Uncertainty Estimation for Ensemble Particle Image Velocimetry
نویسندگان
چکیده
We present a novel approach to estimate the uncertainty in ensemble particle image velocimetry (PIV) measurements. Ensemble PIV is widely used when cross-correlation signal-to-noise ratio (SNR) insufficient perform reliable instantaneous velocity measurement. Despite utility of PIV, quantification for this type measurement has not been studied. The existing algorithms are developed and only do account improved SNR PIV. Existing methods can be divided into direct indirect categories. Indirect require calibration based on effect various parameters (such as noise, size, density, gradient, etc.) correlation SNR. have calibrated error sources relevant an Also, they lower sensitivity compared approaches. Direct methods, such moment (MC) Image Matching (IM), find images planes without any more (Bhattacharya et al., 2018; Sciacchitano 2013). correlations; therefore, MC, which uses generalized (GCC) plane measure uncertainty, most suitable method modified applicable GCC inverse Fourier transform phase represents probability density function (PDF) particles’ displacements Eckstein Vlachos, 2009). replaced with MC’s normalization factor number ensembles. primary limitation that it assumes Gaussian shape PDF standard deviation underlying using fitted Gaussian. However, deviates from distribution due gradient or non-Gaussian random displacements. Therefore, reliability applicability reduced flow fields PDFs. our analysis shows MC consistently underestimates uncertainty. So, needed.
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ژورنال
عنوان ژورنال: International Symposium on Particle Image Velocimetry
سال: 2021
ISSN: ['2769-7576']
DOI: https://doi.org/10.18409/ispiv.v1i1.143