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Advanced numerical techniques, such as fuzzy logic and neural networks have been applied in this work to digital images acquired on a mono-component fuel spray (iso-octane), in order to define, in a stochastic way, the gas-liquid interface evolution. The image is a numerical matrix and so it is possible to characterize geometrical parameters and the time evolution of the jet by using deterministic, statistical stochastic and other several kinds of approach. The algorithm used works with the fuzzy logic concept to binarize the shades gray of the pixel, depending them, by using the schlieren technique, on the gas density. Starting from a primary fixed threshold, the applied technique, can select the ‘gas’ pixel from the ‘liquid’ pixel and so it is possible define the first most probably boundary lines of the spray.

Ultra-high injection pressures, as well as flash-boiling occurrence, are among the most important research fields recently explored for improving Gasoline Direct Injection (GDI) engine performance. Both of them play a key role in the enhancement of the air/fuel mixing process, in the reduction of tailpipe pollutant emissions, as well as in the investigation of new combustion concepts. Injector manufacturers are even more producing devices with ultra-high injection pressures capable of working with flashing sprays. Flash-boiling of fuel sprays occurs when a super-heated fuel is discharged into an environment whose pressure is lower than the saturation pressure of the fuel and can dramatically alter spray formation due to complex two-phase flow effects and rapid droplet vaporization. In GDI engines, typically, it occurs during the injection process when high fuel temperatures make its saturation pressures higher than the in-cylinder one.