On the drag and lift coefficients of ellipsoidal particles under rarefied flow conditions

TL;DR

This paper develops new correlations for drag and lift coefficients of ellipsoidal particles in rarefied flows using DSMC simulations, extending models beyond the continuum regime for practical engineering applications.

Contribution

The study introduces a novel numerical approach combining a cut-cell algorithm with DSMC to accurately model gas-particle interactions and derive extended correlations for non-spherical particles in rarefied regimes.

Findings

New predictive models for drag and lift coefficients in transitional and free-molecular regimes.

Extended correlations applicable outside the simulated Knudsen number range.

Enhanced accuracy over existing models for ellipsoidal particles in rarefied flows.

Abstract

The capability to simulate a two-way coupled interaction between a rarefied gas and an arbitrary-shaped colloidal particle is important for many practical applications, such as aerospace engineering, lung drug deliver and semiconductor manufacturing. By means of numerical simulations based on the Direct Simulation Monte Carlo (DSMC) method, we investigate the influence of the orientation of the particle and rarefaction on the drag and lift coefficients, in the case of prolate and oblate ellipsoidal particles immersed in a uniform ambient flow. This is done by modelling the solid particles using a cut-cell algorithm embedded within our DSMC solver. In this approach, the surface of the particle is described by its analytical expression and the microscopic gas-solid interactions are computed exactly using a ray-tracing technique. The measured drag and lift coefficients are used to extend the correlations available in the continuum regime to the rarefied regime, focusing on the transitional and free-molecular regimes. The functional forms for the correlations for the ellipsoidal particles are chosen as a generalisation from the spherical case. We show that the fits over the data from numerical simulations can be extended to regimes outside the simulated range of $Kn$ by testing the obtained predictive model on values of $Kn$ that where not included in the fitting process, allowing to achieve an higher precision when compared with existing predictive models from literature. Finally, we underline the importance of this work in providing new correlations for non-spherical particles that can be used for point-particle Euler-Lagrangian simulations to address the problem of contamination from finite-size particles in high-tech mechanical systems.