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Elastic turbulence has been found in computations of planar viscoelastic Taylor-Couette flow using the Oldroyd-B model, apparently generated by a linear instability (van Buel et al. Europhys. Lett., 124, 14001, 2018). We demonstrate that no…

Fluid Dynamics · Physics 2025-07-08 Miguel Beneitez , Soufiane Mrini , Rich R. Kerswell

A framework for deriving probabilistic data-driven closure models is proposed for coarse-grained numerical simulations of turbulence in statistically stationary state. The approach unites the ideal large-eddy simulation model and data…

Fluid Dynamics · Physics 2025-03-25 Sagy Ephrati

The 1-D Two-Fluid Model (TFM) promises a powerful and computationally cheap platform for simulating multi-fluid flow phenomena. However, runaway Kelvin-Helmholtz instabilities plagued previous approaches, necessitating aphysical…

Fluid Dynamics · Physics 2025-09-08 Alexander López-de-Bertodano , Alejandro Clausse

Turbulent flows posses broadband, power-law spectra in which multiscale interactions couple high-wavenumber fluctuations to large-scale dynamics. Although diffusion-based generative models offer a principled probabilistic forecasting…

Fluid Dynamics · Physics 2025-12-11 Anish Sambamurthy , Ashesh Chattopadhyay

Laminar-turbulent pattern formation is a distinctive feature of the intermittency regime in subcritical plane shear flows. By performing extensive numerical simulations of the plane channel flow, we show that the pattern emerges from a…

Fluid Dynamics · Physics 2022-12-16 Pavan V. Kashyap , Yohann Duguet , Olivier Dauchot

We present a concise, self-contained derivation of diffusion-based generative models. Starting from basic properties of Gaussian distributions (densities, quadratic expectations, re-parameterisation, products, and KL divergences), we…

Machine Learning · Computer Science 2025-11-18 Sepehr Maleki , Negar Pourmoazemi

Classical eddy viscosity models of turbulence add an eddy viscosity term based on the Kolmogorov-Prandtl parameterization by a turbulent length scale $l$ and a turbulent kinetic energy $k^{\prime }$. Approximations of the unknowns…

Numerical Analysis · Mathematics 2026-03-31 William Layton , Nanda Nechingal Raghunathan

We use laser-Doppler velocimetry (LDV) experiments and Reynolds-averaged Navier--Stokes (RANS) simulations to study the characteristic flow patterns downstream of a standardized clockwise swirl disturbance generator. After quantifying the…

Fluid Dynamics · Physics 2015-10-27 Diego del Olmo Díaz , Denis F. Hinz

In this paper, we apply a recently developed nonparametric modeling approach, the "diffusion forecast", to predict the time-evolution of Fourier modes of turbulent dynamical systems. While the diffusion forecasting method assumes the…

Chaotic Dynamics · Physics 2016-03-23 Tyrus Berry , John Harlim

An innovative \textit{deep learning} approach has been adopted to formulate the eddy-viscosity for large eddy simulation (LES) of wall-bounded turbulent flows. A deep neural network (DNN) is developed which learns to evaluate the…

Fluid Dynamics · Physics 2019-05-31 Anikesh Pal

We characterize statistical properties of the flow field in developed turbulence using concepts from stochastic thermodynamics. On the basis of data from a free air-jet experiment, we demonstrate how the dynamic fluctuations induced by…

Statistical Mechanics · Physics 2013-05-23 D. Nickelsen , A. Engel

We investigate turbulence generated by cosmological structure formation by means of large eddy simulations using adaptive mesh refinement. In contrast to the widely used implicit large eddy simulations, which resolve a limited range of…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-17 W. Schmidt , A. S. Almgren , H. Braun , J. F. Engels , J. C. Niemeyer , J. Schulz , R. R. Mekuria , A. J. Aspden , J. B. Bell

Reynolds-Averaged Navier-Stokes(RANS) method will still play a vital role in the following several decade in aerospace engineering. Although RANS models are widely used, empiricism and large discrepancies between models reduce the…

Fluid Dynamics · Physics 2018-07-05 Weiwei Zhang , Linyang Zhu , Yilang Liu , Jiaqing Kou

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

We prove an estimate of total (viscous plus modelled turbulent) energy dissipation in general eddy viscosity models for shear flows. For general eddy viscosity models, we show that the ratio of the near wall average viscosity to the…

Fluid Dynamics · Physics 2022-10-12 Kiera Kean , William Layton , Michael Schneier

Despite the increasing availability of high-performance computational resources, Reynolds-Averaged Navier-Stokes (RANS) simulations remain the workhorse for the analysis of turbulent flows in real-world applications. Linear eddy viscosity…

Fluid Dynamics · Physics 2023-11-27 Leon Riccius , Atul Agrawal , Phaedon-Stelios Koutsourelakis

In this paper, a posteriori error estimates of functional type for a stationary diffusion problem with nonsymmetric coefficients are derived. The estimate is guaranteed and does not depend on any particular numerical method. An algorithm…

Numerical Analysis · Mathematics 2014-11-24 Olli Mali

We investigate eddy-viscosity distributions in pressure-driven wall turbulence for three canonical configurations: plane closed-channel flow, open-channel flow with a free-slip surface, and pipe flow. Using direct numerical simulation (DNS)…

Fluid Dynamics · Physics 2026-04-13 Ben-Rui Xu , Ao Xu

This article presents an original methodology for the prediction of steady turbulent aerodynamic fields. Due to the important computational cost of high-fidelity aerodynamic simulations, a surrogate model is employed to cope with the…

Fluid Dynamics · Physics 2019-12-05 Romain Dupuis , Jean-Christophe Jouhaud , Pierre Sagaut

In this paper, we propose a variational approach to estimate eddy viscosity using forward sensitivity method (FSM) for closure modeling in nonlinear reduced order models. FSM is a data assimilation technique that blends model's predictions…

Dynamical Systems · Mathematics 2020-11-05 Shady E. Ahmed , Kinjal Bhar , Omer San , Adil Rasheed