Methodological aspects of using high-speed cameras to quantify soil splash phenomenon

A study of particle splash on developing ripple forms for two bed materials

Image processing techniques for the measurement of two-phase bubbly pipe flows using particle image and tracking velocimetry (PIV/PTV)

Optically based measurements in high Reynolds number fluid flows often require high-speed imaging techniques. These cameras typically record data internally and thus are limited by the amount of onboard memory available. A novel camera technology for use in particle tracking velocimetry is presented in this paper. This technology consists of a dynamic vision sensor in which pixels operate in parallel, transmitting asynchronous events only when relative changes in intensity of approximately 10% are encountered with a temporal resolution of 1 μs. This results in a recording system whose data storage and bandwidth requirements are about 100 times smaller than a typical high-speed image sensor. Post-processing times of data collected from this sensor also increase to about 10 times faster than real time. We present a proof-of-concept study comparing this novel sensor with a high-speed CMOS camera capable of recording up to 2,000 fps at 1,024 × 1,024 pixels. Comparisons are made in the ability of each system to track dense (ρ >1 g/cm3) particles in a solid–liquid two-phase pipe flow. Reynolds numbers based on the bulk velocity and pipe diameter up to 100,000 are investigated.

To validate the particle motion in flighted rotating drum (FRD), a laboratory FRD was built and operated at 15% filling degree and 10 rpm rotation speed using plastic balls as bed material. The particle tracking velocimetry (PTV) and magnetic particle tracking (MPT) techniques were applied to investigate the particle flow behavior. The 3D particle flow was modeled by Discrete Element Method (DEM) with LIGGGHTS. The height of the barycenter of all overall particles and particle instantaneous velocity were calculated from PTV and DEM data. The 3D time-averaged particle velocity distributions obtained from MPT experiment and DEM simulation were compared.Keywords: flighted rotating drum; particle motion; particle tracking velocimetry; magnetic particle tracking; DEM simulation.

The motion of graded gravels under steady and spatially uniform turbulent flow is investigated in laboratory conditions using particle tracking velocimetry (PTV). The gravel bed is subjected to flows approaching critical armor velocity, and water worked until static armor is reached. A digital particle tracking (DPT) algorithm, based on image subtraction between subsequent frames, is developed and applied on the particle scale as the graded gravel bed is water-worked. The dynamic evolution of graded gravels is quantified continuously for up to 8 h. Characteristics of particle motion are identified, and movement patterns under complex flow conditions are analyzed. Particle tracking is applied to low-frequency (0.67-fps) and high-frequency (30-fps) data. This study provides a new perspective on gravel particle transport distances, trajectory sinuosity, sediment transport rate, fractional sediment transport rates, particle movement patterns, and instantaneous particle velocities.

In order to determine the kinetic energy of an explosion it is necessary to know the initial velocities of ejected fragments. Calculations of initial velocities made earlier with few exceptions did not take into account the resistance of the air and therefore, greatly underestimated the initial velocities, and consequently the energy of the explosions. A solution of the inverse problem of ballistics which takes into account air resistance makes it possible to find precise values of initial velocities of ejection, determined from the distance of ejected fragments and their ballistic coefficients. The method makes it possible to determine the kinetic energy of explosions for eruptions which were not directly observed. It is shown that the velocity field in volcanic explosions is not spherical,i.e. the velocities of ejection of fragments differ markedly in different directions. Accordingly, the maximum distance of ejection of fragments depends not only on the initial angle of ejection, but also on the character of distribution of initial velocities and the ballistic coefficients of the fragments. For fragments with diameters of 40 cm to 2 m the maximum distance of ejection is realized in the case of angles of ejection of 30–36°. For smaller fragments the optimal angles of ejection are still smaller. The ballistics of explosive eruptions of the volcanoes Asama, Arenal, and Shiveluch are considered.

Fuzzy logic has proven to be a simple and robust method for process control. Instead of requiring a complex model of the system, a user defined rule base is used to control the process. In this paper the principles of fuzzy logic control are applied to Particle Tracking Velocimetry (PTV). Two frames of digitally recorded, single exposure particle imagery are used as input. The fuzzy processor uses the local particle displacement information to determine the correct particle tracks. Fuzzy PTV is an improvement over traditional PTV techniques which typically require a sequence (> 2) of image frames for accurately tracking particles. The fuzzy processor executes in software on a PC without the use of specialized array or fuzzy logic processors. A pair of sample input images with roughly 300 particle images each results in more than 200 velocity vectors in under 8 seconds of processing time.

Dataset of velocities of dry granular flows in a partially obstructed tilted chute

Windblown sand transport is a leading factor in the geophysical evolution of arid and semi-arid regions. The evolution speed is usually indicated by the sand transport rate that is a function of launch velocity of sand particle, which has been investigated by the experimental measurement and numerical simulation. However, the obtained results in literatures are inconsistent. Some researchers have discovered a relation between average launch velocity and wind shear velocity, while some other researchers have suggested that average launch velocity is independent of wind shear velocity. The inconsistence of launch velocity leads to a controversy in the scaling law of the sand transport rate in the windblown case. On the contrary, in subaqueous case, the scaling law of the sand transport rate has been widely accepted as a cubic function of fluid shear velocity. In order to explain the debates surrounding the windblown case and the difference between windblown and subaquatic cases, this study reinvestigates the scaling law of the vertical launch velocity of windblown transported sand particles by using a dimensional analysis in consideration of the compatibility of the characteristic time of sand particle motion and that of air flow. Then a wind tunnel experiment is conducted to confirm the revisited scaling law, where the sand particle motion pictures are recorded by a high-speed camera and then the launch velocity is solved by the particle tracking velocimetry. By incorporating the results of dimensional analysis and wind tunnel experiment, it can be concluded that, the ratio of saltons number to reptons number determines the scaling law of sand particle launch velocity and that of sand transport rate, and using this ratio is able to explain the discrepancies among the classical models of steady sand transport. Moreover, the resulting scaling law can explain the sand sieving phenomenon: a greater fraction of large grains is observed as the distance to the wind tunnel entrance becomes larger.

A horizontally oriented cylindrical tumbler, filled at variable depth with a monoplane of uniform cylindrical media, was rotated at various constant speeds. Resultant motion was captured using a high-speed camera. The images were post-processed with particle tracking velocimetry and image correlation algorithms in order to estimate each particle’s translational and rotational velocity. The particle interactions were then characterized into distance groups based on non-dimensional flow characteristics, where similarities were found with transitions between slip/no-slip and rotation/no-rotation conditions. The results of the particle interactions show rotational chains as analogous to translational force chains. The interactions demonstrated that occurrences of no-slip, no-rotation behavior correspond to areas of confined translational motion. No-slip rotation behavior was lower in areas of high interaction and higher in developing flow areas.

Experimental investigation of interparticle collision rate in particulate flow

An improved correlation based Particle Tracking Velocimetry (PTV) algorithm was proposed in the present paper. The path tracking of the tracer particles was achieved through a correlation operation of the small interrogation window around the studied tracer particles at two-time steps. The central positions of the tracer particles were determined by the correlation operation of the tracer particle image with a Gaussian particle mask in order to improve the accuracy to identify the central positions of particles up to sub-pixel level. The performance of the present improved correlation based Particle Tracking Velocimetry (PTV) algorithm was evaluated by using both synthetic VSJ standard PIV images and actual PIV images of a self-induced sloshing. Compared with other conventional PTV methods, the present improved correlation based PTV algorithm was found to be able to provide better solution and more robust for suppression the effect of background noise in the PIV images.

This work presents two new methods for computing finite-time Lyapunov exponents (FTLEs) from noisy spatiotemporally resolved experimentally measured image data of the type used for particle image velocimetry (PIV) or particle tracking velocimetry (PTV). These new approaches are based on the simple insight that the particle images recorded during PIV experiments represent Lagrangian flow tracers whose trajectories lend themselves to the direct computation of flow maps, and related quantities such as flow map gradients and FTLEs. We show that using this idea we can improve the reliability and accuracy of FTLE calculation through the use of either direct pathline flow map (PFM) calculation, where individual particle pathlines over a fixed period of time are used to determine the flow map, or particle tracking flow map compilation (FMC), where instantaneous tracking results are used to estimate small snapshots of the flow map which are then compiled to describe the complete flow map. Comparisons of the traditional velocity field integration (VFI) method for computing FTLE fields with these new methods show that FMC produces significantly more accurate estimates of the FTLE field for both synthetic data and experimental data especially in cases where the particle number density is low. This is because the VFI estimates particle motion while PTV directly measures particle motion and therefore generates a more accurate flow map. Overall, our results suggest that VFI is not always a reliable approach when applied to noisy experimental PIV data. For cases where particle loss between frames is minimal, the PFM can also produce better results, but the final field is susceptible to error due to the unstructured nature of the raw flow maps. When comparing the ability to match the true separatrix of a flow, FMC is shown to be a far superior method. The separatrix from FMC has an 80 % overlap with the true solution as compared to approximately 25 % for the PFM and only 1 % for the VFI method. FMC shows a significant advantage when the particle seeding is low, which is particularly relevant for applications to environmental or biological flows where adding seed particles is not always practical, and investigation of Lagrangian flow structures must rely on naturally occurring flow tracers.

A micron-resolution particle image velocimetry (PIV) system has been developed to spatially and temporally resolve electroosmotic flow fields within microfluidic bioanalytical devices. A second diagnostic technique, particle tracking velocimetry (PTV) has been used to determine the distribution of electrophoretic mobilities of seed particles and thereby make the PIV measurements quantitative. This second particle tracking technique has been used to determine probability distribution functions of the seed particles. Results from simulations of electric fields yield local electric field strengths in the geometries of interest. The measured mean mobility of the seed particles (obtained from PTV measurements) is then multiplied by the local electric field vector to obtain the electrophoretic velocity. The variance on the particle mobility measurement influences the errors introduced in the electroosmotic flow measurements. After total particle velocities are measured within a microfluidic system of interest, the seed particle electrophoretic velocities are subtracted from the PIV total velocity data to obtain electroosmotic flow field velocities. Ensemble-averaged velocity field measurements for electroosmotic flow at the intersection of a cross-channel are presented.

The relaxation method is known as one of the most powerful algorithms for frame-to-frame particle tracking velocimetry (PTV). But there have been so far few examples applied to the PIV measurement so that the possibility of the method has not yet been explored up to the practical use level. So in the present work, the performance of the relaxation method PTV is examined using the PIV standard images open on the Internet and the potential of this new method is discussed under varied experimental conditions. Some comparison is made with respect to other particle tracking PTV methods inclusive of a multi frame in-line tracking method.