Éditeur(s) : HAL CCSD Springer
Résumé : The analysis of gamma ray measurements provides valuable information about the basement's lithospherical model and the radioactive elements contained in the subsurface. To be exploited, the raw data need pre-processing operations which consist of corrections of the Compton effect, altimetry and the aircraft background, and 2D interpolations. These transformations may modify the data's stochastic component which reflects heterogeneities of the investigated medium. In this study, a fractal analysis is carried out on airborne gamma ray data measured in the Hoggar's area (Algeria). First, it is shown that the analyzed data exhibit fractal properties. Due to the dependence of the latter on the spatial location of the measures, the data can be considered as paths of multifractional Brownian motions. Another result worth noting is that the fractal nature of the raw data is not modified by the pre-processing operations. The fractal analysis can be then performed on the raw spectrometric measurements without submitting them to any pre-processing; thus, the stochastic component of the measurements is kept intact.
ISSN: 1866-7411

hal-00817494
https://hal.archives-ouvertes.fr/hal-00817494
DOI : 10.1007/s12517-011-0407-3

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
In this paper, we have presented a spectral and a multifractal analysis performed on 412 time series of wind speed data each of duration of 350 s and sampled at 20 Hz. The average spectrum for the wind speed displays a scaling behavior, in the inertial range, over two decades, with b ¼ 1:68 close to the Kolmogorov value À 5/3. A multifractal analysis has been motivated by the presence of scaling invariance in data set. Then we have considered their scaling properties in the framework of fully developed turbulence and multifractal cascades. The results obtained for wind speed confirm that the exponent scaling function z V ðqÞ is nonlinear and concave. This exponent characterizes the scaling functions in the inertial range indicating that the wind speed is intermittent and multifractal. Moreover the theoretical quadratic relation for lognormal multifractals is well fitted. We investigate the consequence for wind energy production: we generate stochastic simulations of a multifractal random walk, and using a power curve derived from experimental data, we generate the associated power time series. We show that, due to the saturation of the power curve for large speed values, when the input time series (turbulent wind speed) is multifractal, the output can be almost monofractal.
ISSN: 0167-6105

hal-01527886
https://hal.archives-ouvertes.fr/hal-01527886
DOI : 10.1016/j.jweia.2012.06.002