Scaling of space–time modes with Reynolds number in two-dimensional turbulence

Kevlahan, Nicholas; Alam, Jahrul M; Vasilyev, Oleg V.

doi:10.1017/s0022112006003168

Cited by 33 publications

(27 citation statements)

References 21 publications

(28 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In principle, a very low but non-zero value for this parameter can be prescribed so that the effect of unresolved motions can be completely ignored and the wavelet-based direct numerical solution of the penalized equation (2.5) is carried out, whereũ i ∼ =ũ > i . Even though the number of degrees-of-freedom of the WDNS is strongly reduced compared to non-adaptive DNS and the Reynolds number scaling is improved compared with conventional estimates (Kevlahan, Alam & Vasilyev 2007;Nejadmalayeri, Vezolainen & Vasilyev 2013), the computational cost still remains very high even at moderately large Reynolds number, thus, necessitating the use of turbulence modelling approaches.…”

Section: The Adaptive Wavelet Collocation Methodsmentioning

confidence: 99%

Wavelet-based adaptive simulations of three-dimensional flow past a square cylinder

Stefano¹,

Vasilyev

2014

J. Fluid Mech.

View full text Add to dashboard Cite

The wavelet-based eddy capturing approach is extended to three-dimensional bluff body flows, where the flow geometry is enforced through Brinkman volume penalization. The wavelet-collocation/volume-penalization combined method is applied to the simulation of vortex shedding flow behind an isolated stationary prism with square cross-section. Wavelet-based direct numerical simulation is conducted at low supercritical Reynolds number, where the wake develops fundamental three-dimensional flow structures, while wavelet-based adaptive large-eddy simulation supplied with the one-equation localized dynamic kinetic-energy-based model is performed at moderately high Reynolds number. The present results are in general agreement with experimental findings and numerical solutions provided by classical non-adaptive methods. This study demonstrates that the proposed hybrid methodology for modelling bluff body flows is feasible, accurate and efficient.

show abstract

Section: The Adaptive Wavelet Collocation Methodsmentioning

confidence: 99%

Wavelet-based adaptive simulations of three-dimensional flow past a square cylinder

Stefano¹,

Vasilyev

2014

J. Fluid Mech.

View full text Add to dashboard Cite

show abstract

“…The value of C(R λ , ...) is experimentally given by the computation of ζ(3) but also receives quantitative expression for specific cases of turbulent flows [22] which are derived from a finer approximation (which includes finite Reynolds number effects) of the Kármán-Howarth equation (report as well to [47][48][49][50][51] which are recent works about the discrepancy between experimental the third order structure function and the four fifths law; see as well [52]). Additional considerations on this topic will be discussed in a forthcoming article.…”

Section: Multifractality and Universalitymentioning

confidence: 99%

Comprehensive multifractal analysis of turbulent velocity using the wavelet leaders

et al. 2008

View full text Add to dashboard Cite

Abstract. The multifractal framework relates the scaling properties of turbulence to its local regularity properties through a statistical description as a collection of local singularities. The multifractal properties are moreover linked to the multiplicative cascade process that creates the peculiar properties of turbulence such as intermittency. A comprehensive estimation of the multifractal properties of turbulence from data analysis, using a tool valid for all kind of singularities (including oscillating singularities) and mathematically well-founded, is thus of first importance in order to extract a reliable information on the underlying physical processes. The wavelet leaders yield a new multifractal formalism which meets all these requests. This paper aims at describing it and at applying it to experimental turbulent velocity data. After a detailed discussion of the practical use of the wavelet leader based multifractal formalism, the following questions are carefully investigated: (1) What is the dependence of multifractal properties on the Reynolds number? (2) Are oscillating singularities present in turbulent velocity data? (3) Which multifractal model does correctly account for the observed multifractal properties? Results from several data set analysis are used to discuss the dependence of the computed multifractal properties on the Reynolds number but also to assess their common or universal component. An exact though partial answer (no oscillating singularities are detected) to the issue of the presence of oscillating singularities is provided for the first time. Eventually an accurate parameterization with cumulants exponents up to order 4 confirms that the log-normal model (with c2 = −0.025±0.002) correctly accounts for the universal multifractal properties of turbulent velocity.

show abstract

“…The method has already been successfully applied in wide range of fluid mechanics problems, e.g., that of Vasilyev et al (1997), Vasilyev and Kevlahan (2002), Kevlahan et al (2007), Reckinger et al (2010), and Schneider and Vasilyev (2010). In this section, the methodology is briefly reviewed.…”

Section: Adaptive Wavelet Collocation Methodsmentioning

confidence: 99%

Adaptive volume penalization for ocean modeling

2012

View full text Add to dashboard Cite

The development of various volume penalization techniques for use in modeling topographical features in the ocean is the focus of this paper. Due to the complicated geometry inherent in ocean boundaries, the stair-step representation used in the majority of current global ocean circulation models causes accuracy and numerical stability problems. Brinkman penalization is the basis for the methods developed here and is a numerical technique used to enforce no-slip boundary conditions through the addition of a term to the governing equations. The second aspect to this proposed approach is that all governing equations are solved on a nonuniform, adaptive grid through the use of the adaptive wavelet collocation method. This method solves the governing equations on temporally and spatially varying meshes, which allows higher effective resolution to be obtained with less computational cost. When penalization methods are coupled with the adaptive wavelet collocation method, the flow near the boundary can be well-resolved. It is especially useful for simulations of boundary currents and tsunamis, where flow near the boundary is important. This paper will give a thorough analysis of these methods applied to the shallow water equations, as well as some preliminary work applying these methods to volume penalization for bathymetry representation for use in either the nonhydrostatic or hydrostatic primitive equations.

show abstract

Scaling of space–time modes with Reynolds number in two-dimensional turbulence

Cited by 33 publications

References 21 publications

Wavelet-based adaptive simulations of three-dimensional flow past a square cylinder

Wavelet-based adaptive simulations of three-dimensional flow past a square cylinder

Comprehensive multifractal analysis of turbulent velocity using the wavelet leaders

Adaptive volume penalization for ocean modeling

Contact Info

Product

Resources

About