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The present research proposes a new memory-efficient method using diffusion models to inject turbulent inflow conditions into Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) for various flow problems. A guided diffusion…

We introduce a reinforcement learning (RL) environment to design and benchmark control strategies aimed at reducing drag in turbulent fluid flows enclosed in a channel. The environment provides a framework for computationally-efficient,…

Fluid Dynamics · Physics 2023-02-09 L. Guastoni , J. Rabault , P. Schlatter , H. Azizpour , R. Vinuesa

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…

Fluid Dynamics · Physics 2025-12-09 Chang Hsin Chen , Arnab Moitro , Alexei Y. Poludnenko

Proper-orthogonal decomposition (POD) based reduced-order models (ROM) of structurally dominant fluid flow can support a wide range of engineering applications. Yet, although they perform well for unsteady laminar flows, their…

Fluid Dynamics · Physics 2025-03-11 Haroon Imtiaz , Imran Akhtar , Muhammad R. Hajj

This proposed work introduces a data-assimilation-assisted approach to train neural networks, aimed at effectively reducing epistemic uncertainty in state estimates of separated flows. This method, referred to as model-consistent training,…

Fluid Dynamics · Physics 2024-08-02 Minghan Chu

Extending gradient-type turbulence closures to turbulent premixed flames is challenging due to the significant influence of combustion heat release. We incorporate a deep neural network (DNN) into Reynolds-averaged Navier--Stokes (RANS)…

Fluid Dynamics · Physics 2025-06-18 Priyesh Kakka , Jonathan F. MacArt

A dynamic mixed super-resolution model (DMSRM) for large-eddy simulations (LESs) is proposed, which combines the traditional dynamic mixed model (DMM) formulation with the generation of super-resolved velocity fields from which the…

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

Large-eddy simulation (LES) of a turbulent flow through an array of building-like obstacles is an idealized model to study transport of contaminants in the urban atmospheric boundary layer (UABL). A reasonably accurate LES prediction of…

Fluid Dynamics · Physics 2017-11-09 Jahrul M Alam , Luke P. J. Fitzpatrick

Reynolds-averaged Navier-Stokes (RANS) is one of the most cost-efficient approaches to simulate wind-farm-atmosphere interactions. However, the applicability of RANS-based methods is always limited by the accuracy of turbulence closure…

Fluid Dynamics · Physics 2021-12-08 Ali Eidi , Reza Ghiassi , Xiang Yang , Mahdi Abkar

A previously developed modeling procedure for large eddy simulations (LESs) is extended to allow physical space implementations for inhomogeneous flows. The method is inspired by the well-established theoretical analyses and numerical…

Fluid Dynamics · Physics 2022-10-28 Guangrui Sun , J. Andrzej Domaradzki

With the continuing progress in large eddy simulations (LES), and ever increasing computational resources, it is currently possible to numerically solve the time-dependent and anisotropic large scales of turbulence in a large variety of…

Fluid Dynamics · Physics 2021-12-14 Ryan D. Hass , Aditya S. Ghate , Sanjiva K. Lele

Large eddy simulations (LES) are a powerful tool in understanding processes that are inaccessible by direct simulations due to their complexity, for example, in the highly turbulent regime. However, their accuracy and success depends on a…

Fluid Dynamics · Physics 2017-03-27 Philipp Grete , Dimitar G Vlaykov , Wolfram Schmidt , Dominik R G Schleicher

Climate change necessitates rapid expansion of renewable energy, with wind energy offering a scalable and low-impact solution. However, accurate prediction of wind loads and power generation remains challenging due to uncertainties in wind…

Fluid Dynamics · Physics 2026-04-30 Omar Sallam , Mirjam Fürth

Reynolds-averaged Navier-Stokes simulations are still the main method to study complex flows in engineering. However, traditional turbulence models cannot accurately predict flow fields with separations. In such situation, machine learning…

Fluid Dynamics · Physics 2022-02-02 Yilang Liu , Weiwei Zhang , Zhenhua Xia

Fluid turbulence is characterized by strong coupling across a broad range of scales. Furthermore, besides the usual local cascades, such coupling may extend to interactions that are non-local in scale-space. As such the computational…

A new method for the localization of the regions where small scale turbulent fluctuations are present in hypersonic flows is applied to the large-eddy simulation (LES) of a compressible turbulent jet with an initial Mach number equal to 5.…

Fluid Dynamics · Physics 2015-06-12 D. Tordella , M. Iovieno , S. Massaglia , A. Mignone

A numerical investigation of the flow evolution over a pitching NACA 0012 airfoil incurring in deep dynamic stall phenomena is presented. The experimental data at Reynolds number Re = 135 000 and reduced frequency k = 0.1, provided by Lee…

Fluid Dynamics · Physics 2026-02-09 Giacomo Baldan , Francesco Manara , Gregorio Frassoldati , Alberto Guardone

One of the greatest challenges to using large-eddy simulations (LES) in engineering applications is the large number of grid points required near walls. To mitigate this issue, researchers often couple LES with a simplified model of the…

Fluid Dynamics · Physics 2016-11-15 Alexandre Marques , Qiqi Wang , Johan Larsson , Gregory Laskowski , Sanjeeb Bose

The aim of this paper is to introduce a consistent velocity smoothing method for smoothed particle hydrodynamics (SPH). First the locally averaged Navier-Stokes equations are derived in a mathematically rigorous way to demonstrate the…

Fluid Dynamics · Physics 2018-07-31 Kalale Chola