Linear and nonlinear inversion schemes to retrieve collision kernel values from droplet size distribution change

Abstract

This study presents an attempt to retrieve collision kernel values from changes in the droplet size distribution due to collision growth. Original linear and nonlinear inversion schemes are presented, which use the simple a priori assumption that the total collision rate is given by the sum of the gravitational and turbulent contributions. Our schemes directly handle binned (discretized) size distributions and, therefore, do not require any assumptions on distribution functional forms, such as the self-similarity assumption. To validate the schemes, three-dimensional direct numerical simulation (DNS) of colliding droplets in steady isotropic turbulence is performed. In the DNS, air turbulence is calculated using a pseudo-spectral method, while droplet motions are tracked by the Lagrangian method. Comparison between the retrieved collision kernels and the collision kernels obtained directly from the DNS show that for low Reynolds number flows both the linear and nonlinear inversion schemes give good accuracy. However, for higher Reynolds number flows the linear inversion scheme gives significantly larger retrieval errors, while the errors for the nonlinear scheme remain small.