A systematic approach to calibrate spray and break-up models for the simulation of high-pressure fuel injections

A novel calibration methodology is presented to accurately predict the fundamental characteristics of high-pressure fuel sprays for Gasoline Direct Injection (GDI) applications. The model was developed within Siemens Simcenter STAR-CD 3D CFD software environment and used Lagrangian–Eulerian solution scheme. simulations were carried out based on a quiescent, constant volume, computational vessel reproduce real spray testing environment. combination statistic optimisation methods selection process supported by wide range experimental data. comparative study conducted between two most commonly models atomisation: Kelvin–Helmholtz/Rayleigh–Taylor (KH–RT) Reitz–Diwakar (RD) break-up models. Rosin–Rammler (RR) mono-modal droplet size distribution tuned assign initial at critical nozzle exit location. half factorial design reveal how various factors influence properties, leading dominant ones. Numerical injection space-filling Design Experiment (DoE) schedules, which as input variables. Statistical regression nested procedures then applied define optimal levels factors. method aims give an alternative widely trial-and-error approach unveils correlation characteristics. results show importance secondary coefficients calibrate entire process. RD outperformed KH–RT in terms prediction when comparing numerical tip penetration counterparts. calibrated able correctly properties over pressure. work this paper part APC6 DYNAMO project led Ford Motor Company.