| Acceleration Statistics Of Inertial Particles In Turbulence | ||
| Sathyanarayana Ayyalasomayajula, Sibley School of Mechanical & Aerospace Engineering, Cornell University, 162 Upson Hall, Ithaca, NY 14853, Zellman Warhaft, Sibley School of Mechanical & Aerospace Engineering, Cornell University, 244 Upson Hall, Ithaca, NY 14853 and Lance R. Collins, Sibley School of Mechanical & Aerospace Engineering, Cornell University, 105 Upson Hall, Ithaca, NY 14853 Recent breakthroughs in particle tracking technology have enabled the measurement of fluid particle acceleration statistics in high-Reynolds-number turbulence. The probability density function of each component of acceleration has a highly stretched exponential tail, indicating large acceleration events are much more frequent than for an equivalent Gaussian field. Acceleration statistics of droplets in a wind tunnel show that particle inertia causes the tails of the distribution to become somewhat less stretched. We analyze the influence of particle inertia, in the weak limit, using a perturbation approach. We see that the primary effect of inertia is to bias the sampling of the flow; inertial particles tend to avoid regions with high rotation due to a "centrifuge" effect. Higher-order statistics can be replicated in a model flow consisting of point vortices of random strength and size. Analysis of this flow shows that a second-order effect in the change in the tails of the acceleration distribution of inertial particles is due to the decreasing correlation time of acceleration events of increasing magnitude. Extended Abstract Status: Not Uploaded | ||