesar Celis , Andres Mendiburu , Luis Bravo , Prashant Khare

While deep learning has shown tremendous success in a wide range of domains, it remains a grand challenge to incorporate physical principles in a systematic manner to the design, training, and inference of such models. In this paper, we aim…

Computational Physics · Physics 2020-06-16 Rui Wang , Karthik Kashinath , Mustafa Mustafa , Adrian Albert , Rose Yu

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…

Fluid Dynamics · Physics 2023-06-07 Adrián Lozano-Durán , H. Jane Bae

A simple variant of recycling and rescaling method to generate inflow turbulence using unstructured grid CFD codes is presented. The method has been validated on large eddy simulation of spatially developing flat plate turbulent boundary…

Fluid Dynamics · Physics 2014-08-22 Sunil K. Arolla

We show that in addition to providing effective and competitive closures, when analysed in terms of dynamics and physically-relevant diagnostics, artificial neural networks (ANNs) can be both interpretable and provide useful insights in the…

Computational Physics · Physics 2020-12-30 Gavin D. Portwood , Balasubramanya T. Nadiga , Juan A. Saenz , Daniel Livescu

One promising decomposition of turbulent dynamics is that into building blocks such as equilibrium and periodic solutions and orbits connecting these. While the numerical approximation of such building blocks is feasible for flows in small…

Fluid Dynamics · Physics 2018-11-14 Lennaert van Veen , Genta Kawahara , Tatsuya Yasuda

Simulation of turbulent flows, especially at the edges of clouds in the atmosphere, is an inherently challenging task. Hitherto, the best possible computational method to perform such experiments is the Direct Numerical Simulation (DNS).…

Fluid Dynamics · Physics 2022-08-19 Moumita Bhowmik , Manmeet Singh , Suryachandra Rao , Souvik Paul

Accurate prediction of wind flow fields in urban canopies is crucial for ensuring pedestrian comfort, safety, and sustainable urban design. Traditional methods using wind tunnels and Computational Fluid Dynamics, such as Large-Eddy…

Computational Physics · Physics 2025-07-10 Themistoklis Vargiemezis , Catherine Gorlé

This paper establishes a data-driven modeling framework for lean Hydrogen (H2)-air reaction rates for the Large Eddy Simulation (LES) of turbulent reactive flows. This is particularly challenging since H2 molecules diffuse much faster than…

Computational Engineering, Finance, and Science · Computer Science 2025-02-19 Quentin Malé , Corentin J Lapeyre , Nicolas Noiray

We describe and compare two time-periodic flows embedded in Large Eddy Simulation (LES) of turbulence in a three-dimensional, periodic domain subject to constant external forcing. One of these flows models the regeneration of large-scale…

Fluid Dynamics · Physics 2019-02-20 Lennaert van Veen , Alberto Vela Martin , Genta Kawahara , Tatsuya Yasuda

In this paper, we propose an approach for simulating wall-bounded incompressible turbulent flows by integrating the technology of random vortex method with the core principles of large-eddy simulations (LES). In particular, we employ the…

Fluid Dynamics · Physics 2025-11-11 Zihao Guo , Zhongmin Qian

Data-driven turbulence modeling is experiencing a surge in interest following algorithmic and hardware developments in the data sciences. We discuss an approach using the differentiable physics paradigm that combines known physics with…

Neural networks offer highly expressive turbulence closures, yet their complexity obscures the physical mechanisms they aim to model, and their computational cost can limit their tractability. To address these limitations, we introduce a…

Fluid Dynamics · Physics 2026-04-29 Samantha Friess , Aviral Prakash , John A. Evans

Reliable prediction of turbulent flows is an important necessity across different fields of science and engineering. In Computational Fluid Dynamics (CFD) simulations, the most common type of models are eddy viscosity models that are…

Fluid Dynamics · Physics 2023-07-25 Minghan Chu , Weicheng Qian

The performance of the nonlinearly stable flux reconstruction (NSFR) schemes for resolving subsonic viscous turbulent free-shear flows is investigated. The schemes are extensively verified for the direct numerical simulation (DNS) of the…

Fluid Dynamics · Physics 2024-11-20 Julien Brillon , Siva Nadarajah

We present a variant of the immersed boundary method integrated with octree meshes for highly efficient and accurate Large-Eddy Simulations (LES) of flows around complex geometries. We demonstrate the scalability of the proposed method up…

With increasing emphasis on carbon neutrality, accurate and efficient combustion prediction has become essential for the design and optimization of new generation combustion systems. This study established a computational framework by…

Direct numerical simulations (DNS) are performed to study the turbulent shear flow of an electrically conducting fluid in a cylindrical container. The flow is driven by the interaction between the radial electric currents ($I$) injected…

Fluid Dynamics · Physics 2021-04-21 Long Chen , Alban Pothérat , Ming-Jiu Ni , René Moreau

This work uses the Mori-Zwanzig (M-Z) formalism, a concept originating from non-equilibrium statistical mechanics, as a basis for the development of coarse-grained models of turbulence. The mechanics of the generalized Langevin equation…

Fluid Dynamics · Physics 2017-02-01 Eric J. Parish , Karthik Duraisamy