Optimisation of temporal averaging processes in PIV
Optimisation of temporal averaging processes in PIV
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DOI：
10.1007/s00348-011-1080-8
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发表时间：
2012-03-01
影响因子：
2.4
通讯作者：
Fouras, Andreas
中科院分区：
文献类型：
--
作者：
Samarage, Chaminda R.;Carberry, Josie;Fouras, Andreas
引入了相关和矢量平均的混合，以充分利用每个过程的优点。进行了一系列广泛的蒙特卡罗模拟，以研究混合平均并对矢量平均和相关平均进行评估。仿真结果表明，在大范围成像条件下，混合平均比相关平均和矢量平均都提高了测量精度。通过对实验微流和宏流进行混合平均，验证了模拟结果。在脉动条件下，相关平均产生一个多模态的平均相关函数，这可能导致不可预测的测量结果。蒙特卡罗模拟表明，在这种情况下，混合平均优于相关平均。在Re = 98时，对脱落圆柱后的非定常尾迹进行了实验验证。
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.