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Micro-PIV-Based Diffusometry

Micro-PIV-Based Diffusometry, Fig. 1 Comparison of (a) autocorrelation function, (b) cross-correlation function without any Brownian motion, and (c) cross-correlation function with Brownian motion... [Pg.2135]

Micro-PIV-Based Diffusometry, Fig. 2 Broadening of the correlation function due to a velocity gradient... [Pg.2137]

To obtain the velocity field with the PIV method (see also Micro-PIV-Based Diffusometry) two images with a short time interval At are applied. It is possible to use the same images for the estimation of the temperature and the velocity fields (see Fig. 6). Therefore intensity images are created of the RGB images, which are pre-processed as described above and divided into interrogation areas. The two-dimensional cross correlation of related interrogation areas leads to the pixel displacement in the measurement plane direction s, and with the length of a square pixel and time interval At the velocity vector can be calculated with the formula ... [Pg.1017]

Micro-PIV-Based Diffusometry, Figure 1 Comparison of (a) autocorrelatinn s... [Pg.1302]

Micro-PIV-Based Diffusometry, Rgure 3 Illustration of the effect of a velocity gradient on the cross-correlation function... [Pg.1303]

Micro-PIV-Based Diffusometry, Figure 4 Temperatures in a stationary fiuid deduced using the PIV based Thermometry (PIVT) method piotted against the temperatures measured with a thermocouple. The average difference between the predicted and measured temperatures was 2.1 °C... [Pg.1304]

See other pages where Micro-PIV-Based Diffusometry is mentioned: [Pg.1059]    [Pg.1213]    [Pg.1653]    [Pg.2133]    [Pg.2133]    [Pg.2134]    [Pg.2135]    [Pg.2136]    [Pg.2137]    [Pg.2138]    [Pg.2139]    [Pg.2186]    [Pg.2534]    [Pg.2846]    [Pg.3415]    [Pg.3473]    [Pg.148]    [Pg.736]    [Pg.1301]    [Pg.1302]    [Pg.1303]    [Pg.1304]    [Pg.1334]    [Pg.1557]    [Pg.1723]    [Pg.2125]    [Pg.2140]    [Pg.2176]   
See also in sourсe #XX -- [ Pg.1300 ]



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Diffusometry

Micro piv

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