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Modeling combustion of transportation fuels remains a difficult task due to the extremely large number of species constituting commercial gasoline and diesel. However, for this purpose, multi-component surrogate fuel models with a reduced number of key species and dedicated reaction subsets can be used to reproduce the physical and chemical traits of diesel and gasoline, also allowing to perform CFD calculations. Recently, a detailed surrogate fuel kinetic model, named C3 mechanism, was developed by merging high-fidelity sub-mechanisms from different research groups, i.e. C0-C4 chemistry (NUI Galway), linear C6-C7 and iso-octane chemistry (Lawrence Livermore National Laboratory), and monocyclic aromatic hydrocarbons (MAHs) and polycyclic aromatic hydrocarbons (PAHs) (ITV-RWTH Aachen and CRECK modelling Lab-Politecnico di Milano).

In recent years, the increase of gasoline fuel injection pressure is a way to improve thermal efficiency and lower engine-out emissions in GDI homogenous combustion concept. The challenge of controlling particulate formation as well in mass and number concentrations imposed by emissions regulations can be pursued improving the mixture preparation process and avoiding mixture inhomogeneity with ultra-high injection pressure values up to 100 MPa. The increase of the fuel injection pressure in GDI homogeneous systems meets the demand for increased injector static flow, while simultaneously improves the spray atomization and mixing characteristics with consequent better combustion performance. Few studies quantify the effects of high injection pressure on transient gasoline spray evolution. The aim of this work was to simulate with OpenFOAM the spray morphology of a commercial gasoline injected in a constant volume vessel by a prototypal GDI injector.

The modeling of fuel sprays under well-characterized conditions relevant for heavy-duty Diesel engine applications, allows for detailed analyses of individual phenomena aimed at improving emission formation and fuel consumption. However, the complexity of a reacting fuel spray under heavy-duty conditions currently prohibits direct simulation. Using a systematic approach, we extrapolate available spray models to the desired conditions without inclusion of chemical reactions. For validation, experimental techniques are utilized to characterize inert sprays of n-dodecane in a high-pressure, high-temperature (900 K) constant volume vessel with full optical access. The liquid fuel spray is studied using high-speed diffused back-illumination for conditions with different densities (22.8 and 40 kg/m3) and injection pressures (150, 80 and 160 MPa), using a 0.205-mm orifice diameter nozzle.

The paper deals with the design and manufacturing of a McPherson suspension arm made from short glass fiber reinforced polyamide (PA66). The design of the arm and the design of the molds have been made jointly. According to Industry 4.0 paradigms, a full digitalization of both the product and process has been performed. Since the mechanical behavior of the suspension arm strongly depends on constraints which are difficult to be modelled, a simpler structure with well-defined mechanical constraints has been developed. By means of such simple structure, the model for the behavior of the material has been validated. Since the suspension arm is a hybrid structure, the associated simple structure is hybrid as well, featuring a metal sheet with over-molded polymer. The issues referring to material flow, material to material contact, weld lines, fatigue strength, high and low temperature behavior, creep, dynamic strength have been investigated on the simple structure.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

The flow field resulting from injecting a gas jet into a crossflow confined in a narrow square duct has been studied under steady regime using schlieren imaging and laser Doppler velocimetry (LDV). This transparent duct is intended to simulate the intake port of an internal combustion engine fueled by gaseous mixture, and the jet is issued from a round nozzle. The schlieren images show that the relative small size of the duct would confine the development of the transverse jet, and the interaction among jet and sidewalls strongly influences the mixing process between jet and crossflow. The mean velocity and turbulence fields have been studied in detail through LDV measurements, at both center plane and several cross sections. The well-known flow feature formed by a counter rotating vortex pair (CVP) has been observed, which starts to appear at the jet exit section and persists far downstream contributing to enhancing mixing process.

This paper is focused on the development and application of a CFD methodology that can be applied to predict the fuel-air mixing process in stratified charge, sparkignition engines. The Eulerian-Lagrangian approach was used to model the spray evolution together with a liquid film model that properly takes into account its effects on the fuel-air mixing process into account. However, numerical simulation of stratified combustion in SI engines is a very challenging task for CFD modeling, due to the complex interaction of different physical phenomena involving turbulent, reacting and multiphase flows evolving inside a moving geometry. Hence, for a proper assessment of the different sub-models involved a detailed set of experimental optical data is required. To this end, a large experimental database was built by the authors.

In the paper some methods are presented, with the corresponding practical examples, related to MonteCarlo (MC) techniques for thermal model/test correlation purposes. The MonteCarlo techniques applied to model correlation are intended to be used as an alternative to empirical ‘manual’ correlation techniques, gradients methods, matrix methods based on least square fit minimization. First of all, Design Of Experiments (DoE) tools are used to determine the model response to uncertain parameters and the confidence level of such a response. A sensitivity map is built, allowing the design of the test to maximize the response of the system to the uncertain parameters. Techniques derived from the extreme statistics are used to extrapolate data beyond test limits, with a sufficient confidence in the queue behaviour.

The sustainability of Martian outposts development is strongly based on the capability of achieving a high level of autonomy both in terms of operations management and of resources availability. In situ production of consumables is a key point to allow humans to work and live on Mars avoiding or limiting the need for re-supplies of materials from Earth. Required consumables can be produced in situ exploiting the locally available resources, but also by means of green-houses and waste recycle systems. Dedicated robotic missions for in situ demonstration of this type of technologies are a fundamental step of the Martian In Situ Resources Utilization (ISRU) development roadmap. This paper is focused on the extraction of oxygen and fuels (e.g. methane) from the Martian atmosphere, and presents a feasibility study for a small technological demonstration plant.

A three dimensional numerical simulation of the ECN “Spray A” is presented. Both primary and secondary breakup of the spray are included. The fuel is n-Dodecane. The n-Dodecane kinetic mechanism is modeled using a skeletal mechanism that consists of 103 species and 370 reactions [9]. The kinetic mechanism is computationally heavy when coupled with three dimensional numerical simulations. Multidimensional chemistry coordinate mapping (CCM) approach is used to speedup the simulation. CCM involves two-way mapping between CFD cells and a discretized multidimensional thermodynamic space, the so called multidimensional chemistry coordinate space. In the text, the cells in the discretized multidimensional thermodynamic space are called zone to discriminate them from the CFD cells. In this way, the CFD cells which are at the similar thermodynamic state are identified and grouped into a unique zone. The stiff ODEs operates only on the zones containing at least one CFD cell.

The effects of biodiesel oxidation stability on diesel fuel injection equipment (FIE) behavior were investigated using newly developed test rig and methodology. On the test rig, biodiesel blend fuels were circulated through a fuel tank and a common rail injection system. Fuel injected from typical diesel injectors was returned into the fuel tank to enhance the speed of fuel degradation. The results showed that injector deposits could be reproduced on a test rig. It was observed that injector body temperature increase accelerates the degradation of fuel and therefore gives earlier FIE failure. Fuel renewal could partially restore the injection quantity after complete failure at low injection pressure, thus showing a potential cleaning effect on injector deposits when refueling a car.

A set of additives was selected to improve the durability of the physical-chemical and biological characteristics of mineral diesel and its blend with biodiesel. Two biodiesels were used: soybean (SME) and rapeseed (RME). Both physical-chemical properties and fuel dispersion of fuel blends and their mixtures with additives were measured that could have effects on the combustion process in diesel engines. The dispersion of the fuel is affected by the injection nozzle integrity, influencing the capacity of the fuel to vaporize, while the modification of the fuel molecular structure can cause changes in combustion reaction. A 7 hole Common Rail (CR) 2nd generation injector, 136 μm in diameter, was used at 80 MPa and 1.0 ms injection pressure and duration, respectively. The injection rate was determined using the Bosch's Method, while the fuel dispersion was measured by analyzing the images of spray evolving in an optical accessible quiescent vessel.

Highway and roadway surface measurement is a practice that has been ongoing for decades now. This sort of measurement is intended to ensure a safe level of road perturbances. The measurement may be conducted by a slow moving apparatus directly measuring the elevation of the road, at varying distance intervals, to obtain a road profile, with varying degrees of resolution. An alternate means is to measure the surface roughness at highway speeds using accelerometers coupled with high speed distance measurements, such as laser sensors. Vehicles out rigged with such a system are termed inertial profilers. This type of inertial measurement provides a sort of filtered roadway profile. Much research has been conducted on the analysis of highway roughness, and the associated metrics involved. In many instances, it is desirable to maintain an off-road course such that the course will provide sufficient challenges to a vehicle during durability testing.

The air entrainment in a transient diesel spray was studied using laser Doppler anemometry to provide information on the effect of gas density and temperature. The spray was injected vertically into a confined quiescent atmosphere and the entrained mass flow rate was evaluated by measuring the air velocity component normal to a cylindrical geometric surface surrounding the spray, and extending to about 200 nozzle diameters (50 mm). The experimental results, relative to a density range from 0.84 to 7.02 kg/m3 and a temperature range from 293 to 473 K, indicate that the non dimensional entrainment rate, averaged in time over the main injection period, depends on the distance from the nozzle and both gas density and temperature. A first analysis, based on the available data, allowed to quantify the dependence and provided a correlation with such variables.

In the recent years, the interest in heavy-duty engines fueled with Compressed Natural Gas (CNG) is increasing due to the necessity to comply with the stringent CO2 limitation imposed by national and international regulations. Indeed, the reduced number of carbon atoms of the NG molecule allows to reduce the CO2 emissions compared to a conventional fuel. The possibility to produce synthetic methane from renewable energy sources, or bio-methane from agricultural biomass and/or animal waste, contributes to support the switch from conventional liquid fuels to CNG. To drive the engine development and reduce the time-to-market, the employment of numerical analysis is mandatory. This requires a continuous improvement of the simulation models toward real predictive analyses able to reduce the experimental R&D efforts. In this framework, 1D numerical codes are fundamental tools for system design, energy management optimization, and so on.

Dimethyl ether (DME) represents a promising fuel for heavy-duty engines thanks to its high cetane number, volatility, absence of aromatics, reduced tank-to-wheel CO2 emissions compared to Diesel fuel and the possibility to be produced from renewable energy sources. However, optimization of compression-ignition engines fueled with DME requires suitable computational tools to design dedicated injection and combustion systems: reduced injection pressures and increased nozzle diameters are expected compared to conventional Diesel engines, which influences both the air-fuel mixing and the combustion process. This work intends to evaluate the validity of two different combustion models for the prediction of performance and pollutant emissions in compression-ignition engines operating with DME. The first one is the Representative Interactive Flamelet while the second is the Approximated Diffusive Flamelet.

This work has the objective to present the extension of a novel quasi-dimensional model, developed to simulate the combustion process in diesel Compression Ignition (CI) engines, to describe this process when Dimethyl ether (DME) is used as fuel. DME is a promising fuel in heavy-duty CI engines application thanks to its high Cetane Number (CN), volatility, high reactivity, almost smokeless combustion, lower CO2 emission and the possibility to be produced with renewable energy sources. In this paper, a brief description of the thermodynamic model will be presented, with particular attention to the implementation of the Tabulated Kinetic Ignition (TKI) model, and how the various models interact to simulate the combustion process. The model has been validated against experimental data derived from constant-volume DME combustion, in this case the most important parameters analyzed and compared were the Ignition Delay (ID) and Flame Lift Off Length (FLOL).

The effects of fuel temperature on both the geometry and the droplet size and velocity of a GDI swirled injector spray were investigated by means of visualizations and PDA measurements. Isooctane was used as model fuel and was injected in a quiescent bomb at injection pressure of 7 MPa. Bomb pressure ranged from 40 kPa to 800 kPa with injector nozzle temperature ranging from 293 K to 393 K. A drastic change in spray geometry was observed when conditions above the vaporization curve were reached. The temperature increase has two macroscopic effects on the spray geometry: at the nozzle exit the liquid flash boiling strongly enlarges the spray angle, at a certain distance from the nozzle the air entrainment collapses the spray. Raising the fuel temperature up to flash boiling conditions causes a significant decrease of the average droplet size.

We present a framework for the robust optimization of the heat flux distribution for an anti-ice electro-thermal ice protection system (AI-ETIPS) and iced airfoil performance analysis under uncertain conditions. The considered uncertainty regards a lack of knowledge concerning the characteristics of the cloud i.e. the liquid water content and the median volume diameter of water droplets, and the accuracy of measuring devices i.e., the static temperature probe, uncertain parameters are modeled as uniform random variables. A forward uncertainty propagation analysis is carried out using a Monte Carlo approach. The optimization framework relies on a gradient-free algorithm (Mesh Adaptive Direct Search) and three different problem formulations are considered in this work. Two bi-objective deterministic optimizations aim to minimize power consumption and either minimize ice formations or the iced airfoil drag coefficient.

The relationship between ethanol and iso-butanol fuel concentrations and vehicle particulate matter emissions was investigated. This study utilized a gasoline direct injection (GDI) flexible fuel vehicle (FFV) with wall-guided fueling system tested with four fuels, including E10, E51, E83, and an iso-butanol blend at a proportion of 55% by volume. Emission measurements were conducted over the Federal Test Procedure (FTP) driving cycle on a chassis dynamometer with an emphasis on the physical and chemical characterization of particulate matter (PM) emissions. The results indicated that the addition of higher ethanol blends and the iso-butanol blend resulted in large reductions in PM mass, soot, and total and solid particle number emissions. PM emissions for the baseline E10 fuel were characterized by a higher fraction of elemental carbon (EC), whereas the PM emissions for the higher ethanol blends were more organic carbon (OC) in nature.