«Detailed Program

ID 193

A Compressible Σ-Υ Two-Fluid Atomization Model with Dynamic Interface Sharpening based on Flow Topology Detection

Georgia Nykteri
City, University of London
United Kingdom

Phoevos Koukouvinis
City, University of London
United Kingdom

Manolis Gavaises
City, University of London
United Kingdom

 

Abstract:

Liquid fuel atomization is characterized by multi-scale flow features and the coexistence of different flow regimes which complicate the simulation of an atomizing spray under realistic operating conditions. The present work introduces an atomization model dealing with such multi-scale complexities. The proposed model is compressible, so it can capture the density variations that affect spray penetration and atomization mechanisms. It is developed within a multi-phase Eulerian-Eulerian framework that considers slip velocity effects between the phases and introduces an additional transport equation for the surface area (Σ); the latter aims to model the unresolved sub-grid scale surface area variation. Moreover, a flow topology detection algorithm is applied in the flow field aiming to distinguish between different flow regimes; finally, the numerical algorithm applies appropriate closure relations for the interfacial source terms of the two-fluid model. The interfacial structures are also treated differently depending on the flow topology; a VOF method is applied in dense spray regions for resolving the interface fully and a non-sharp interface model is imposed in dilute spray regions, where sub-grid scale models are implemented for the modelling of relevant phenomena. The efficient coupling between the two-fluid model and the VOF method is examined via a standard interface capturing validation case of a rising bubble in a stagnant liquid. For the validation of the dynamic switching between different model formulations based on local topology and the numerical stability under the coexistence of various flow regimes, a Rayleigh-Taylor instability case is simulated and tested with the proposed model.