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The pseudospectral method, in conjunction with a new technique for obtaining scaling exponents $\zeta_n$ from the structure functions $S_n(r)$, is presented as an alternative to the extended self-similarity (ESS) method and the use of…

流体动力学 · 物理学 2014-11-25 W. D. McComb , S. R. Yoffe , M. F. Linkmann , A. Berera

From Navier-Stokes turbulence numerical simulations we show that for the extended self similarity (ESS) method it is essential to take the third order structure function taken with the modulus and called $D_3^*(r)$, rather than the standard…

chao-dyn · 物理学 2009-10-30 Siegfried Grossmann , Detlef Lohse , Achim Reeh

In turbulent flows the $n$'th order structure functions $S_n(R)$ scale like $R^{\zeta_n}$ when $R$ is in the "inertial range". Extended Self-Similarity refers to the substantial increase in the range of power law behaviour of $S_n(R)$ when…

chao-dyn · 物理学 2009-10-28 Daniel Segel , Victor L'vov , Itamar Procaccia

In order to reliably compute the longitudinal structure functions in decaying and forced turbulence, local isotropy is examined with the aid of the isotropic expression of the incompressible conditions for the second and third order…

Extended Self-Similarity (ESS), a procedure that remarkably extends the range of scaling for structure functions in Navier--Stokes turbulence and thus allows improved determination of intermittency exponents, has never been fully explained.…

混沌动力学 · 物理学 2010-04-29 Sagar Chakraborty , Uriel Frisch , Samriddhi Sankar Ray

We compare the predictions of stochastic closure theory (SCT) with experimental measurements of homogeneous turbulence made in the Variable Density Turbulence Tunnel (VDTT) at the Max Planck Institute for Dynamics and Self-Organization in…

流体动力学 · 物理学 2018-10-19 John Kaminsky , Gregory P. Bewley , Michael Sinhuber , Bjorn Birnir

We propose and verify a wave-vector-space version of generalized extended self similarity and broaden its applicability to uncover intriguing, universal scaling in the far dissipation range by computing high-order ($\leq 20\/$) structure…

chao-dyn · 物理学 2009-10-28 Sujan K. Dhar , Anirban Sain , Rahul Pandit

Traditionally, trends of universal turbulence statistics are presented versus R-lambda, which is the Reynolds number based on Taylor's scale, lambda, and the root-mean-squared (rms) velocity component, u'. Taylor's scale and u', and hence…

流体动力学 · 物理学 2009-11-07 Reginald J. Hill

A recent discovery about the inertial range of homogeneous and isotropic turbulence is the saturation of the scaling exponents $\zeta_n$ for large $n$, defined via structure functions of order $n$ as $S_{n}(r)=\overline{(\delta_r…

流体动力学 · 物理学 2022-08-23 Katepalli R. Sreenivasan , Victor Yakhot

A parallel pseudospectral code for the direct numerical simulation (DNS) of isotropic turbulence has been developed. The code has been extensively benchmarked using established results from literature. The code has been used to conduct a…

流体动力学 · 物理学 2013-06-17 Samuel R. Yoffe

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…

流体动力学 · 物理学 2025-12-09 Chang Hsin Chen , Arnab Moitro , Alexei Y. Poludnenko

For a single timestep, a spectral solver is known to be more accurate than its finite-difference counterpart. However, as we show in this paper, turbulence simulations using the two methods have nearly the same accuracy. In this paper, we…

流体动力学 · 物理学 2025-08-15 Akash Rodhiya , Shashwat Bhattacharya , Mahendra K Verma

Stochastic Structural Stability Theory (S3T) provides analytical methods for understanding the emergence and equilibration of jets from the turbulence in planetary atmospheres based on the dynamics of the statistical mean state of the…

流体动力学 · 物理学 2015-03-20 Navid C. Constantinou , Brian F. Farrell , Petros J. Ioannou

The scaling of the longitudinal velocity structure functions, $S_q(r) = < | \delta u (r) |^q > \sim r^{\zeta_q}$, is analyzed up to order $q=8$ in a decaying rotating turbulence experiment from a large Particle Image Velocimetry (PIV)…

流体动力学 · 物理学 2009-11-13 J. Seiwert , C. Morize , F. Moisy

New scalar structure functions with different sign-symmetry properties are defined. These structure functions possess different scaling exponents even when their order is the same. Their scaling properties are investigated for second and…

混沌动力学 · 物理学 2009-11-10 Konstantinos G. Aivalis , Susan Kurien , Joerg Schumacher , Katepalli R. Sreenivasan

We report on recent progress in understanding the tubular phase of self-avoiding anisotropic membranes. After an introduction to the problem, we sketch the renormalization group arguments and symmetry considerations that lead us to the most…

高能物理 - 格点 · 物理学 2009-10-31 M. Bowick , A. Travesset

Self-similarity of wall-attached coherent structures in a turbulent channel at $Re_\tau=543$ is explored by means of resolvent analysis. In this modelling framework, coherent structures are understood to arise as a response of the…

流体动力学 · 物理学 2022-04-04 U. Karban , E. Martini , A. V. G. Cavalieri , L. Lesshafft , P. Jordan

We generalize the `filtering spectrum' [1] to probe scales along different directions by spatial coarse-graining. This multi-dimensional filtering spectrum quantifies the spectral content of flows that are not necessarily homogeneous. From…

流体动力学 · 物理学 2023-10-20 Dongxiao Zhao , Hussein Aluie

We revisit the relation between the variance of three-dimensional (3D) density ($\sigma^{2}_{\rho}$) and that of the projected two-dimensional (2D) column density ($\sigma^{2}_{\Sigma}$) in turbulent media, which is of great importance in…

星系天体物理 · 物理学 2024-06-26 Heesun Yoon , Jungyeon Cho

This study presents a novel approach for enhancing Reynolds-averaged Navier-Stokes (RANS) turbulence modeling through the application of a Relative Importance Term Analysis (RITA) methodology to develop a new zonally-augmented $k-\omega$…

流体动力学 · 物理学 2025-11-26 Tyler Buchanan , Monica Lăcătuş , Alastair West , Richard P. Dwight
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