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Multi-dimensional models coupled with a reduced chemical mechanism were used to investigate the effect of fuel on exergy destruction fraction and sources in a reactivity controlled compression ignition (RCCI) engine. The exergy destruction due to chemical reaction (Deschem) makes the largest contribution to the total exergy destruction. Different from the obvious low temperature heat release (LTHR) behavior in gasoline/diesel RCCI, methanol has a negative effect on the LTHR of diesel, so the exergy destruction accumulation from LTHR to high temperature heat release (HTHR) can be avoided in methanol/diesel RCCI, contributing to the reduction of Deschem. Moreover, the combustion temperature in methanol/diesel RCCI is higher compared to gasoline/diesel RCCI, which is also beneficial to the lower exergy destruction fraction. Therefore, the exergy destruction of methanol/diesel RCCI is lower than that of gasoline/diesel RCCI at the same combustion phasing.

Syngas is considered to be a promising alternative fuel for the dual-fuel reactivity controlled compression ignition (RCCI) engine to reduce the fuel consumption and emissions. However, the optimal syngas compositions and fuel supply strategies in RCCI combustion are significantly affected by engine configurations, which have not been investigated yet. In this study, by integrating the KIVA-3V code and the non-dominated sort genetic algorithm II (NSGA-II), the optimizations for a 0.477 L single-cylinder engine with shallow/wide piston bowl (Engine A) and a 1.325 L single-cylinder engine with conventional omega-type piston (Engine B) under the syngas/diesel RCCI combustion were performed. The optimized operating parameters include the fuel-supply strategies, syngas compositions, and intake conditions. The results indicate that the fuel-supply strategy is flexible in Engine A due to the shallow/wide piston bowl and the relatively small cylinder bore.

Dimethyl ether (DME) attracts increasing attentions in recent years, because it can reduce the carbon monoxide (CO), unburned hydrocarbon (HC), and soot emissions for engines as the transportation fuel or the fuel additive. In this paper, a reduced DME oxidation mechanism is developed using the decoupling methodology. The rate constants of the fuel-related reactions are optimized using the non-dominated sorting genetic algorithm II (NSGA-II) to reproduce the ignition delay times in shock tubes and major species concentrations in jet-stirred reactors (JSR) over low-to-high temperatures. In NSGA-II, the range of the rate constants was considered to ensure the reliability of the optimized mechanism. Moreover, an improved objective function was proposed to maintain the faithfulness of the optimized mechanism to the original reaction mechanism, and a new method was presented to determine the optimal solution from the Pareto front.

Spray behaviors of pure biodiesel and its blend with conventional diesel have been substantially studied in the last decade. However, the studies on the spray behaviors of pure fatty acid methyl esters (FAMEs) are scarce. The primary components of most biodiesel fuels are methyl palmitate (C16:0), methyl stearate (C18:0), methyl oleate (C18:1), methyl linoleate (C18:2) and methyl linolenate (C18:3), and methyl laurate (C12:0) is also the dominant component of some biodiesels. In this study, the spray behaviors of the aforementioned six FAMEs in biodiesel fuels under engine-relevant conditions were numerically studied using the KIVA-3V code. The physical properties needed for spray modeling were predicted with most recently developed property prediction models and added into the fuel library of KIVA-3V. The transient behaviors of liquid penetrations and vaporization characteristics of these FAMEs were numerically studied under various engine-relevant conditions.

It has been recognized that density, viscosity, surface tension, and volatility of liquid fuel are of great importance on the atomization and vaporization characteristics of biodiesel spray. This paper presents a comprehensive physical property prediction of biodiesel fuel for spray modeling with most recently developed property prediction models. The temperature-dependent properties of a soy methyl ester (SME) biodiesel were well predicted by the updated prediction methods. Then, the physical properties of the SME biodiesel were added into the KIVA-3V fuel library. By using the well predicted fuel properties, the spray behaviors of SME were successfully simulated by the KIVA-3V code under late-cycle post-injection, conventional diesel injection, and early-injection engine-relevant conditions. The simulation results agree reasonably well with the available experimental liquid penetrations under conditions of various ambient densities and temperatures.