LES of Vaporizing Gasoline Sprays Considering Multi-Injection Averaging and Grid-Convergent Mesh Resolution

Conference · Thu Jan 01 04:00:00 EST 2015

DOI:https://doi.org/10.1115/ICEF2015-1003· OSTI ID:1336938

Som, Sibendu; Wang, Zihan; Pei, Yuanjiang; Senecal, Peter Kelly; Pomraning, Eric

A state-of-the-art spray modeling methodology, recently presented by Senecal et al. [ , , ], is applied to Large Eddy Simulations (LES) of vaporizing gasoline sprays. Simulations of non-combusting Spray G (gasoline fuel) from the Engine Combustion Network are performed. Adaptive mesh refinement (AMR) with cell sizes from 0.09 mm to 0.5 mm are utilized to further demonstrate grid convergence of the dynamic structure LES model for the gasoline sprays. Grid settings are recommended to optimize the accuracy/runtime tradeoff for LES-based spray simulations at different injection pressure conditions typically encountered in gasoline direct injection (GDI) applications. The influence of LES sub-grid scale (SGS) models is explored by comparing the results from dynamic structure and Smagorinsky based models against simulations without any SGS model. Twenty different realizations are simulated by changing the random number seed used in the spray sub-models. It is shown that for global quantities such as spray penetration, comparing a single LES simulation to experimental data is reasonable. Through a detailed analysis using the relevance index (RI) criteria, recommendations are made regarding the minimum number of LES realizations required for accurate prediction of the gasoline sprays.

• Research Organization: Argonne National Laboratory (ANL)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE) - Office of Vehicle Technology
• DOE Contract Number: AC02-06CH11357
• OSTI ID: 1336938
• Country of Publication: United States
• Language: English