# Statistical model for the orientation of non-spherical particles settling in turbulence

## TL;DR

This paper presents a Gaussian statistical model to predict the orientation distribution of small anisotropic particles settling in turbulence, aiding understanding of cloud microphysics and related phenomena.

## Contribution

The paper introduces a simple Gaussian model that accurately predicts particle orientation distributions considering inertia, advancing the understanding of particle behavior in turbulent flows.

## Key findings

- Model accurately predicts orientation distribution
- Applicable to ice-crystals in clouds
- Enhances understanding of cloud microphysics

## Abstract

The orientation of small anisotropic particles settling in a turbulent fluid determines some essential properties of the suspension. We show that the orientation distribution of small heavy spheroids settling through turbulence can be accurately predicted by a simple Gaussian statistical model that takes into account particle inertia and provides a quantitative understanding of the orientation distribution on the problem parameters when fluid inertia is negligible. Our results open the way to a parameterisation of the distribution of ice-crystals in clouds, and potentially leads to an improved understanding of radiation reflection, or particle aggregation through collisions in clouds.