Computer vision technique for tracking bed load movement

Citation
An. Papanicolaou et al., Computer vision technique for tracking bed load movement, J COMP CIV, 13(2), 1999, pp. 71-79
Citations number
27
Categorie Soggetti
Civil Engineering
Journal title
JOURNAL OF COMPUTING IN CIVIL ENGINEERING
ISSN journal
08873801 → ACNP
Volume
13
Issue
2
Year of publication
1999
Pages
71 - 79
Database
ISI
SICI code
0887-3801(199904)13:2<71:CVTFTB>2.0.ZU;2-X
Abstract
An advanced image analysis system, called Khoros, was used to investigate t he bed load movement of sediment particles in a laboratory flume. Incipient dow conditions prevailed throughout the experiments. Painted glass balls o f identical diameter and density were used to simulate the sediment particl es. They were uniformly placed on top of a tightly packed hat porous bed. E xperiments were performed with two distinct surface packing configurations. A video camera was used to monitor their motion within a specified area of view. The resulting video record was converted to digital images using a f rame grabber. These digital images were downloaded to a workstation for ana lysis. The outcome of this analysis provided quantitative information about the frequency of the entrainment of the glass beads, their displacement di stance, and the mode of their motion. Such information, when used in conjun ction with laser Doppler velocimeter measurements of the fluid velocity, ca n elucidate the physical mechanisms that are responsible for the entrainmen t of sediment. During the analysis of the tests, it was observed that the d isplacement of the beads was sporadic and occurred typically by rolling. Th e glass beads moved predominately along the flow direction, while on some o ccasions they were displaced in the transverse direction. For the two packi ng density tests that were examined, the minimum traveling distance in the longitudinal direction was found to be equal to one bead diameter and the m aximum was equal to 10 bead diameters. In the transverse direction, the max imum particle traveling distance was equal to four bead diameters. Finally, it is shown that the existing imaging workspace can be used to accurately identify the displacements of small particles, which are typically encounte red near incipient flow conditions and are not easily detectable with the b are eye. The imaging method described here is dynamic in nature and may pro ve to be a valuable tool for studying two-phase flows, as well as for visua lizing flow structures taking place near the boundary in turbulent flows.