Ellipsoidal soft micro-particles suspended in dilute viscous flow

Soft particles in viscous flows are prevalent both in nature and in various industrial applications. Notable examples include biological cells such as blood cells and bacteria as well as hydrogels and vesicles. To model these intriguing particles, we present an extension of our recent, efficient, and versatile pseudo-rigid body approach, originally developed for initially spherical soft particles suspended in arbitrary macroscale viscous flows. The novel extension allows modeling the barycenter and shape dynamics of soft initially non-spherical, i.e. ellipsoidal particles by introducing a novel shape and orientation tensor. We consider soft, micrometer-sized, ellipsoidal particles deforming affinely. To this end, we combine affine deformations (as inherent to a pseudo-rigid body) and the Jeffery-Roscoe model to analytically determine the traction exerted on a soft ellipsoidal particle suspended locally in a creeping flow at the particle scale. Without loss of generality, we assume nonlinear hyperelastic material behavior for the particles considered. The novel extension of our recent numerical approach for soft particles demonstrates that the deformation and motion of the particles can be accurately reproduced also for ellipsoidal particles and captures results from the literature, however, at drastically reduced computational costs. Furthermore, we identify both the tumbling and trembling dynamic regime for soft ellipsoidal particles suspended in simple shear flow again capturing results from the literature. Our extended approach is first validated using experimental and numerical studies from the literature for quasi-rigid as well as soft particles, followed by a comparison of the effects of particle deformability for some well-known fluid flow cases, such as laminar pipe flow, lid-driven cavity flow, and a simplified bifurcation. We find that taking particle deformability into account leads to notable deviations in the particle trajectory compared to rigid particles, with increased deviations for higher initial particle aspect ratio. Furthermore, we demonstrate that our approach can track a statistically relevant number of soft particles in complex flow situations.