Access the full text.
Sign up today, get DeepDyve free for 14 days.
S. Ghaemi, F. Scarano (2011)
Counter-hairpin vortices in the turbulent wake of a sharp trailing edgeJournal of Fluid Mechanics, 689
T. Astarita (2007)
Analysis of weighting windows for image deformation methods in PIVExperiments in Fluids, 43
F. Scarano (2002)
Iterative image deformation methods in PIVMeasurement Science and Technology, 13
A. Fincham, G. Delerce (2000)
Advanced optimization of correlation imaging velocimetry algorithmsExperiments in Fluids, 29
RD Keane, RJ Adrian (1992)
Theory of cross-correlation analysis of PIV imagesAppl Sci Res, 49
P. Burt, E. Adelson (1983)
The Laplacian Pyramid as a Compact Image CodeIEEE Trans. Commun., 31
A. Boillot, A. Prasad (1996)
Optimization procedure for pulse separation in cross-correlation PIVExperiments in Fluids, 21
T. Persoons, D. Murray (2008)
Improving the measurement accuracy of PIV in a synthetic jet flow
(2006)
Instantaneous pressure and material derivative measurements using a four exposure PIV system
J. Nogueira, A. Lecuona, S. Nauri, M. Legrand, P. Rodríguez (2009)
Multiple Δt strategy for particle image velocimetry (PIV) error correction, applied to a hot propulsive jetMeasurement Science and Technology, 20
T. Astarita, G. Cardone (2005)
Analysis of interpolation schemes for image deformation methods in PIVExperiments in Fluids, 38
Richard Keane, R. Adrian (1990)
Optimization of particle image velocimeters. I, Double pulsed systemsMeasurement Science and Technology, 1
GK Batchelor (1964)
Axial flow in trailing line vorticesJ Fluid Mech, 20
Richard Keane, R. Adrian (1992)
Theory of cross-correlation analysis of PIV imagesFlow Turbulence and Combustion, 49
M. Legrand, J. Nogueira, R. Ventas, A. Lecuona (2012)
Simultaneous assessment of peak-locking and CCD readout errors through a multiple Δt strategyExperiments in Fluids, 53
R. Adrian (1991)
Particle-Imaging Techniques for Experimental Fluid MechanicsAnnual Review of Fluid Mechanics, 23
R. Adrian, D. Durão, F. Durst, M. Maeda, J. Whitelaw (1991)
Applications of Laser Techniques to Fluid Mechanics
(2006)
Wall-shear-stress and nearwall turbulence measurements up to single pixel resolution by means of long distance PIV
R. Hain, C. Kähler, C. Tropea (2007)
Comparison of CCD, CMOS and intensified camerasExperiments in Fluids, 42
M. Raffel (2002)
Particle Image Velocimetry: A Practical Guide
(2010)
Lagrangian and Eulerian pressure field evaluation of rod-airfoil flow from tomographic PIV
C. Haigermoser (2009)
Application of an acoustic analogy to PIV data from rectangular cavity flowsExperiments in Fluids, 47
H. Huang, D. Dabiri, M. Gharib (1997)
On errors of digital particle image velocimetryMeasurement Science and Technology, 8
F. Schrijer, F. Scarano (2008)
Effect of predictor–corrector filtering on the stability and spatial resolution of iterative PIV interrogationExperiments in Fluids, 45
E. Overmars, N. Warncke, C. Poelma, J. Westerweel (2010)
Bias errors in PIV : the pixel locking effect revisited
(1997)
Low-cost, high resolution DPIV for measurement in turbulent fluid flows
D. Violato, F. Scarano (2011)
Three-dimensional evolution of flow structures in transitional circular and chevron jetsKnowledge, Technology & Policy
F. Scarano, Kristof Bryon, D. Violato (2010)
Time-resolved analysis of circular and chevron jets transition by tomo-PIV
M. Stanislas, K. Okamoto, C. Kähler, J. Westerweel, F. Scarano (2008)
Main results of the third international PIV ChallengeExperiments in Fluids, 45
R. Hain, C. Kähler (2007)
Fundamentals of multiframe particle image velocimetry (PIV)Experiments in Fluids, 42
M. Uberoi, B. Shivamoggi, S. Chen (1979)
Axial flow in trailing line vorticesPhysics of Fluids, 22
J. Westerweel, P. Geelhoed, R. Lindken (2004)
Single-pixel resolution ensemble correlation for micro-PIV applicationsExperiments in Fluids, 37
G. Bonmassar, E. Schwartz (1998)
Improved cross-correlation for template matching on the Laplacian pyramidPattern Recognit. Lett., 19
(2010)
Generalized estimation for averages of non-stationary flows
C. Meinhart, S. Wereley, J. Santiago (2000)
A PIV Algorithm for Estimating Time-Averaged Velocity FieldsJournal of Fluids Engineering-transactions of The Asme, 122
D Violato, F Scarano (2011)
Three-dimensional evolution of flow structures in transitional circular and chevrons jetsPhys Fluids, 23
J. Westerweel (1997)
Fundamentals of digital particle image velocimetryMeasurement Science and Technology, 8
(2006)
Development of higher-order analysis for multi-frame time-resolved PIV
A. Prasad (2000)
Particle image velocimetry
J. Charonko, Cameron King, Barton Smith, P. Vlachos (2010)
Assessment of pressure field calculations from particle image velocimetry measurementsMeasurement Science and Technology, 21
F. Scarano, M. Riethmuller (2000)
Advances in iterative multigrid PIV image processingExperiments in Fluids, 29
S. Morris (2011)
Shear-Layer Instabilities: Particle Image Velocimetry Measurements and Implications for AcousticsAnnual Review of Fluid Mechanics, 43
F. Scarano, P. Moore (2011)
An advection-based model to increase the temporal resolution of PIV time seriesExperiments in Fluids, 52
F. Pereira, A. Ciarravano, G. Romano, F. Felice (2004)
ADAPTIVE MULTI-FRAME PIV
A novel technique is introduced to increase the precision and robustness of time-resolved particle image velocimetry (TR-PIV) measurements. The innovative element of the technique is the linear combination of the correlation signal computed at different separation time intervals. The domain of the correlation signal resulting from different temporal separations is matched via homothetic transformation prior to the averaging of the correlation maps. The resulting ensemble-averaged correlation function features a significantly higher signal-to-noise ratio and a more precise velocity estimation due to the evaluation of a larger particle image displacement. The method relies on a local optimization of the observation time between snapshots taking into account the local out-of-plane motion, continuum deformation due to in-plane velocity gradient and acceleration errors. The performance of the pyramid correlation algorithm is assessed on a synthetically generated image sequence reproducing a three-dimensional Batchelor vortex; experiments conducted in air and water flows are used to assess the performance on time-resolved PIV image sequences. The numerical assessment demonstrates the effectiveness of the pyramid correlation technique in reducing both random and bias errors by a factor 3 and one order of magnitude, respectively. The experimental assessment yields a significant increase of signal strength indicating enhanced measurement robustness. Moreover, the amplitude of noisy fluctuations is considerably attenuated and higher precision is obtained for the evaluation of time-resolved velocity and acceleration.
Experiments in Fluids – Springer Journals
Published: Jul 15, 2012
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.