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Application of the optical flow method to velocity determination in hydraulic structure models
(2016)
Optical flow estimation is known from Computer Vision where it is used to determine obstacle movements through a sequence of images following an assumption of brightness conservation. This paper presents the first study on application of the optical flow method to aerated stepped spillway flows. For this purpose, the flow is captured with a high-speed camera and illuminated with a synchronized LED light source. The flow velocities, obtained using a basic Horn–Schunck method for estimation of the optical flow coupled with an image pyramid multi-resolution approach for image filtering, compare well with data from intrusive conductivity probe measurements. Application of the Horn–Schunck method yields densely populated flow field data sets with velocity information for every pixel. It is found that the image pyramid approach has the most significant effect on the accuracy compared to other image processing techniques. However, the final results show some dependency on the pixel intensity distribution, with better accuracy found for grey values between 100 and 150.
Abstractauthoren Graphene oxide (GO) nanoparticles were incorporated in temperature-sensitive Poly(N-isopropylacrylamide) (PNIPAAm) hydrogels. The nanoparticles increase the light absorption and convert light energy into heat efficiently. Thus, the hydrogels with GO can be stimulated spatially resolved by illumination as it was demonstrated by IR thermography. The temporal progression of the temperature maximum was detected for different concentrations of GO within the polymer network. Furthermore, the compatibility of PNIPAAm hydrogels with GO and cell cultures was investigated. For this purpose, culture medium was incubated with hydrogels containing GO and the viability and morphology of chinese hamster ovary (CHO) cells was examined after several days of culturing in presence of this medium.
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