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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.

The US Department of Energy has formulated different gasoline fuels called ''Fuels for Advanced Combustion Engines (FACE)'' to standardize their compositions. FACE I is a low octane number gasoline fuel with research octane number (RON) of approximately 70. The detailed hydrocarbon analysis (DHA) of FACE I shows that it contains 33 components. This large number of components cannot be handled in fuel spray simulation where thousands of droplets are directly injected in combustion chamber. These droplets are to be heated, broken-up, collided and evaporated simultaneously. Heating and evaporation of single droplet FACE I fuel was investigated. The heating and evaporation model accounts for the effects of finite thermal conductivity, finite liquid diffusivity and recirculation inside the droplet, referred to as the effective thermal conductivity/effective diffusivity (ETC/ED) model.

Pre-ignition in SI engine is a critical issue that needs addressing as it may lead to super knock event. It is widely accepted that pre-ignition event emanates from hot spot(s) that can be anywhere inside the combustion chamber. The location and timing of hotspot is expected to influence the knock intensity from a pre-ignition event. In this study, we study the effect of location and timing of hot spot inside the combustion chamber using numerical simulations. The simulation is performed using a three-dimensional computational fluid dynamics (CFD) code, CONVERGE™. We simulate 3-D engine geometry coupled with chemistry, turbulence and moving structures (valves, piston). G-equation model for flame tracking coupled with multi-zone model is utilized to capture auto-ignition (knock) and solve gas phase kinetics. A parametric study on the effect of hot spot timing and location inside the combustion chamber is performed.

Gasoline compression ignition (GCI) engines are becoming more popular alternative for conventional spark engines to harvest the advantage of high volatility. Recent experimental study demonstrated that high reactivity gasoline fuel can be operated in a conventional mixing controlled combustion mode producing lower soot emissions than that of diesel fuel under similar efficiency and NOx level [1]. Therefore, there is much interest in using gasoline-like fuels in compression ignition engines. In order to improve the fidelity of simulation-based GCI combustion system development, it is mandatory to enhance the prediction of spray combustion of gasoline-like fuels. The purpose of this study is to model the spray characteristics of high reactivity gasoline fuels and validate the models with experimental results obtained through an optically accessible constant volume vessel under vaporizing [2] and reactive conditions [3].

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.

Partially premixed combustion (PPC) is an operating mode that lies between the conventional compression ignition (CI) mode and homogeneous charge compression ignition (HCCI) mode. The combustion in this mixed mode is complex as it is neither diffusion-controlled (CI mode) nor governed solely by chemical kinetics (HCCI mode). In this study, CFD simulations were performed to evaluate flame index, which distinguishes between zones having a premixed flame and non-premixed flame. Experiments performed in the optical engine supplied data to validate the model. In order to realize PPC, the start of injection (SOI) was fixed at −40 CAD (aTDC) so that a required ignition delay is created to premix air/fuel mixture. The reference operating point was selected to be with 3 bar IMEP and 1200 rpm. Naphtha with a RON of 77 and its corresponding PRF surrogate were tested. The simulations captured the general trends observed in the experiments well.

In most large-eddy simulation (LES) applications to two-phase engine flows, the liquid-air interactions need to be accounted for as source terms in the respective governing equations. Accurate calculation of these source terms requires the relative velocity “seen” by liquid droplets as they move across the flow, which generally needs to be estimated using a turbulent dispersion model. Turbulent dispersion modeling in LES is very scarce in the literature. In most studies on engine spray flows, sub-grid scale (SGS) models for the turbulent dispersion still follow the same stochastic approach originally proposed for Reynolds-averaged Navier-Stokes (RANS). In this study, an SGS dispersion model is formulated in which the instantaneous gas velocity is decomposed into a deterministic part and a stochastic part. The deterministic part is reconstructed using the approximate deconvolution method (ADM), in which the large-scale flow can be readily calculated.