Skewness factor of turbulent velocity derivative

1994 ◽  
Vol 10 (1) ◽  
pp. 12-15 ◽  
Author(s):  
Qian Jian
1976 ◽  
Vol 77 (1) ◽  
pp. 45-62 ◽  
Author(s):  
K. S. Lii ◽  
M. Rosenblatt ◽  
C. Van Atta

A bispectral analysis of high Reynolds number turbulent velocity-derivative data is carried out. The computations suggest that contributions of wavenumber triplets to the rate of vorticity production and spectral transfer are non-local in wavenumber space and comparable over the whole range of wavenumbers studied. Statistical resolvability of the bispectral estimates is obtained. An appendix on the asymptotic behaviour of bispectral estimates is given.


2012 ◽  
Vol 47 (4) ◽  
pp. 851-872 ◽  
Author(s):  
Geoffrey C. Friesen ◽  
Yi Zhang ◽  
Thomas S. Zorn

AbstractThis study tests whether belief differences affect the cross-sectional variation of risk-neutral skewness using data on firm-level stock options traded on the Chicago Board Options Exchange from 2003 to 2006. We find that stocks with greater belief differences have more negative skews, even after controlling for systematic risk and other firm-level variables known to affect skewness. Factor analysis identifies latent variables linked to risk and belief differences. The belief factor explains more variation in the risk-neutral skewness than the risk-based factor. Our results suggest that belief differences may be one of the unexplained firm-specific components affecting skewness.


2002 ◽  
Vol 4 (1) ◽  
pp. 39-51
Author(s):  
Helen Kettle ◽  
Keith Beven ◽  
Barry Hankin

A method has been developed to estimate turbulent dispersion based on fuzzy rules that use local transverse velocity shears to predict turbulent velocity fluctuations. Turbulence measurements of flow around a rectangular dead zone in an open channel laboratory flume were conducted using an acoustic Doppler velocimeter (ADV) probe. The mean velocity and turbulence characteristics in and around the shear zone were analysed for different flows and geometries. Relationships between the mean transverse velocity shear and the turbulent velocity fluctuations are encapsulated in a simple set of fuzzy rules. The rules are included in a steady-state hybrid finite-volume advection–diffusion scheme to simulate the mixing of hot water in an open-channel dead zone. The fuzzy rules produce a fuzzy number for the magnitude of the average velocity fluctuation at each cell boundary. These are then combined within the finite-volume model using the single-value simulation method to give a fuzzy number for the temperature in each cell. The results are compared with laboratory flume data and a computational fluid dynamics (CFD) simulation from PHOENICS. The fuzzy model compares favourably with the experiment data and offers an alternative to traditional CFD models.


1973 ◽  
Vol 59 (3) ◽  
pp. 537-559 ◽  
Author(s):  
C. W. Van Atta ◽  
T. T. Yeh

Some of the statistical characteristics of the breakdown coefficient, defined as the ratio of averages over different spatial regions of positive variables characterizing the fine structure and internal intermittency in high Reynolds number turbulence, have been investigated using experimental data for the streamwise velocity derivative ∂u/∂tmeasured in an atmospheric boundary layer. The assumptions and predictions of the hypothesis of scale similarity developed by Novikov and by Gurvich & Yaglom do not adequately describe or predict the statistical characteristics of the breakdown coefficientqr,lof the square of the streamwise velocity derivative. Systematic variations in the measured probability densities and consistent variations in the measured moments show that the assumption that the probability density of the breakdown coefficient is a function only of the scale ratio is not satisfied. The small positive correlation between adjoint values ofqr,land measurements of higher moments indicate that the assumption that the probability densities for adjoint values ofqr,lare statistically independent is also not satisfied. The moments ofqr,ldo not have the simple power-law character that is a consequence of scale similarity.As the scale ratiol/rchanges, the probability density ofqr,levolves from a sharply peaked, highly negatively skewed density for large values of the scale ratio to a very symmetrical distribution when the scale ratio is equal to two, and then to a highly positively skewed density as the scale ratio approaches one. There is a considerable effect of heterogeneity on the values of the higher moments, and a small but measurable effect on the mean value. The moments are roughly symmetrical functions of the displacement of the shorter segment from the centre of the larger one, with a minimum value when the shorter segment is centrally located within the larger one.


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