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The flow performance of intake port significantly affects engine output power, fuel economy, and exhaust emissions in gasoline engines. Thus, optimal intake port geometry is desired in gasoline engines. To optimize the flow performance of intake port, a new optimization method combining genetic algorithm (GA) and artificial neural network (ANN) was proposed. First, an automatic system for generating the geometry of the tangential intake port was constructed to create various port geometries through inputting the 18 pre-defined structural parameters. Then, the effects of four critical structural parameters were investigated through numerical simulation. On the basis of the computational results, an ANN was used to model the flow performance of the intake port, and a genetic algorithm was simultaneously employed to optimize the flow performance by optimizing the four important structural parameters. Finally, the optimization results were verified through numerical simulation.

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.

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.