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In this work a detailed model to simulate the transient behavior of catalytic converters is presented. The model is able to predict the unsteady and reacting flows in the exhaust ducts, by solving the system of conservation equations of mass, momentum, energy and transport of reacting chemical species. The en-gine and the intake system have not been included in the simulation, imposing the measured values of mass flow, gas temperature and chemical composition as a boundary condition at the inlet of the exhaust system. A detailed analysis of the diffusion stage triggering is proposed along with simplifications of the physics, finalized to the reduction of the calculation time. Submodels for water condensation and its following evaporation on the monolith surface have been taken into account as well as oxygen storage promoted by ceria oxides.

The continuous pursuit of higher combustion efficiencies, as well as the possible usage of synthetic fuels with different properties than fossil-ones, require reliable and low-cost numerical approaches to support and speed-up engines industrial design. In this context, SI engines operated with homogeneous ultra-lean mixtures both characterized by a classical ignition configuration or equipped with an active prechamber represent the most promising solutions. In this work, for the classical ignition arrangement, a 3DCFD strategy to model the impact of the ignition system type on the CCV is developed using the RANS approach for turbulence modelling. The spark-discharge is modelled through a set of Lagrangian particles, whose velocity is modified with a zero-divergence perturbation at each discharge event, then evolved according to the Simplified Langevin Model (SLM) to simulate stochastic interactions with the surrounding gas flow.

Active prechamber combustion systems for SI engines represent a feasible and effective solution in reducing fuel consumption and pollutant emissions for both marine and ground heavy-duty engines. However, reliable and low-cost numerical approaches need to be developed to support and speed-up their industrial design considering their geometry complexity and the involved multiple flow length scales. This work presents a CFD methodology based on the RANS approach for the simulation of active prechamber spark-ignition engines. To reduce the computational time, the gas exchange process is computed only in the prechamber region to correctly describe the flow and mixture distributions, while the whole cylinder geometry is considered only for the power-cycle (compression, combustion and expansion). Outside the prechamber the in-cylinder flow field at IVC is estimated from the measured swirl ratio.

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.

A correct prediction of the initial stages of the combustion process in SI engines is of great importance to understand how local flow conditions, fuel properties, mixture stratification and ignition affect the in-cylinder pressure development and pollutant formation. However, flame kernel growth is governed by many interacting processes including energy transfer from the electrical circuit to the gas phase, interaction between the plasma channel and the flow field, transition between different combustion regimes and gas expansion at very high temperatures. In this work, the authors intend to present a comprehensive, multi-dimensional model that can be used to predict the initial combustion stages in SI engines. In particular, the spark channel is represented by a set of Lagrangian particles where each one of them acts as a single flame kernel.

Nowadays a great attention is paid to the level and quality of noise radiated from the tailpipe end of intake and exhaust systems, to control the gas dynamic noise emitted by the engine as well as the characteristics of the cabin interior sound. The muffler geometry can be optimized consequently, to attenuate or remark certain spectral components of the engine noise, according to the result expected. Evidently the design of complex silencing systems is a time-consuming operation, which must be carried out by means of concurrent experimental measurements and numerical simulations. In particular, 1D and multiD linear/non-linear simulation codes can be applied to predict the silencer behavior in the time and frequency domain. This paper describes the development of a 1D-multiD integrated approach for the simulation of complex muffler configurations such as reverse chambers with inlet and outlet pipe extensions and perforated silencers with the addition of sound absorbing material.

The present work describes the numerical modeling of medium-speed marine engines, operating in a fumigated dual-fuel mode, i.e. with the second fuel injected in the ports. This engine technology allows reducing engine-out emissions while maintaining the engine efficiency and can be fairly easily retrofitted from current diesel engines. The main premixed fuel that is added can be a low-carbon one and can additionally be of a renewable nature, thereby reducing or even completely removing the global warming impact. To fully optimize the operational parameters of such a large marine engine, computational fluid dynamics can be very helpful. Accurately describing the combustion process in such an engine is key, as the prediction of the heat release and the pollutant formation is crucial. Auto-ignition of the diesel fuel needs to be captured, followed by the combustion and flame propagation of the premixed fuel.

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 accurate prediction of pollutant emissions generated by IC engines is a key aspect to guarantee the respect of the emission regulation legislation. This paper describes the approach followed by the authors to achieve a strict numerical coupling of two different 1D modeling tools in a co-simulation environment, aiming at a reliable calculation of engine-out and tailpipe emissions. The main idea is to allow an accurate 1D simulation of the unsteady flows and wave motion inside the intake and exhaust systems, without resorting to an over-simplified geometrical discretization, and to rely on advanced thermodynamic combustion models and kinetic sub-models for the calculation of cylinder-out emissions. A specific fluid dynamic approach is then used to track the chemical composition along the exhaust duct-system, in order to evaluate the conversion efficiency of after-treatment devices, such as TWC, GPF, DPF, DOC, SCR and so on.

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.

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.

Polymer electrolyte membrane (PEM) fuel cells will play a crucial role in the decarbonization of the transport sector, in particular for heavy duty applications. However, performance and durability of PEMFC stacks is still a concern especially when operated under high power density conditions, as required in order to improve the compactness and to reduce the cost of the system. In this context, the optimization of the geometry of hydrogen and air distributors represents a key factor to improve the distribution of the reactants on the active surface, in order to guarantee a proper water management and avoiding membrane dehydration.

Multiple injections and high EGR rates are now widely adopted for combustion and emissions control in passenger car diesel engines. In a wide range of operating conditions, fuel is provided through one to five separated injection events, and recirculated gas fractions between 0 to 30% are used. Within this context, fast and reliable multi-dimensional models are necessary to define suitable injection strategies for different operating points and reduce both the costs and time required for engine design and development. In this work, the authors have applied a modified version of the characteristic time-scale combustion model (CTC) to predict combustion and pollutant emissions in diesel engines using advanced injection strategies. The Shell auto-ignition model is used to predict auto-ignition, with a suitable set of coefficients that were tuned for diesel fuel.

In the rapidly changing scenario of the energy transition, data-driven tools for kinetic mechanism development and testing can greatly support the evaluation of the combustion properties of new potential e-fuels. Despite the effectiveness of kinetic mechanism generation and optimization procedures and the increased availability of experimental data, integrated methodologies combining data analysis, kinetic simulations, chemical lumping, and kinetic mechanism optimization are still lacking. This paper presents an integrated workflow that combines recently developed automated tools for kinetic mechanism development and testing, from data collection to kinetic model reduction and optimization. The proposed methodology is applied to build a consistent, efficient, and well-performing kinetic mechanism for the combustion of oxymethylene ethers (OMEs), which are promising synthetic e-fuels for transportation.

Prediction of in-cylinder flows and fuel-air mixing are two fundamental pre-requisites for a successful simulation of direct-injection engines. Over the years, many efforts were carried out in order to improve available turbulence and spray models. However, enhancements in physical modeling can be drastically affected by how the mesh is structured. Grid quality can negatively influence the prediction of organized charge motion structures, turbulence generation and interaction between in-cylinder flows and injected sprays. This is even more relevant for modern direct injection engines, where multiple injections and control of charge motions are employed in a large portion of the operating map. Currently, two different approaches for mesh generation exist: manual and automatic. The first makes generally possible to generate high-quality meshes but, at the same time, it is very time consuming and not completely free from user errors.

In the last years, as a response to the more and more restrictive emission legislation, new devices (SRC, DOC, NOx-trap, DPF) have been progressively introduced as standard components of modern after-treatment system for Diesel engines. In addition, the adoption of electrical heating is nowadays regarded with interest as an effective solution to promote the light-off of the catalyst at low temperature, especially at the start-up of the engine and during the low load operation of the engine typical of the urban drive. In this work, a state-of-the-art 48 V electrical heated catalyst is considered, in order to investigate its effect in increasing the abatement efficiency of a standard DOC. The electrical heating device considered is based on a metallic support, arranged in a spiral layout, and it is heated by the Joule effect due to the passage of the electrical current.

The increasing diffusion of gasoline direct injection (GDI) engines requires a more detailed and reliable description of the phenomena occurring during the fuel injection process. As well known the thermal and fluid-dynamic conditions present in the combustion chamber greatly influence the air-fuel mixture process deriving from GDI injectors. GDI fuel sprays typically evolve in wide range of ambient pressure and temperatures depending on the engine load. In some particular injection conditions, when in-cylinder pressure is relatively low, flash evaporation might occur significantly affecting the fuel-air mixing process. In some other particular injection conditions spray impingement on the piston wall might occur, causing high unburned hydrocarbons and soot emissions, so currently representing one of the main drawbacks of GDI engines.

Gasoline, direct injection engines represent one of the most widely adopted powertrain for passenger cars. However, further development efforts are necessary to meet the future fuel consumption and emission standards imposing an efficiency increase and a reduction of particulate matter emissions. Within this context, computational fluid dynamics is nowadays a consolidated tool to support engine design; this work is focused on the development of a set of CFD models for the prediction of combustion in modern GDI engines. The one-equation Weller model coupled with a zero-dimensional approach to handle initial flame kernel growth was applied to predict flame propagation. To account for mixture fraction fluctuations which might lead to the presence of soot precursor species, burned gas chemical composition is computed using tabulated kinetics with a presumed probability density function.

Computational fluid dynamics (CFD) modeling has many potentials for the design and calibration of modern and future engine concepts, including facilitating the exploration of operation conditions and casting light on the involved physical and chemical phenomena. As more attention is paid to the matching of different fuel types and combustion strategies, the use of detailed chemistry in characterizing auto-ignition, flame stabilization processes and the formation of pollutant emissions is becoming critical, yet computationally intensive. Therefore, there is much interest in using tabulated approaches to account for detailed chemistry with an affordable computational cost. In the present work, the tabulated flamelet progress variable approach (TFPV), based on flamelet assumptions, was investigated and validated by simulating constant-volume Diesel combustion with primary reference fuels - binary mixtures of n-heptane and iso-octane.

Predictive combustion models are useful tools towards the development of clean and efficient engines operating with alternative fuels. This work intends to validate two different combustion models on compression-ignition engines fueled with Dimethyl Ether. Both approaches give a detailed characterization of the combustion kinetics, but they substantially differ in how the interaction between fluid-dynamics and chemistry is treated. The first one is single-flamelet Representative Interactive Flamelet, which considers turbulence-kinetic interaction but cannot correctly describe the stabilization of the flame. The second, named Tabulated Well Mixed, correctly accounts for local flow and mixture conditions but does not consider interaction between turbulence and chemistry. An experimental campaign was carried out on a heavy-duty truck engine running on DME at a constant load considering trade-off of EGR and SOI.