Abstract
Potential fuel economy improvements and environmental legislation have renewed interest in Gasoline Direct Injection (GDI) engines. Computational models of fuel injection and mixing processes pre-ignition are being developed for engine optimisation. These highly transient thermofluid models require verification against temporally and spatially resolved data-sets. The authors have previously established the capability of PDA to provide suitable temporally and spatially resolved spray characteristics such as mean droplet size, velocity components and qualitative mass distribution. This paper utilises this data-set to assess the predictive capability of a numerical model for GDI spray prediction. After a brief description of the two-phase model and discretisation sensitivity, the influence of initial spray conditions is discussed. A minimum of 5 initial global spray characteristics are required to model the downstream spray characteristics adequately under isothermal, atmospheric conditions. Verification of predicted transient spray characteristics such as the hollow-cone, cone collapse, head vortex, stratification and penetration are discussed, and further improvements to modelling GDI sprays proposed.