Search Results

This study presents a computational framework to predict the outcome of combustion process based on a given RANS initial condition by performing statistical analysis of Sankaran number, Sa, and ignition regime theory proposed by Im et al. [1]. A criterion to predict strong auto-ignition/detonation a priori is used in this study, which is based on Sankaran-Zeldovich criterion. In the context of detonation, Sa is normalized by a sound speed, and is spatially calculated for the bulk mixture with temperature and equivalence ratio stratifications. The initial conditions from previous pre-ignition simulations were used to compute the spatial Sa distribution followed by the statistics of Sa including the mean Sa, the probability density function (PDF) of Sa, and the detonation probability, PD. Sa is found to be decreased and detonation probability increased significantly with increase of temperature.

Super-knock that occurs in spark ignition (SI) engines is investigated using two-dimensional (2D) numerical simulations. The temperature, pressure, velocity, and mixture distributions are obtained and mapped from a top dead center (TDC) slice of full-cycle three-dimensional (3D) engine simulations. Ignition is triggered at one end of the cylinder and a hot spot of known temperature was used to initiate a pre-ignition front to study super-knock. The computational fluid dynamics code CONVERGE was used for the simulations. A minimum grid size of 25 μm was employed to capture the shock wave and detonation inside the domain. The Reynolds-averaged Navier-Stokes (RANS) method was employed to represent the turbulent flow and gas-phase combustion chemistry was represented using a reduced chemical kinetic mechanism for primary reference fuels. A multi-zone model, based on a well-stirred reactor assumption, was used to solve the reaction terms.