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Deterministic closures for coarse-grained turbulence models help reproduce mean statistics, but often fail to capture the finite-time growth of uncertainty. Using the framework of shell models as a quantitative multi-scale testbed, we…

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

Site-specific flow and turbulence information are needed for various practical applications, ranging from aerodynamic/aeroelastic modeling for wind turbine design to optical diffraction calculations. Even though highly desirable, collecting…

Atmospheric and Oceanic Physics · Physics 2013-07-10 Yao Wang , Sukanta Basu , Lance Manuel

A dynamical model is proposed for isotropic turbulence driven by steady forcing that yields a viscosity independent dynamics for the small-scale (inertial) regime. This reproduces the Kolmogorov spectrum for the two-point velocity…

Statistical Mechanics · Physics 2011-07-04 Mohammad Mehrafarin

We live in an age in which high-performance computing is transforming the way we do science. Previously intractable problems are now becoming accessible by means of increasingly realistic numerical simulations. One of the most enduring and…

Turbulent dynamical systems characterized by both a high-dimensional phase space and a large number of instabilities are ubiquitous among many complex systems in science and engineering. The existence of a strange attractor in the turbulent…

Fluid Dynamics · Physics 2018-02-23 Andrew J. Majda , Di Qi

Lagrangian acceleration has been investigated both experimentally and numerically in the past, and it has been shown to exhibit extreme fluctuations, which have been rationalized as events in which tracer particles get trapped into vortical…

Fluid Dynamics · Physics 2025-07-24 Lorenzo Piro , Massimo Cencini , Roberto Benzi

The main objective of this work is to develop a unified framework that can be used as a lens to quantitatively assess and augment a wide range of coarse-grained models of turbulence, viz. large eddy simulations (LES), hybrid…

Fluid Dynamics · Physics 2023-01-25 Aniruddhe Pradhan , Karthik Duraisamy

In this paper, we discuss the incorporation of dynamic subgrid scale (SGS) models in the lattice-Boltzmann method (LBM) for large-eddy simulation (LES) of turbulent flows. The use of a dynamic procedure, which involves sampling or…

Computational Physics · Physics 2015-05-13 Kannan N. Premnath , Martin J. Pattison , Sanjoy Banerjee

Turbulence constitutes an exceptionally complex and irregular flow phenomenon that manifests in liquids, gases, and plasma, making it ubiquitous in both natural processes and engineering applications. Given the relatively modest…

Fluid Dynamics · Physics 2025-07-08 Ziqi Ji , Penghao Duan , Gang Du

Numerical and experimental turbulence simulations are nowadays reaching the size of the so-called big data, thus requiring refined investigative tools for appropriate statistical analyses and data mining. We present a new approach based on…

Fluid Dynamics · Physics 2017-01-05 Stefania Scarsoglio , Giovanni Iacobello , Luca Ridolfi

A hybrid RANS/LES framework is developed based on a recently proposed Improved Delayed Detached Eddy Simulation (IDDES) model combined with a variant of recycling and rescaling method of generating inflow turbulence. This framework was…

Fluid Dynamics · Physics 2014-08-06 Sunil K. Arolla

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

A recent Letter by Oberlack et al. [Phys. Rev. Lett. 128, 024502 (2022)] claims to have derived new symmetry-induced solutions of the non-modelled statistical Navier-Stokes equations of turbulent channel flow. A high accuracy match to DNS…

Fluid Dynamics · Physics 2023-02-13 Michael Frewer , George Khujadze

The development of a wall model using machine learning methods for the large-eddy simulation (LES) of separated flows is still an unsolved problem. Our approach is to leverage the significance of separated flow data, for which existing…

Fluid Dynamics · Physics 2024-12-25 Zhideng Zhou , Xin-lei Zhang , Guo-wei He , Xiaolei Yang

In nonlinear dynamical systems with highly nonorthogonal linear eigenvectors, linear non-modal analysis is more useful than normal mode analysis in predicting turbulent properties. However, the non-trivial time evolution of non-modal…

Plasma Physics · Physics 2015-06-22 Brett Friedman , Troy A. Carter

This paper puts forth two new closure models for the proper orthogonal decomposition reduced-order modeling of structurally dominated turbulent flows: the dynamic subgrid-scale model and the variational multiscale model. These models, which…

Computational Physics · Physics 2015-05-28 Zhu Wang , Imran Akhtar , Jeff Borggaard , Traian Iliescu

We study the statistical properties of stationary, isotropic and homogeneous turbulence in two-dimensional (2D) flows, focusing on the direct cascade, that is on wave-numbers large compared to the integral scale, where both energy and…

Statistical Mechanics · Physics 2024-08-29 Malo Tarpin , Léonie Canet , Carlo Pagani , Nicolás Wschebor

The closure problem of turbulence is still a challenging issue in turbulence modeling. In this work, a stability condition is used to close turbulence. Specifically, we regard single-phase flow as a mixture of turbulent and non-turbulent…

Fluid Dynamics · Physics 2014-06-20 Lin Zhang , Xiaoping Qiu , Limin Wang , Jinghai Li

In this work, a stochastic representation based on a physical transport principle is proposed to account for mesoscale eddy effects on the large-scale oceanic circulation. This stochastic framework arises from a decomposition of the…

Geophysics · Physics 2022-07-26 Long Li , Bruno Deremble , Noé Lahaye , Etienne Mémin
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