Effects of Turbulence on Settling Velocities of Synthetic and Natural Particles

Friday, 19 December 2014
Corrine Jacobs, Marek Jendrassak, Roi Gurka and Erin E Hackett, Coastal Carolina University, School of Coastal and Marine Systems Science, Conway, SC, United States
For large-scale sediment transport predictions, an important parameter is the settling or terminal velocity of particles because it plays a key role in determining the concentration of sediment particles within the water column as well as the deposition rate of particles onto the seabed. The settling velocity of particles is influenced by the fluid dynamic environment as well as attributes of the particle, such as its size, shape, and density. This laboratory study examines the effects of turbulence, generated by an oscillating grid, on both synthetic and natural particles for a range of flow conditions. Because synthetic particles are spherical, they serve as a reference for the natural particles that are irregular in shape. Particle image velocimetry (PIV) and high-speed imaging systems were used simultaneously to study the interaction between the fluid mechanics and sediment particles’ dynamics in a tank. The particles’ dynamics were analyzed using a custom two-dimensional tracking algorithm used to obtain distributions of the particle’s velocity and acceleration. Turbulence properties, such as root-mean-square turbulent velocity and vorticity, were calculated from the PIV data. Results are classified by Stokes number, which was based-on the integral scale deduced from the auto-correlation function of velocity. We find particles with large Stokes numbers are unaffected by the turbulence, while particles with small Stokes numbers primarily show an increase in settling velocity in comparison to stagnant flow. The results also show an inverse relationship between Stokes number and standard deviation of the settling velocity. This research enables a better understanding of the interdependence between particles and turbulent flow, which can be used to improve parameterizations in large-scale sediment transport models.