Juan Salazar

Inertial particle acceleration statistics in turbulence: Effects of filtering, biased sampling, and flow topology

In this study, we investigate the effect of “biased sampling,” i.e., the clustering of inertial particles in regions of the flow with low vorticity, and “filtering,” i.e., the tendency of inertial particles to attenuate the fluid velocity fluctuations, on the probability density function of inertial particle accelerations. In particular, we find that the concept of “biased filtering” introduced by Ayyalasomayajula et al. [“Modeling inertial particle acceleration statistics in isotropic turbulence,” Phys. Fluids 20, 0945104 (2008)10.1063/1.2976174], in which particles filter stronger acceleration events more than weaker ones, is relevant to the higher order moments of acceleration. Flow topology and its connection to acceleration is explored through invariants of the velocity-gradient, strain-rate, and rotation-rate tensors. A semi-quantitative analysis is performed where we assess the contribution of specific flow topologies to acceleration moments. Our findings show that the contributions of regions of h...