Turbulent multiphase flows are found throughout our universe, all over Earth and in many man-made systems. Despite surrounding us, their dynamics are still in many ways obscure and require further study. These chaotic systems are however quite complicated to both simulate or explore experimentally. In this thesis, we present our laboratory investigation of particle-laden turbulent flows in air. We first focus on the statistical dynamics of dilute multiphase turbulence. Utilizing a zero-mean-flow air turbulence chamber, we drop size-selected solid particles and study their dynamics with particle imaging and tracking velocimetry at multiple resolutions. The carrier flow is simultaneously measured by particle image velocimetry of suspended tracers, allowing the characterization of the interplay between both the dispersed and continuous phases. The turbulence Reynolds number based on the Taylor microscale ranges from 200 – 500, while the particle Stokes number based on the Kolmogorov scale varies between O(1) and O(10). Clustering is confirmed to be most intense for Stokes ≈ 1 , but it extends over larger scales for heavier particles. Individual clusters form a hierarchy of self-similar, fractal-like objects, preferentially aligned with gravity and sizes that can reach the integral scale of the turbulence. Remarkably, the settling velocity of Stokes ≈ 1 particles can be several times larger than the still-air terminal velocity, and the clusters can fall even faster. This is caused by downward fluid fluctuations preferentially sweeping the particles, and we propose that this mechanism is influenced by both large and small scales of the turbulence. The particle-fluid slip velocities show large variance, and both the instantaneous particle Reynolds number and drag coefficient can greatly differ from their nominal values. Finally, for sufficient loadings, the particles generally augment the small-scale fluid velocity fluctuations, which however may account for a limited fraction of the turbulent kinetic energy. We also investigate denser particle-laden flows, specifically plumes driven by the downward buoyancy of inertial particles. With similar tools, we conduct two experiments: one to capture the particle-phase behavior and another to measure the ambient air velocity. Our first focus is on the assumption of self-similarity, which unlike single-phase plumes is not a trivial assumption. We also characterize the mean plume properties observed: the particle-phase velocity and the plume spread comparing their evolution with axial distance from the plume source. From our measurements of the ambient air flow we calculate the entrainment velocity into the particle-laden plumes and using the time-averaged value we estimate the entrainment coefficient along the plume. We find a relatively stable entrainment rate, as expected in the assumption used to formulate many integral plume models. Lastly we compared our experimental results to single and multiphase plume models with the same initial conditions as our experiments. Our multiphase plume model, inspired by the work of Liu (2003) and Lai et al. (2016), well described our velocity measurements, which single phase models were completely unequipped for.
University of Minnesota Ph.D. dissertation.May 2020. Major: Aerospace Engineering and Mechanics. Advisor: Filippo Coletti. 1 computer file (PDF); xv, 146 pages.
Laboratory Investigation Of Dispere Multiphase-Turbulent Flows, Dilute & Dense Distributions Of Inertial Particles Settling In Air.
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