Diffusion of intruders in granular suspensions: Enskog theory and random walk interpretation

TL;DR

This paper applies Enskog kinetic theory and a random walk interpretation to analyze the diffusion of intruders in granular suspensions, comparing theoretical predictions with simulations and exploring the effects of system parameters.

Contribution

It introduces a detailed Enskog theory-based model for intruder diffusion in granular suspensions, validated by simulations and enhanced by a random walk perspective.

Findings

First Sonine approximation agrees well with simulations for most cases.

Second Sonine approximation improves accuracy, especially for lighter intruders.

Collisional effects significantly influence the diffusion coefficient.

Abstract

The Enskog kinetic theory is applied to compute the mean square displacement of intruders immersed in a granular gas of smooth inelastic hard spheres (grains). Both species (intruders and grains) are surrounded by an interstitial molecular gas (background) that plays the role of a thermal bath. The influence of the latter on the motion of intruders and grains is modeled via a standard viscous drag force supplemented by a stochastic Langevin-like force proportional to the background temperature. We solve the corresponding Enskog--Lorentz kinetic equation by means of the Chapman--Enskog expansion truncated to first order in the gradient of the intruder number density. The integral equation for the diffusion coefficient is solved by considering the first two Sonine approximations. To test these results, we also compute the diffusion coefficient from the numerical solution of the inelastic Enskog equation by means of the direct simulation Monte Carlo method. We find that the first Sonine approximation generally agrees well with the simulation results, although significant discrepancies arise when the intruders become lighter than the grains. Such discrepancies are largely mitigated by the use of the second-Sonine approximation, in excellent agreement with computer simulations even for moderately strong inelasticities and/or dissimilar mass and diameter ratios. We invoke a random walk picture of the intruders' motion to shed light on the physics underlying the intricate dependence of the diffusion coefficient on the main system parameters. This approach, recently employed to study the case of an intruder immersed in a granular gas, also proves useful in the present case of a granular suspension. Finally, we discuss the applicability of our model to real systems in the self-diffusion case. We conclude that collisional effects may strongly impact the diffusion coefficient of the grains.