PIV Accuracy Analysis
There are many factors that influence the measurement error when determining velocity using Particle Image Velocimetry (PIV). Careful selection of suitable particles/droplets ensures that their movement corresponds to that of the fluid under investigation. The imaging of the particles in the measuring plane on the camera sensor is subject to the highest demands on optics and sensor, since the particle size is often below the resolution and the scattered light is very low. The evaluation of PIV images also requires complex methods to minimize the measurement error, e. g. due to velocity gradients.
An analysis of synthetic PIV images makes it possible to systematically determine the influence of individual parameters such as particle image size, particle image density, image noise, gradients, etc... On the one hand, this makes it possible to estimate the measurement uncertainty and on the other hand, knowledge of the effect of the various parameters enables an optimization of the PIV measurement setup. For example, an optimal working distance of the camera, an optimum time difference between two exposures or an optimal laser beam profile can be theoretically determined.
An analysis of synthetic PIV images makes it possible to systematically determine the influence of individual parameters such as particle image size, particle image density, image noise, gradients, etc... On the one hand, this makes it possible to estimate the measurement uncertainty and on the other hand, knowledge of the effect of the various parameters enables an optimization of the PIV measurement setup. For example, an optimal working distance of the camera, an optimum time difference between two exposures or an optimal laser beam profile can be theoretically determined.
Person in charge:
Publications:
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Scharnowski S, Grayson K, de Silva CM, Hutchins N, Marusic I, Kähler CJ (2017) Generalization of the PIV loss-of-correlation formula introduced by Keane and Adrian. Experiments in Fluids 58:150
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Scharnowski S, Kähler CJ (2016) On the loss-of-correlation due to PIV image noise. Experiments in Fluids 57:119
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Scharnowski S, Kähler CJ (2016) Estimation and optimization of loss-of-pair uncertainties based on PIV correlation functions. Experiments in Fluids 57:23
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Scharnowski S, Kähler CJ (2013) On the effect of curved streamlines on the accuracy of PIV vector fields. Experiments in Fluids 54:1435
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Cierpka C, Scharnowski S, Kähler CJ (2013) Parallax correction for precise near-wall flow investigations using particle imaging. Applied Optics 52:2923-2931
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Kähler CJ, Scharnowski S, Cierpka C (2012) On the uncertainty of digital PIV and PTV near walls. Experiments in Fluids 52:1641-1656
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Kähler CJ, Scharnowski S, Cierpka C (2012) On the resolution limit of digital particle image velocimetry. Experiments in Fluids 52:1629-1639