Estimating global and local scaling exponents in turbulent flows using discrete wavelet transformations

2001 ◽  
Vol 13 (1) ◽  
pp. 241-250 ◽  
Author(s):  
Gabriel Katul ◽  
Brani Vidakovic ◽  
John Albertson
Author(s):  
Peter J. Forrester

The eigenvalue probability density function (PDF) for the Gaussian unitary ensemble has a well-known analogy with the Boltzmann factor for a classical log-gas with pair potential [Formula: see text], confined by a one-body harmonic potential. A generalization is to replace the pair potential by [Formula: see text]. The resulting PDF first appeared in the statistical physics literature in relation to non-intersecting Brownian walkers, equally spaced at time [Formula: see text], and subsequently in the study of quantum many-body systems of the Calogero–Sutherland type, and also in Chern–Simons field theory. It is an example of a determinantal point process with correlation kernel based on the Stieltjes–Wigert polynomials. We take up the problem of determining the moments of this ensemble, and find an exact expression in terms of a particular little [Formula: see text]-Jacobi polynomial. From their large [Formula: see text] form, the global density can be computed. Previous work has evaluated the edge scaling limit of the correlation kernel in terms of the Ramanujan ([Formula: see text]-Airy) function. We show how in a particular [Formula: see text] scaling limit, this reduces to the Airy kernel.


2016 ◽  
Vol 15 (1) ◽  
pp. 67
Author(s):  
M. L. S. Indrusiak ◽  
A. J. Kozakevicius ◽  
S. V. Möller

In this work, wavelet transforms are the analysis tools for studying transient and discontinuous phenomena associated to turbulent flows. The application in quest results from velocity measurements with hot wire anemometry in the transient wake considering a circular cylinder in an aerodynamic channel. Continuous and discrete wavelet transforms are applied and compared with the corresponding results given by the Fourier transform. For the continuous wavelet transform, the Morlet function was adopted as transform basis, and for the discrete case, the Daubechies orthonormal wavelet with 20 null moments. Results using the discrete wavelet packet transform are also presented and compared. A wake past a cylinder was analytically simulated and compared with the actual one, both in transient flow. The ability of the wavelet transforms in the analysis of unsteady phenomena and the potential of the wavelet approach as a complementary tool to the Fourier spectrum for the analysis of stationary phenomena is presented and discussed.


Fractals ◽  
1995 ◽  
Vol 03 (04) ◽  
pp. 879-891 ◽  
Author(s):  
M. SERNETZ ◽  
M. JUSTEN ◽  
F. JESTCZEMSKI

Three-dimensional data sets of kidney arterial vessels were obtained from resin casts by serial sectioning and by micro-NMR-tomography, and were analyzed by the mass-radius-relation both for global and local scaling properties. We present for the first time the spatial resolution of local scaling and thus the dispersion of the fractal dimension within the organs. The arterial system is characterized as a non-homogeneous fractal. We discuss and relate the fractal structure to the scaling and allometry of metabolic rates in living organisms.


Author(s):  
Martina Čampulová

Data smoothing is often required within the environmental data analysis. A number of methods and algorithms that can be applied for data smoothing have been proposed. This paper gives an overview and compares the performance of different smoothing procedures that estimate the trend in the data, based on the surrounding noisy observations that can be applied on environmental data. The considered methods include kernel regression with both global and local bandwidth, moving average, exponential smoothing, robust repeated median regression, trend filtering and approach based on discrete Fourier and discrete wavelet transform. The methods are applied to real data obtained by measurement of PM10concentrations and compared in a simulation study.


2019 ◽  
Vol 149 ◽  
pp. 154-172 ◽  
Author(s):  
Asad Arfeen ◽  
Krzysztof Pawlikowski ◽  
Don McNickle ◽  
Andreas Willig

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