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Standard eddy viscosity models, while robust, cannot represent backscatter and have severe difficulties with complex turbulence not at statistical equilibrium. This report gives a new derivation of eddy viscosity models from an equation for…

Numerical Analysis · Mathematics 2015-03-05 Nan Jiang , William Layton

Serrations are commonly employed to mitigate the turbulent boundary layer trailing-edge noise. However, significant discrepancies persist between model predictions and experimental observations. In this paper, we show that this results from…

Fluid Dynamics · Physics 2023-12-27 Haopeng Tian , Benshuai Lyu

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

This work presents a new approach for premixed turbulent combustion modeling based on convolutional neural networks (CNN). We first propose a framework to reformulate the problem of subgrid flame surface density estimation as a machine…

Fluid Dynamics · Physics 2019-08-02 C. J. Lapeyre , A. Misdariis , N. Cazard , D. Veynante , T. Poinsot

Response modes computed via linear resolvent analysis of a turbulent mean-flow field have been shown to qualitatively capture characteristics of the observed turbulent coherent structures in both wall-bounded and free shear flows. To make…

Fluid Dynamics · Physics 2021-05-12 Ethan Pickering , Georgios Rigas , Oliver T. Schmidt , Denis Sipp , Tim Colonius

Deep learning provides a versatile suite of methods for extracting structured information from complex datasets, enabling deeper understanding of underlying fluid dynamic phenomena. The field of turbulence modeling, in particular, benefits…

Machine Learning · Computer Science 2025-07-31 Anuraj Maurya

A three-dimensional flamelet model considering vortex stretching with unitary Lewis number is used to simulate diluted hydrogen-oxygen diffusion flames. Non-reacting nitrogen is used as the diluent gas in the fuel stream. Unitary Lewis…

Fluid Dynamics · Physics 2024-10-08 Wes Hellwig , Xian Shi , William A. Sirignano

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

Two models based on convolutional neural networks are trained to predict the two-dimensional velocity-fluctuation fields at different wall-normal locations in a turbulent open channel flow, using the wall-shear-stress components and the…

Fluid Dynamics · Physics 2020-06-23 L. Guastoni , A. Güemes , A. Ianiro , S. Discetti , P. Schlatter , H. Azizpour , R. Vinuesa

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 neutral fluids by means of…

Cosmology and Nongalactic Astrophysics · Physics 2014-04-10 Wolfram Schmidt

Distributed lag models (DLMs) express the cumulative and delayed dependence between pairs of time-indexed response and explanatory variables. In practical application, users of DLMs examine the estimated influence of a series of lagged…

Applications · Statistics 2018-01-23 Alastair Rushworth

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…

Fluid Dynamics · Physics 2019-03-06 Arvind Mohan , Don Daniel , Michael Chertkov , Daniel Livescu

By analogy with the kinetic theory of gases, most turbulence modeling strate- gies rely on an eddy viscosity to model the unresolved turbulent fluctuations. How- ever, the ratio of unresolved to resolved scales - very much like a degree of…

Fluid Dynamics · Physics 2016-08-24 Marcello Righi

The performances of a new data processing technique, namely the Empirical Mode Decomposition, are evaluated on a fully developed turbulent velocity signal perturbed by a numerical forcing which mimics a long-period flapping. First, we…

Fluid Dynamics · Physics 2015-05-20 Nicolas Mazellier , Fabrice Foucher

Comparisons studies between simulated variable density turbulent flows often consist of direct graphical representations where the level of agreement is determined by eye. This work demonstrates a formal validation methodology using an…

Fluid Dynamics · Physics 2023-10-11 Austin Davis , Samuel Jones , John J. Charonko , Chris M. Malone , Katherine Prestridge

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

A stochastic EDQNM approach is used to investigate self-similar decaying isotropic turbulence at high Reynolds number ($400 \leq Re_\lambda \leq 10^4$). The realistic energy spectrum functional form recently proposed by Meyers & Meneveau is…

Fluid Dynamics · Physics 2013-09-25 Marcello Meldi , Pierre Sagaut , Didier Lucor

The variational multiscale (VMS) formulation is used to develop residual-based VMS large eddy simulation (LES) models for Rayleigh-B\'{e}nard convection. The resulting model is a mixed model that incorporates the VMS model and an eddy…

Computational Physics · Physics 2020-05-21 David Sondak , Thomas M. Smith , Roger P. Pawlowski , Sidafa Conde , John N. Shadid

Previous research on late-reverberation modeling has mainly focused on exponentially decaying room impulse responses, whereas methods for accurately modeling non-exponential reverberation remain challenging. This paper extends the…

Audio and Speech Processing · Electrical Eng. & Systems 2024-04-02 Jon Fagerström , Sebastian J. Schlecht , Vesa Välimäki

Some recent methods, like the Empirical Mode Decomposition (EMD), propose to decompose a signal accordingly to its contained information. Even though its adaptability seems useful for many applications, the main issue with this approach is…

Functional Analysis · Mathematics 2024-11-01 Jerome Gilles