The experimental research on the bed sands movement and the transitions of random motion regimes, has a lot to do with the obtaining of high-resolution images and particle trajectories. To improve the accuracy and availability of experiment, the new measurement and analysis methods based on UP/PTV technology are researched. First of all, the arrangement and technical requirements of underwater photography system without interference are investigated. According to PTV principle, the particle recognition and tracking program PTP based on Matlab platform is developed by adopting dynamic threshold and optimizing algorithm. Besides, new ideas of active particles and wagging effect are introduced, and the critical active area of wagging particles less than 0.2D50 is proposed. Multiple filtering is used to improve the effectiveness of sample data and to reduce the locating error of particles. Using the relatively complete data of bed sands trajectories based on series of experiments and UP/PTV technology, the Lagrange process properties of the particle movement are analyzed. The PDF of particle velocity shows a gamma function curve, which coincides with the research of Lajeunesse et al. Because of the length of the obtained trajectories is at least five times longer than former collected data, the PDF curve of step distance behaves much better than previous research including Roseberry et al. These results above indicate the reliable and scientific nature of the new experimental method.
|Translated title of the contribution||Experimental Method for Observing the Bed Sands Motion Regimes in Open Channel Flow Based on UP/PTV Technology|
|Original language||Chinese (Traditional)|
|Number of pages||13|
|Journal||Yingyong Jichu yu Gongcheng Kexue Xuebao/Journal of Basic Science and Engineering|
|State||Published - Feb 2021|
Bibliographical notePublisher Copyright:
© 2021, The Editorial Board of Journal of Basic Science and Engineering. All right reserved.
- Active particles
- Bed load
- Image recognition
- Incipient threshold
- Particle tracking
- Probability density
- Underwater photograph
- Wagging effect