Stereo-particle image velocimetry uncertainty quantification

被引:31
|
作者
Bhattacharya, Sayantan [1 ]
Charonko, John J. [2 ]
Vlachos, Pavlos P. [1 ]
机构
[1] Purdue Univ, Sch Mech Engn, W Lafayette, IN 47907 USA
[2] Los Alamos Natl Lab, Div Phys, Los Alamos, NM USA
基金
美国国家科学基金会;
关键词
particle image velocimetry; PIV; stereo-PIV; uncertainty; SPATIAL-RESOLUTION; SELF-CALIBRATION; WIND-TUNNEL; PIV; ACCURACY;
D O I
10.1088/1361-6501/28/1/015301
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Particle image velocimetry (PIV) measurements are subject to multiple elemental error sources and thus estimating overall measurement uncertainty is challenging. Recent advances have led to a posteriori uncertainty estimation methods for planar two-component PIV. However, no complete methodology exists for uncertainty quantification in stereo PIV. In the current work, a comprehensive framework is presented to quantify the uncertainty stemming from stereo registration error and combine it with the underlying planar velocity uncertainties. The disparity in particle locations of the dewarped images is used to estimate the positional uncertainty of the world coordinate system, which is then propagated to the uncertainty in the calibration mapping function coefficients. Next, the calibration uncertainty is combined with the planar uncertainty fields of the individual cameras through an uncertainty propagation equation and uncertainty estimates are obtained for all three velocity components. The methodology was tested with synthetic stereo PIV data for different light sheet thicknesses, with and without registration error, and also validated with an experimental vortex ring case from 2014 PIV challenge. Thorough sensitivity analysis was performed to assess the relative impact of the various parameters to the overall uncertainty. The results suggest that in absence of any disparity, the stereo PIV uncertainty prediction method is more sensitive to the planar uncertainty estimates than to the angle uncertainty, although the latter is not negligible for non-zero disparity. Overall the presented uncertainty quantification framework showed excellent agreement between the error and uncertainty RMS values for both the synthetic and the experimental data and demonstrated reliable uncertainty prediction coverage. This stereo PIV uncertainty quantification framework provides the first comprehensive treatment on the subject and potentially lays foundations applicable to volumetric PIV measurements.
引用
收藏
页数:17
相关论文
共 50 条
  • [1] Uncertainty quantification in particle image velocimetry
    Christensen, K. T.
    Scarano, F.
    [J]. MEASUREMENT SCIENCE AND TECHNOLOGY, 2015, 26 (07)
  • [3] AUTOMATIC PARTICLE IMAGE VELOCIMETRY UNCERTAINTY QUANTIFICATION
    Timmins, Benjamin H.
    Smith, Barton L.
    Vlachos, Pavlos P.
    [J]. PROCEEDINGS OF THE ASME FLUIDS ENGINEERING DIVISION SUMMER CONFERENCE - 2010 - VOL 1, PTS A-C, 2010, : 2811 - 2826
  • [4] Brief review of uncertainty quantification for particle image velocimetry
    Farias, M. H.
    Teixeira, R. S.
    Koiller, J.
    Santos, A. M.
    [J]. 8TH BRAZILIAN CONGRESS ON METROLOGY (METROLOGIA 2015), 2016, 733
  • [5] Special issue on uncertainty quantification in particle image velocimetry and Lagrangian particle tracking
    Sciacchitano, Andrea
    Discetti, Stefano
    [J]. MEASUREMENT SCIENCE AND TECHNOLOGY, 2022, 33 (01)
  • [6] APPLICATION OF PARTICLE IMAGE VELOCIMETRY AND STEREO PARTICLE IMAGE VELOCIMETRY ON SOIL BIOLOGY
    Yuan, Bingxiang
    Chen, Rui
    Teng, Jun
    [J]. JOURNAL OF INVESTIGATIVE MEDICINE, 2014, 62 (08) : S101 - S101
  • [7] Stereo-Particle Image Velocimetry Measurements of a Patient-Specific Fontan Physiology Utilizing Novel Pressure Augmentation Stents
    Chopski, Steven G.
    Rangus, Owen M.
    Fox, Carson S.
    Moskowitz, William B.
    Throckmorton, Amy L.
    [J]. ARTIFICIAL ORGANS, 2015, 39 (03) : 228 - 236
  • [8] Particle image velocimetry analysis with simultaneous uncertainty quantification using Bayesian neural networks
    Morrell, Mia C.
    Hickmann, Kyle
    Wilson, Brandon M.
    [J]. MEASUREMENT SCIENCE AND TECHNOLOGY, 2021, 32 (10)
  • [9] Fundamentals of multiple plane stereo particle image velocimetry
    Kähler, CJ
    Kompenhans, J
    [J]. EXPERIMENTS IN FLUIDS, 2000, 29 (Suppl 1) : S70 - S77
  • [10] Particle image velocimetry (PIV) uncertainty quantification using moment of correlation (MC) plane
    Bhattacharya, Sayantan
    Charonko, John J.
    Vlachos, Pavios P.
    [J]. MEASUREMENT SCIENCE AND TECHNOLOGY, 2018, 29 (11)