On the settling and clustering behavior of polydisperse gas-solid flows with application to pyroclastic density currents

TL;DR

This study investigates how polydispersity influences sedimentation and clustering in gas-solid flows, revealing significant effects on structure formation and proposing new predictive metrics and models for these complex multiphase systems.

Contribution

It provides the first detailed analysis of polydisperse gas-solid flow behavior, highlighting the impact on clustering and introducing new predictive tools for these flows.

Findings

Polydispersity significantly affects cluster formation, especially in dilute flows.

Higher volume fractions reduce the impact of polydispersity on flow behavior.

A new clustering metric 'surface loading' effectively predicts clustering degree.

Abstract

Sedimenting flows occur in a range of society-critical systems, such as circulating fluidized bed reactors and pyroclastic density currents (PDCs), the most hazardous volcanic process. In these systems, mass loading is sufficiently high ($\gg\mathcal{O}(1)$) and momentum coupling between the phases gives rise to mesoscale behavior, such as formation of coherent structures. This heterogeneity has been demonstrated to generate and sustain turbulence in the carrier phase and directly impact large-scale quantities of interest, such as settling time. While contemporary work has explored the physical processes underpinning these multiphase phenomenon for monodisperse assemblies of particles, polydispersity flow behavior has been largely understudied. Since all real-world flows are polydisperse, understanding the role of polydispersity in gas-solid systems is critical for informing closures that are accurate and robust. This work characterizes the sedimentation behavior of two polydispersed gas-solid flows, with statistical and physical properties of the particulate phase sampled from historical PDC ejecta. Highly resolved data for both polydisperse distributions of particles at two volume fractions (1% and 10%) is collected using an Euler-Lagrange framework and is compared with monodisperse configurations of particles with diameters equivalent to the arithmetic mean of the polydisperse configurations. From this data, we find that polydispersity has an important impact on cluster formation and structure and that this is most pronounced for more dilute flows. At higher volume fraction, the effect of polydispersity is less pronounced. We also propose a new metric for predicting the degree of clustering, termed `surface loading', and a model for the coefficient of drag that produces accurate predictions for settling velocity given the high-fidelity data presented.