Abstract

The simulation of heat release, flame propagation speeds, and pollutant formation was carried out in both a turbocharged compressed natural gas (CNG) engine and a multivalve naturally aspirated bifuel engine running on either CNG or gasoline. The predictive tool used for investigation is based on an enhanced fractal geometry concept of the flame front, which is able to capture the modulation of turbulent to laminar burning speed ratio throughout the overall combustion phase without introducing flame kernel growth or burnout submodels. The prediction model was applied to a wide range of engine speeds, loads, relative air-fuel ratios, and spark advances, and the obtained results were compared to experimental data. These latter were extracted from measured in-cylinder pressure by an advanced diagnostics technique that was previously developed by the authors. The results confirmed a quite accurate prediction of burning speed even without any kind of tuning, with respect to different currently available fractal as well as nonfractal approaches for the simulation of flame-turbulence interaction. Furthermore, the computational code proved to be capable of capturing the effects of fuel composition, different combustion-chamber concepts, and operating conditions on engine performance and emissions.

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