caa a22 4500 60619830X CHVBK 20210128100933.0 cr unu---uuuuu 210128e20150401xx s 000 0 eng 10.1007/s00348-015-1940-8 doi (NATIONALLICENCE)springer-10.1007/s00348-015-1940-8 On PIV random error minimization with optimal POD-based low-order reconstruction [Elektronische Daten] [Marco Raiola, Stefano Discetti, Andrea Ianiro] Random noise removal from particle image velocimetry (PIV) data and spectra is of paramount importance, especially for the computation of derivative quantities and spectra. Data filtering is critical, as a trade-off between filter effectiveness and spatial resolution penalty should be found. In this paper, a filtering method based on proper orthogonal decomposition and low-order reconstruction (LOR) is proposed. The existence of an optimal number of modes based on the minimization of both reconstruction error and signal withdrawal is demonstrated. A criterion to perform the choice of the optimal number of modes is proposed. The method is validated via synthetic and real experiments. As prototype problems, we consider PIV vector fields obtained from channel flow DNS data and from PIV measurement in the wake of a circular cylinder. We determine the optimal number of modes to be used for the LOR in order to minimize the statistical random error. The results highlight a significant reduction in the measurement error. Dynamic velocity range is enhanced, enabling to correctly capture spectral information of small turbulent scales down to the half of the cutoff wavelength of original data. In addition to this, the capability of detecting coherent structures is improved. The robustness of the method is proved, both for low signal-to-noise ratios and for small-sized ensembles. The proposed method can significantly improve the physical insight into the investigation of turbulent flows. Springer-Verlag Berlin Heidelberg, 2015 Raiola Marco Aerospace Engineering Group, Universidad Carlos III de Madrid, Avenida de la Universidad 30, 28911, Leganés, Spain aut Discetti Stefano Aerospace Engineering Group, Universidad Carlos III de Madrid, Avenida de la Universidad 30, 28911, Leganés, Spain aut Ianiro Andrea Aerospace Engineering Group, Universidad Carlos III de Madrid, Avenida de la Universidad 30, 28911, Leganés, Spain aut Experiments in Fluids Springer Berlin Heidelberg 56/4(2015-04-01), 1-15 0723-4864 56:4<1 2015 56 348 https://doi.org/10.1007/s00348-015-1940-8 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00348-015-1940-8 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Raiola Marco Aerospace Engineering Group, Universidad Carlos III de Madrid, Avenida de la Universidad 30, 28911, Leganés, Spain aut NATIONALLICENCE 700 1- Discetti Stefano Aerospace Engineering Group, Universidad Carlos III de Madrid, Avenida de la Universidad 30, 28911, Leganés, Spain aut NATIONALLICENCE 700 1- Ianiro Andrea Aerospace Engineering Group, Universidad Carlos III de Madrid, Avenida de la Universidad 30, 28911, Leganés, Spain aut NATIONALLICENCE 773 0- Experiments in Fluids Springer Berlin Heidelberg 56/4(2015-04-01), 1-15 0723-4864 56:4<1 2015 56 348