Optimisation of temporal averaging processes in PIV |
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| Authors: | Chaminda R. Samarage Josie Carberry Kerry Hourigan Andreas Fouras |
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| Affiliation: | (1) Division of Biological Engineering, Department of Mechanical & Aerospace Engineering, Monash University, Melbourne, VIC, 3800, Australia;(2) Fluids Laboratory for Aeronautical and Industrial Research (FLAIR), Department of Mechanical & Aerospace Engineering, Monash University, Melbourne, VIC, 3800, Australia;(3) Division of Biological Engineering, Monash University, Melbourne, VIC, 3800, Australia;(4) Division of Biological Engineering, Fluids Laboratory for Aeronautical and Industrial Research (FLAIR), Department of Mechanical & Aerospace Engineering, Monash University, Melbourne, VIC, 3800, Australia;; |
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| Abstract: | A hybrid of correlation and vector averaging is introduced to capitalise on the advantages of each process. An extensive series of Monte Carlo simulations have been conducted to investigate hybrid averaging and evaluate it against both vector and correlation averaging. The simulations show that hybrid averaging improves the measurement accuracy over both correlation and vector averaging over a wide range of imaging conditions. The simulations are validated by applying hybrid averaging to experimental micro- and macro-flows. In pulsatile conditions, correlation averaging yields an averaged correlation function that is multi-modal, which can result in unpredictable measurements. A Monte Carlo simulation shows the benefits of hybrid averaging over correlation averaging in such conditions. This has been experimentally validated on the unsteady wake behind a shedding circular cylinder at Re = 98. |
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