Aerodynamic interaction and the force modification in a dense particle distribution

The flow within a dense distribution of particulates is modified by the presence of proximal particles. This modified filed inturn generate a force distribution within the particulates which is quiet different from an individual isolated particle. This complex system is studied using the gas-kinetic DSMC approach to develop models for large scale Eulerian-Lagrangian simulations

Multiphase particle in cell (MP-PIC) code development

Lagrangian particle modules that communicate back to the background flow is developed on the FLASH code framework to simulate dense particle systems. The developed code has filtering terms to incorporate the particle volume fraction and the momentum and energy source terms. The code is currently used to study the interaction of dense particle distributions with strong shock waves.

Table-top Experiment Modeling to Understand Particle Lifting in Nuclear Blasts

The ground soil entrained by near-surface nuclear blasts is detrimental to nuclear cloud generation. The nuclear mushroom cloud generates radiative inertial particles or fallouts that are carried by the upper-atmospheric currents to larger distances affecting a larger section of the vegetation through residual radiation. The mechanism of particle entrainment in these systems is not well understood. In the study, we numerically model a table-top electrostatic discharge performed at the New Jersey Institute of Technology (NJIT) by Dr. Ed Dreizin that mimics a large-scale nuclear blast to understand the gas-dynamic mechanisms under play.

The study revealed that for a monolayer of particles, the boundary layer velocity gradient established Saffman force is responsible for the initial lift-off of particles. Followed by the drag force generated by the thermal updraft. 

Surrogate mobility models for irregular aggregates

Dust grains present in nature, although tiny, have complex physical constructs. Fractal-like aggregates of dust are generated by the aggregation of smaller, spherical dust monomers. These grape-like super-grains can have complicated aerodynamic mobility owing to their complex, porous, asymmetric structure.

The high-fidelity gas-kinetic study models the gas phase as well as the aggregate gas interaction on a molecular level. The study resolves the convoluted gas streamlines through the porous aggregate interiors to accurately predict the fluid-induced grain mobility parameters such as the drag, lateral lift, and pitching torque. The extension of the study to rarefied gas conditions covers a large spectrum of practical flow regimes experienced by such grains.

Evolution of an expanding canonical particle-laden spherical blast wave system

A canonical multiphase system composed of an embedded monodisperse distribution of spherical particles in a spherical, high-energy gaseous charge is studied numerically using an Eulerian–Lagrangian approach to elucidate the role of non-dilute particle effects on the dynamics of the two-phase flow system. The direct simulation Monte Carlo method is modified to model inelastic particle–particle collisions and to model the gaseous flow inter-leaving through complex structures of monodisperse dense distributions of spherical particles to obtain parameters that are fit to semi-empirical particle cloud drag laws that account for aerodynamic interactions. The study reveals that inter-particle collisions decrease the total particle kinetic energy at early stages of the particle-laden blast wave system evolution, but near-particle interaction increases the particle kinetic energy at this stage. In contrast, at later stages of evolution, collisions tend to retain more kinetic energy, while the aerodynamic interactions tend to dissipate particle kinetic energy.

Uncertainty quantification of multiphase gas-particle flows (In progress)

The uncertainties associated with Eulerian-Lagrangian modeling of multiphase gas-particle systems are analyzed using the conventional uncertainty quantification (UQ) approach. The parameter sensitivity studies will help direct research in devising a better reduced-order surrogate models for multiphase system evolution.