The simulation of heat release, flame propagation speeds and pollutant formation was carried out in both a turbocharged CNG engine and a multivalve naturally-aspirated bi-fuel 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 burn out sub-models. The fractal approach is coupled to a simple refined quasi-dimensional multizone combustion model, which includes specifically developed sub-models for evaluating CO and NO formation, in addition to a CAD procedure to determine the burned-gas front area and radius, as is detaild in [16]. An insight is also given into main features of in-cylinder turbulence modeling, as an easy and effective evaluation of the turbulence intensity is needed for an accurate computation of the turbulent burning speed. The predictive model was applied to a wide range of engine speeds (N = 2000–5500 rpm), loads (bmep = 200–790 kPa for the naturally-aspirated engine, bmep = 200–1400 kPa for the turbocharged one), relative air-fuel ratios (RAFR = 0.80–1.60) and spark advances (SA ranging from 8 deg of retard to 8 deg of advance from MBT), 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 non-fractal approaches for the simulation of flame-turbulence interaction. Furthermore, the authors’ computational code showed 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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