Interphase coupling for gas-droplet flows using the fully Lagrangian approach

TL;DR

This paper introduces a new fully Lagrangian approach combined with kernel regression for efficient two-way coupled simulations of evaporating sprays, maintaining high accuracy while significantly reducing computational costs.

Contribution

The novel method integrates FLA and kernel regression for detailed, efficient two-way coupling in spray simulations, outperforming traditional particle tracking in speed.

Findings

Achieves comparable accuracy to standard Lagrangian methods

Provides approximately 100-fold speedup in simulations

Retains detailed droplet cloud structures

Abstract

A novel method combining the fully Lagrangian approach (FLA) and kernel regression has been developed for two-way coupled simulations of evaporating sprays. The carrier phase is incompressible viscous flow described by the Navier-Stokes equations. The admixture is considered to be a cloud of monodisperse evaporating droplets, which is treated as a continuum in the FLA. All droplet parameters are calculated along selected trajectories with the number density calculated using the Lagrangian form of the continuity equation. To enable two-way coupling, the momentum and mass phase exchange terms must be calculated in each volume element of an Eulerian mesh. This is achieved by using kernel regression in conjunction with the FLA trajectory data, which retains the detail of complex structures in droplet clouds by adaptively scaling the kernel support according to the local droplet field deformation. In this work, the mass and momentum coupling source terms obtained using the FLA are assessed against reference values calculated using a standard Lagrangian particle tracking simulation that incorporates a PSI-CELL box-counting method. It is shown that the FLA retains the same level of fidelity and smoothness as the reference PSI-CELL case, whilst also providing a computational speedup factor of around 100 times due to the decreased droplet seeding.