• Energy Research

With the aim of identifying technical solutions to lower the particulate matter emissions, the engine research community made a consistent effort to investigate the root causes leading to soot formation. Nowadays, the computational power increase allows the use of advanced soot emissions models in 3D-CFD turbulent reacting flows simulations. However, the adaptation of soot models originally developed for Diesel applications to gasoline direct injection engines is still an ongoing process. A limited number of studies in literature attempted to model soot produced by gasoline direct injection engines, obtaining a qualitative agreement with the experiments. To the authors' best knowledge, none of the previous studies provided a methodology to quantitatively match particulate matter, particulate number and particle size distribution function measured at the exhaust without a case-by-case soot model tuning. In the present study, a Sectional Method-based methodology to quantitatively predict gasoline direct injection soot formation is presented and validated against engine-out emissions measured on a single-cylinder optically accessible gasoline direct injection research engine. While adapting the model to the gasoline direct injection soot framework, attention is devoted to modelling the dependence of the processes involved in soot formation on soot precursors chemistry. A well-validated chemical kinetics mechanism is chosen to accurately predict soot precursors formation pathways retaining an accurate description of the main oxidation pathways for oxygenated fuel surrogates. To account for the prominent premixed combustion mode characterizing modern GDI units, a constant pressure reactor library is generated containing the rates for the chemistry-based processes involved in soot formation and evolution at engine-like conditions. The proposed methodology is successfully applied to a 3D computational fluid dynamics model of the engine to predict soot engine-out emissions at the exhaust.

In the maritime transportation, e-fuels represent a valid alternative to fossil energy sour- ces, in order to accomplish the European Union goals in terms of climate neutrality. Among the e-fuels, the ammonia-hydrogen mixtures can play a leading role, as the combination of the two allows to exploit the advantages of each one, simultaneously compensating their gaps. The main goal of the present publication is the proposal of a robust numerical frame- work based on 0D, 1D and 3D tools for CFD analyses of internal combustion engines fueled with ammonia-hydrogen mixtures. The 1D engine model provides boundary conditions for the multi-dimensional in- vestigations and estimates the overall engine performance. 3D in-cylinder detailed ana- lyses are proficiently used to predict combustion efficiency (via the well-established G-equation model supported by laminar flame speed correlations for both ammonia and hydrogen) and emissions (with a detailed chemistry based approach). Heat transfer and knock tendency are evaluated as well, by in-house developed models. As for the 0D/1D chemical kinetics calculations, firstly they support 3D analyses (for example via the gen- eration of ignition delay time tables). Moreover, they allow insights on aspects such as NOx formation, to individuate mixture qualities able to strongly reduce the emissions.

Abstract Several environment agencies worldwide have identified biofuels as a viable solution to meet the stringent targets imposed by future regulations in terms of on-road transport emissions. In the last decades, petroleum-based gasoline has been increasingly blended with oxygenated fuels, mostly ethanol. Blending ethanol with gasoline has two major effects: an increase of the octane number, thus promoting new scenarios for engine efficiency optimization, and a potential reduction of soot emissions. 3D-CFD simulations represent a powerful tool to optimize the use of ethanol-gasoline blends in internal combustion engines. Since most of the combustion models implemented in 3D-CFD codes are based on the “flamelet assumption”, they require laminar flame speed as an input. Therefore, a thorough understanding of the gasoline-ethanol blend chemical behavior at engine-relevant conditions is crucial. While several laminar flame speed correlations are available in literature for both gasoline and pure ethanol at ambient conditions, none is available, to the extent of authors’ knowledge, to describe laminar flame speed of gasoline-ethanol blends (for different ethanol volume contents) at engine relevant conditions. For this reason, in the present work, laminar flame speed correlations based on 1D detailed chemical kinetics calculations are derived targeting typical full-load engine-like conditions, for different ethanol-gasoline blends. A methodology providing a surrogate able to match crucial properties of a fuel is presented at first and validated against available experimental data. Then, laminar flame speed correlations obtained from 1D chemical kinetics simulations are proposed for each fuel blend surrogate.