Comparison of Turbulence Modeling Methods for Evaluating GDI Sprays with Transient Needle Motion 2019-01-0271
Understanding the complex, transient spray phenomena associated with Gasoline Direct Injection (GDI) technologies continues to be key when designing injection systems to meet the stringent performance and emissions standards of modern internal combustion engines. Internal flow phenomena, such as string cavitation and hole-to-hole flow variations, are often highly transient and affected by turbulence. To better understand the current degree to which turbulence modeling influences simulations of GDI sprays, RANS and LES simulations have been performed on the multi-hole Spray G injector, with both results compared to previously available X-Ray radiography data. Specifically, the k-ω SST RANS model and the k-equation LES model with a WALE sub-grid scale stress model have been tested on an identical grid generated with the Generation 3 Spray G geometry, which includes as-produced injector dimensions based on X-Ray radiography measurements. The Homogeneous Relaxation Model (HRM) was employed to capture the effects of cavitation and flash boiling in both simulations. The increasingly popular Σ-Y model was used to compare droplet size predictions, as it is heavily dependent on turbulence modeling. A unique sealing algorithm was also included, providing the ability to capture post-injection dynamics. Finally, a grid dependence study was performed to determine the resolution requirements of the LES cases and demonstrate adequate convergence. The LES model was found to produce stronger correlations between the needle motion and per-hole rate of injection during injection, as well as capturing more spatial fluctuations in the spray when compared to the RANS framework. Both turbulence models resulted in flow rates that agreed well with experimental measurements.
Gabriel L. Jacobsohn, Chinmoy K. Mohapatra, Ronald O. Grover, Daniel J. Duke, David P. Schmidt
University of Massachusetts Amherst, University of Massachusetts-Amherst, General Motors Research and Development, Monash University