Università degli studi di Modena e Reggio Emilia

Soot engine-out emissions are no longer a prerogative of Diesel engines. Emission regulations related to Gasoline units aim to curb the soot emissions along with other pollutants. In this scenario, Computational Fluid Dynamics (CFD) is a very promising research and development tool to explore the influence of engine design and operational parameters, as well as of the fuel chemical nature, on the particulate matter formation. Among the soot models, the Sectional Method is an advanced resource to provide information on Particle Number, Particulate Mass and Particle Size Distribution. In this study, the Sectional Method is applied in conjunction with a customized soot library, where the source terms governing the soot sections transport equations are stored. The library is computed via chemical kinetics simulation of a 0D constant pressure reactor, which provides fuel-related coefficients for each individual source term over the entire range of conditions experienced by the 3D-CFD model. 3D-CFD simulations are then carried out for three different injection timings without case-by-case tuning. Numerical results are then compared to the experimental dataset by using a consistent methodology. A satisfactory agreement between 3D-CFD results and experimental measurements is reached for soot mass and particle numbers, while the particle size distribution function is only partially reproduced. Soot-related quantities are thoroughly analyzed for each of the examined injection strategies to understand the mechanisms leading to soot formation and emissions.

In the optimization of GDI engines, fuel injection plays a crucial role since it can affect the combustion process and, thus, fuel efficiency and pollutant emissions. The challenging task is to obtain the required fuel distribution and atomization inside the combustion chamber over a wide range of engine operating conditions. To achieve such goals, flash-boiling can be exploited. Flash-boiling is a phenomenon occurring when fuel temperature exceeds saturation temperature or, similarly, when ambient pressure is lower than saturation one. Under these conditions, which can occur inside the injector or directly in the combustion chamber, the fuel undergoes extremely accelerated breakup and quickly evaporates. The proposed manuscript shows the application of an alternative flashboiling model, recently implemented by Siemens-PLM in STAR-CD V.2019.1, to be applied in 3D-CFD Lagrangian simulations of GDI sprays. Results are validated against experimental data, provided by the SprayLAB of the University of Perugia, on a single-hole research injector. The new flash-boiling model consists of three main parts: an atomization model able to compute droplet initial conditions and the overall spray cone angle; an evaporation model and, finally, a droplet break-up model; the last two models are designed to simulate all the physical events occurring when droplets are injected into the combustion chamber. As for the investigated operating condition, vessel pressure and temperature are 40 kPa and 293K, respectively; as for the fuel (n-Heptane) temperature, it ranges from 303.15 K to 393.15 K, on equal injection pressure (10 MPa). The numerical-experimental comparison is carried out in terms of liquid penetration, imaging, and droplet sizing.

The statistical tendency of a GDI spark-ignition engine to undergo knocking combustion as a consequence of spark timing variation is numerically investigated. In particular, attention is focused on the importance to match combustion-relevant and knock-relevant fuel properties to ensure consistency with the experimental evidence. An inhouse surrogate formulation methodology is used to emulate real gasoline properties, comparing fuel models of increasing complexity. Knock is investigated using a proprietary statistical knock model (GruMo Knock Model, GK-PDF). The model can infer a log-normal distribution of knock intensity within a RANS formalism, by means of transport equations for variances and turbulence-derived probability density functions (PDFs) for physical quantities. The calculated distributions are compared to measured statistical distributions. The proposed numerical/experimental comparison constitutes an advancement in synthetic chemistry integration into 3D-CFD combustion simulations.

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.

Fuel injectors featuring differentiated hole-to-hole dimensions improve the fuel distribution in the cylinder ensuring a more efficient and cleaner combustion for GDI (Gasoline Direct Injection) engines. A proper diagnostic system able to detect the actual fuel flow rate exiting each hole of a GDI nozzle is requested in order to optimize the matching between the spray and the combustion chamber. Measuring the spray impact force of a single plume allows the detection of the momentum flux exiting the single hole and, under appropriate hypotheses, the evaluation of the corresponding mass flow rate time-profile. In this paper two methodologies for the hole-specific flow rate evaluation, both based on the spray momentum technique, were applied to two different GDI nozzles, one featuring equal hole dimensions and one with two larger holes. Three different energizing times at 100 bar of fuel pressure were tested in order to cover a wide range of operating conditions. The results were validated in terms of injected mass by means of a proper device able to collect and weigh the fuel injected by each single nozzle hole, and in terms of mass flow rate using a Zeuch-method flow meter as reference. Both the proposed methodologies showed an excellent accuracy in the fuel amount detection with percentage error lower than 5% for standard energizing times and lower than 10% for very short injections working in ballistic conditions. The mass flow rate time-profile proved a good accuracy in the detection of the start and end of injection and the static flow rate level.

The scientific literature focusing on the numerical simulation of fuel sprays is plenty of atomization and secondary break-up models, all aiming at simulating GDI sprays under possibly any engine condition in terms of injection pressure and cylinder back pressure. However, it is well known that the predictive capabilities of even the most diffused break-up models are affected by injection parameters, especially backpressure. As a consequence, model constants require usually substantial tuning based on the specific operating conditions. In this manuscript, an alternative atomization methodology is proposed for the 3D-CFD simulation of GDI sprays, aiming at reducing case-to-case tuning of the model constants for variations of the operating conditions. In particular, attention is focused on the effects of back pressure, which has a huge impact on both the morphology and the sizing of GDI sprays. 3D-CFD Lagrangian simulations of two different multi-hole GDI injectors are presented. The first injector is a 5-hole GDI prototype unit operated at ambient conditions. The second one is the well-known Spray G, characterized by a higher back pressure (up to 0.6 MPa). Results are compared against experimental data in terms of liquid penetration, PDA (Phase Doppler Anemometry) data of droplet sizing / velocity and imaging. CFD results are demonstrated to be highly sensitive to the spray vessel pressure, mainly because of the atomization strategy. The proposed alternative approach proves to strongly reduce such dependency. To confirm the improvements, such approach is combined to two different well-known secondary break-up models, namely Reitz's model and the KHRT one.

The scientific literature focusing on the numerical simulation of fuel sprays is rich in atomization and secondary break-up models. However, it is well known that the predictive capability of even the most diused models is aected by the combination of injection parameters and operating conditions, especially backpressure. In this paper, an alternative atomization strategy is proposed for the 3D-Computational Fluid Dynamics (CFD) simulation of Gasoline Direct Injection (GDI) sprays, aiming at extending simulation predictive capabilities over a wider range of operating conditions. In particular, attention is focused on the eects of back pressure, which has a remarkable impact on both the morphology and the sizing of GDI sprays. 3D-CFD Lagrangian simulations of two dierent multi-hole injectors are presented. The first injector is a 5-hole GDI prototype unit operated at ambient conditions. The second one is the well-known Spray G, characterized by a higher back pressure (up to 0.6 MPa). Numerical results are compared against experiments in terms of liquid penetration and Phase Doppler Anemometry (PDA) data of droplet sizing/velocity and imaging. CFD results are demonstrated to be highly sensitive to spray vessel pressure, mainly because of the atomization strategy. The proposed alternative approach proves to strongly reduce such dependency. Moreover, in order to further validate the alternative primary break-up strategy adopted for the initialization of the droplets, an internal nozzle flow simulation is carried out on the Spray G injector, able to provide information on the characteristic diameter of the liquid column exiting from the nozzle.

Heat Transfer plays a fundamental role in internal combustion engines, as able to affect several aspects, such as efficiency, emissions and reliability. As for this last, a proper heat transfer prediction is mandatory for the estimation of the engine temperatures at peak power condition, it being the most critical one from a thermal point of view. At part-load/low revving speed operations, heat transfer is detrimental for the engine efficiency, deeply reducing indicated work of the burnt gases on the piston. Focusing on the in-cylinder domain, 3D-CFD simulations represent an irreplaceable tool for the estimation of gas-to-wall heat fluxes. Several models have been developed in the past, aiming at providing a reliable estimation of the heat transfer at any condition in terms of load and revving speed. To save computational cost and time, the most diffused wall approach for the numerical simulation of confined reacting flows is the high-Reynolds one, which means that heat transfer model is based on a thermal wall function. Unfortunately, wall functions (logarithmic profiles of the inertial layer) can be claimed only at restricted conditions, such as isothermal steady-state flow, velocity parallel to the wall and negligible pressure gradient. In practice, none of these assumptions is valid for industrial applications such as an in-cylinder simulation. Therefore in these cases, as demonstrated by different works in the past, wall functions do not exist and their adoption leads to a non-negligible error in the estimation of the heat transfer. The main goal of this work is to build up a methodology able to investigate the presence of wall functions in actual industrial applications, in particular in 3D-CFD in-cylinder analyses. Compared to previous works available in literature, where DNS or LES are carried out on simplified geometries and/or at low revving speed conditions because of the computational cost, in the present paper a RANS approach to turbulence and a low-Reynolds wall treatment are adopted. Moreover, a new strategy to obtain dimensionless profiles of velocity and temperature from computed fields is introduced. At first, the proposed methodology is validated on a 2D plane channel. Then, a preliminary application on a research engine, namely the GM Pancake engine, is proposed, showing that dimensionless profiles of velocity and temperature calculated on the combustion chamber walls are remarkably different from standard analytical wall functions.

Findings from the International Agency for Research on Cancer (IARC) classified particulate matter (PM) as carcinogenic to humans. While being a promising solution to reduce greenhouse gases (GHG) emissions and increase engine fuel economy, Gasoline Direct Injected (GDI) engines produce a number of particles (PN) of fine size higher than Port Fuel Injected (PFI) ones. As a consequence, the EU commission significantly tightened the emission standards for passenger cars, following which all gasoline engines will have to meet the euro-6d regulation coming into force in 2020. Efforts are made by the research community to understand the root causes leading to soot formation and possibly identify technical solutions to lower it. An important piece of the puzzle is the investigation of soot formation via 3D-CFD. To this aim, relevant efforts have been and are still being paid to adapt soot emissions models, originally developed for Diesel combustion, for GDI units. Among the many available models, one of the most advanced is the so-called Sectional Method. So far, studies presented in literature were not able to formulate a methodology to quantitatively match experimental PM, PN and PSDF without a dedicated soot model tuning. In the present work, a Sectional Method-based methodology to quantitatively predict GDI soot is presented and validated against PM, PN and PSDF measurements on a optically accessible GDI research unit. While adapting the model to GDI soot, attention is devoted to the modelling of soot precursor chemistry: a customized version of a pre-existing chemical kinetics mechanism, used to predict the formation of the key PAH (Polycyclic Aromatic Hydrocarbons) species, is presented and validated via 1D numerical simulations on a premixed flat flame burner dataset available in literature. The present work demonstrates that a Sectional Method-based approach can be a powerful tool to quantitatively predict engine-out soot emissions.