Access the full text.
Sign up today, get DeepDyve free for 14 days.
R. Adrian, B. Jones, M. Chung, Y. Hassan, C. Nithianandan, A. Tung (1989)
Approximation of turbulent conditional averages by stochastic estimationPhysics of Fluids, 1
R. Adrian (1996)
Stochastic Estimation of the Structure of Turbulent Fields
S. Pope (2000)
Turbulent FlowsMeasurement Science and Technology, 12
G. Spedding, E. Rignot (1993)
Performance analysis and application of grid interpolation techniques for fluid flowsExperiments in Fluids, 15
Juan Agüí, Javier Jiménez (1987)
On the performance of particle trackingJournal of Fluid Mechanics, 185
GK Batchelor (1960)
Homogeneous turbulence
J. Bonnet (1996)
Eddy structure identification
R. Adrian, C. Yao (1985)
Power spectra of fluid velocities measured by laser Doppler velocimetryExperiments in Fluids, 5
R. Rogallo (1981)
Numerical experiments in homogeneous turbulence, 81
(1986)
An interpolation scheme for randomly spaced sparse velocity data , unpublished note , Mech
(1991)
Vector field interpolation in fluid flow,
E. Müller, H. Nobach, C. Tropea (1998)
A refined reconstruction-based correlation estimator for two-channel, non-coincidence laser Doppler anemometryMeasurement Science and Technology, 9
R. Adrian (1975)
On the role of conditional averages in turbulence theory.No source information available
J. Proakis (1985)
Probability, random variables and stochastic processesIEEE Trans. Acoust. Speech Signal Process., 33
Ji Zhong, Thomas Huang, R. Adrian (1994)
Vector-valued multidimensional signal processing and analysis in the context of fluid flows
RJ Adrian (1977)
Turbulence in liquids.
Richard Keane, R. Adrian, Yuanhui Zhang (1995)
Super-resolution particle imaging velocimetryMeasurement Science and Technology, 6
J Agui, J Jimenez (1987)
On the performance of particle tracking velocimetryJ Fluid Mech, 185
L. Benedict, H. Nobach, C. Tropea (2000)
Estimation of turbulent velocity spectra from laser Doppler dataMeasurement Science and Technology, 11
A new approach for the interpolation of a filtered turbulence velocity field given random point samples of unfiltered turbulence velocity data is described. In this optimal interpolation method, the best possible value of the interpolated filtered field is obtained as a stochastic estimate of a conditional average, which minimizes the mean square error between the interpolated filtered velocity field and the true filtered velocity field. Besides its origins in approximation theory, the optimal interpolation method also has other advantages over more commonly used ad hoc interpolation methods (like the ‘adaptive Gaussian window’). The optimal estimate of the filtered velocity field can be guaranteed to preserve the solenoidal nature of the filtered velocity field and also the underlying correlation structure of both the filtered and the unfiltered velocity fields. The a posteriori performance of the optimal interpolation method is evaluated using data obtained from high-resolution direct numerical simulation of isotropic turbulence. Our results show that for a given sample data density, there exists an optimal choice of the characteristic width of cut-off filter that gives the least possible relative mean square error between the true filtered velocity and the interpolated filtered velocity. The width of this ‘optimal’ filter and the corresponding minimum relative error appear to decrease with increase in sample data density. Errors due to the optimal interpolation method are observed to be quite low for appropriate choices of the data density and the characteristic width of the filter. The optimal interpolation method is also seen to outperform the ‘adaptive Gaussian window’, in representing the interpolated field given the data at random sample locations. The overall a posteriori performance of the optimal interpolation method was found to be quite good and hence makes a potential candidate for use in interpolation of PTV and super-resolution PIV data.
Experiments in Fluids – Springer Journals
Published: Jul 19, 2005
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.