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Home > News > Ph.D. Thesis > Ph.D. Thesis 2020

Lundi 19 octobre 2020, soutenance de thèse de Daniel Odens Mora-Paiba

Clustering and settling dynamics of inertial particles under turbulence

Turbulent particle laden flows are widespread in industrial applications, and natural phenomena. Over the last decades, two observations: preferential concentration, and particle settling velocity modification have stood out as the most relevant consequences of such particle - turbulence interactions. Given the complexity of the problem, I will present an overview of the work conducted during my PhD. It will include: a sensitivity analysis of the Vorono\"i tessellation method, which is widely used to quantify preferential concentration. We found some pitfalls that compromise the results of the analysis using uni-dimensional records. Second, I will also describe some particularities of turbulence cascade in active grid generated flows, e.g., our results show that an active grid left open (with minimum blockage) exhibits scalings similar to those found in fractal grids. Third, I will describe a new method to estimate the integral length scale. The method is applicable to many flow conditions, even when the autocorrelation function does not cross zero, such as in some active grid generated flows. In addition, I will present some results of a proposed new approach to estimate the carrier phase turbulence in the presence of particles. Measuring both phases accurately is a challenging task. Finally, I will show some data suggesting that the Taylor Reynolds number $Re_\lambda$ is the leading order contributor the particles settling velocity modification: at increasing values of $Re_\lambda$ the particles are prone to have their settling velocities hindered.