Image-based Lagrangian Particle Tracking in Bed-load Experiments

Abstract

Image analysis has been increasingly used for the measurement of river flows due to its capabilities to furnish detailed quantitative depictions at a relatively low cost. This manuscript describes an application of particle tracking velocimetry (PTV) to a bed-load experiment with lightweight sediment. The key characteristics of the investigated sediment transport conditions were the presence of a covered flow and of a fixed rough bed above which particles were released in limited number at the flume inlet. Under the applied flow conditions, the motion of the individual bed-load particles was intermittent, with alternating movement and stillness terms. The flow pattern was preliminarily characterized by acoustic measurements of vertical profiles of the stream-wise velocity. During process visualization, a large field of view was obtained using two action-cameras placed at different locations along the flume. The experimental protocol is described in terms of channel calibration, experiment realization, image pre-processing, automatic particle tracking, and post-processing of particle track data from the two cameras. The presented proof-of-concept results include probability distributions of the particle hop length and duration. The achievements of this work are compared to those of existing literature to demonstrate the validity of the protocol.

Experimental Censorship of Bed Load Particle Motions and Bias Correction of the Associated Frequency Distributions

“…Nonetheless, the bias correction suggests improvement in the reconstructed distributions and, importantly, in the estimates of the mean values of the distributions, which are larger than those reported by Fathel et al (). Aside from bias correction of these estimates, both examples highlight the importance of appropriately designing experiments in order to mitigate effects of truncation that may come together with censorship (e.g., Radice et al, ).…”

Multicamera, Multimethod Measurements for Hydromorphologic Laboratory Experiments

“…The importance of this aspect depends on the time scales of the processes under investigation. In some earlier works related to sediment transport mechanics and interaction with a turbulent flow [39,49], the cameras were synchronized (possibly, also with other instruments) using suitable methods such as correlating spikes in temporal signals or by switching the room lights on and off. In the present study, instead, the time scales of the sediment front migration are relatively long and, therefore, the cameras could be synchronized up to a precision of 1 s using a stopwatch and marking on a paper the time at which the shooting was triggered for each camera.…”

“…Therefore, image distortion had to be removed by applying a radial transformation to the coordinates of the pixels in the image, as described by [38]. Pixel radial coordinates r were transformed into new ones r t as follows: r t = r/(1 + k × r), where k is a scalar parameter that must be determined by the user on the basis of a sample image imposing that curved lines become rectilinear (for a visual demonstration, see a recent video article by [39]). It is better to repeat this operation after each experiment, even though, if the camera is always placed in the same position, the required image transformation will be always the same.…”

On Reasons of the Scatter of Literature Data for Bed‐Load Particle Hops

“…Particle Tracking Velocimetry was conducted using the Streams software (Nokes, ) which was successfully applied in earlier studies of Campagnol et al (, ), Ballio and Radice (), Hosseini‐Sadabadi et al (, ), and Radice et al (). The stream‐wise and transverse coordinates ( x and y , respectively) of the fed particles were determined for each movie frame corresponding to an instant in time.…”