Monofractal and multifractal analysis of simulated heat release fluctuations in a spark ignition heat engine

We study data from cycle-by-cycle variations in heat release for a simulated spark-ignited engine. Our analyses are based on nonlinear scaling properties of heat release fluctuations obtained from a turbulent combustion model. We apply monofractal and multifractal methods to characterize the fluctuations for several fuel–air ratio values, ϕϕ, from lean mixtures to stoichiometric situations. The monofractal approach reveals that, for lean and stoichiometric conditions, the fluctuations are characterized by the presence of weak anticorrelations, whereas for intermediate mixtures we observe complex dynamics characterized by a crossover in the scaling exponents: for short scales, the variations display positive correlations while for large scales the fluctuations are close to white noise. Moreover, a broad multifractal spectrum is observed for intermediate fuel ratio values, while for low and high ϕϕ the fluctuations lead to a narrow spectrum. Finally, we explore the origin of correlations by using the surrogate data method to compare the findings of multifractality and scaling exponents between original simulated and randomized data.