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To meet stringent emissions regulations, filtration devices are often used in engine exhaust systems to reduce particulate mass (PM) and particulate number (PN). Diesel particulate filters (DPFs) are a well-established means of reducing PM from diesel engines to meet emissions regulations. New emissions regulations will most likely require a similar technology on gasoline engines with direct injection, gasoline particulate filters (GPFs). Due to differences in the exhaust and particulate characteristics, the design and operation of GPFs and DPFs differ. In a DPF filtration is dominated by the buildup of a soot cake. Whereas in a GPF, much of the soot is trapped inside the porous substrate, or filter wall, where deep-bed filtration is dominant. Thus, an accurate model describing the porous filtration properties of GPF substrates is desired. The pore filtration model (PFM) was developed to more accurately model the deep-bed filtration process that occurs in a GPF.

Natural gas is a promising alternative fuel for internal combustion engines due to its rich reserves and low price, as well as good physical and chemical properties. Its low carbon structure and high octane number are beneficial for CO2 reduction and knock mitigation, respectively. Diesel and natural gas dual fuel combustion is a viable pathway to utilize natural gas in diesel engines. To achieve high efficiency and low emission combustion in a practical diesel engine over a wide range of operating conditions, understanding the performance responses to engine system parameter variations is needed. The controllability of two combustion strategies, diesel pilot ignition (DPI) and single injection reactivity controlled compression ignition (RCCI), were evaluated using the multi-dimension CFD simulation in this paper.

A swept-volume method of calculating the volume swept by the flame during each time step is developed and used to improve the calculation of fuel reaction rates. The improved reaction rates have been applied to the ignition model and coupled with the level set G-equation combustion model. In the ignition model, a single initial kernel is formed after which the kernel is convected by the gas flow and its growth rate is determined by the flame speed and thermal expansion due to the energy transfer from the electrical circuit. The predicted ignition kernel size was compared with the available experimental data and good agreements were achieved. Once the ignition kernel reaches a size when the fully turbulent flame is developed, the G-equation model is switched on to track the mean turbulent flame front propagation.

In this work the modeling aspects of fuel vaporization are studied. To start with, the effects of vaporization model on engine simulations are studied. This is done by using two different fuel surrogates. Next a set of non-reacting spray simulations were performed under different ambient and operating conditions and for two different fuels. This was done for spray model validation and to look at the effect of vaporization model on liquid penetration length. Following an observed discrepancy in one of the spray cases, effect of ambient temperature on liquid length, two sensitivity analyses were performed. These analyses take into account the effects of each spray-sub model on vaporization and effects of spray breakup constants on liquid penetration. Using the results from the sensitivity analyses and linearized stability theory an empirical correction factor was developed to correct the spray behavior at low ambient temperatures.

Modeling ignition kernel development in spark ignition engines is crucial to capturing the sources of cyclic variability, both with RANS and LES simulations. Appropriate kernel modeling must ensure that energy transfer from the electrodes to the gas phase has the correct timing, rate and locations, until the flame surface is large enough to be represented on the mesh by the G-Equation level-set method. However, in most kernel models, geometric details driving kernel growth are missing: either because it is described as Lagrangian particles, or because its development is simplified, i.e., down to multiple spherical flames. This paper covers the geometric aspects of kernel development, which makes up the core of a Triangulated Lagrangian Ignition Kernel model. One (or multiple, if it restrikes) spark channel is initialized as a one-dimensional Lagrangian particle thread.

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.