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The settling behavior of polydisperse droplets in homogeneous and isotropic turbulence was measured by an ultra-high-resolution two-dimensional Particle Image Velocimetry. The aim of the present study is to provide new insight on the dependence of multi-scale particle settling behavior on characteristic parameters of two-phase turbulent flow via a sophisticate conditional analysis. The relative settling strength (defined as the ratio of mean droplet settling velocity to root mean square velocity of turbulence), whose effect on droplet settling behavior is of the primary interest, ranges as SvL=0.5–2.0. The turbulence Taylor Reynolds number is Reλ=200–300, and the droplet Stokes number is Stp=0.1–10. Voronoï analysis is performed to obtain the concentration field of discrete droplets from particle images. Particle structures including clusters or voids are detected, and the droplet settling velocities corresponding to various probing conditions, such as Stp, local particle concentration, and size of particle structures, were then analyzed. For the present configuration (droplet net sedimentation), there is a non-monotonic dependency of the settling velocity on local particle concentration. The negative correlation between them occurs in the moderate-concentration sub-regime and is insensitive to the variation of SvL, in which individual droplets interact with turbulent flow independently. It can be well explained by the commonly invoked preferential sweeping mechanisms. On the other hand, the dense-concentration regime, in which droplets prefer to accumulate into clusters, presents a positive correlation; namely, the conditional-averaged settling velocity decreases with the increase in local particle concentration. In this sub-regime, it is not the scale of single particles but the scale of particle clusters and the relative strength of turbulence (measured by SvL) that jointly determines the droplet settling behavior. Such a process, to our knowledge, is consistent with the so-called multi-scale preferential sweeping effect.
The settling behavior of polydisperse droplets in homogeneous and isotropic turbulence was measured by an ultra-high-resolution two-dimensional Particle Image Velocimetry. The aim of the present study is to provide new insight on the dependence of multi-scale particle settling behavior on characteristic parameters of two-phase turbulent flow via a sophisticate conditional analysis. The relative settling strength (defined as the ratio of mean droplet settling velocity to root mean square velocity of turbulence), whose effect on droplet settling behavior is of the primary interest, ranges as SvL=0.5–2.0. The turbulence Taylor Reynolds number is Reλ=200–300, and the droplet Stokes number is Stp=0.1–10. Voronoï analysis is performed to obtain the concentration field of discrete droplets from particle images. Particle structures including clusters or voids are detected, and the droplet settling velocities corresponding to various probing conditions, such as Stp, local particle concentration, and size of particle structures, were then analyzed. For the present configuration (droplet net sedimentation), there is a non-monotonic dependency of the settling velocity on local particle concentration. The negative correlation between them occurs in the moderate-concentration sub-regime and is insensitive to the variation of SvL, in which individual droplets interact with turbulent flow independently. It can be well explained by the commonly invoked preferential sweeping mechanisms. On the other hand, the dense-concentration regime, in which droplets prefer to accumulate into clusters, presents a positive correlation; namely, the conditional-averaged settling velocity decreases with the increase in local particle concentration. In this sub-regime, it is not the scale of single particles but the scale of particle clusters and the relative strength of turbulence (measured by SvL) that jointly determines the droplet settling behavior. Such a process, to our knowledge, is consistent with the so-called multi-scale preferential sweeping effect.
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