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Detailed and fast combustion models are necessary to support design of Diesel engines with low emission and fuel consumption. Over the years, the importance of turbulence chemistry interaction to correctly describe the diffusion flame structure was demonstrated by a detailed assessment with optical data from constant-volume vessel experiments. The main objective of this work is to carry out an extensive validation of two different combustion models which are suitable for the simulation of Diesel engine combustion. The first one is the Representative Interactive Flamelet model (RIF) employing direct chemistry integration. A single flamelet formulation is generally used to reduce the computational time but this aspect limits the capability to reproduce the flame stabilization process. To overcome such limitation, a second model called tabulated flamelet progress variable (TFPV) is tested in this work.

Detailed chemistry represents a fundamental pre-requisite for a realistic simulation of combustion process in Diesel engines to properly reproduce ignition delay and flame structure (lift-off and soot precursors) in a wide range of operating conditions. In this work, the authors developed reduced mechanisms for n-dodecane starting from the comprehensive kinetic mechanism developed at Politecnico di Milano, well validated and tested in a wide range of operating conditions [1]. An algorithm combining Sensitivity and Flux Analysis was employed for the present skeletal reduction. The size of the mechanisms can be limited to less than 100 species and incorporates the most important details of low-temperature kinetics for a proper prediction of the ignition delay. Furthermore, the high-temperature chemistry is also properly described both in terms of reactivity and species formation, including unsaturated compounds such as acetylene, whose concentration controls soot formation.

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.

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.

Premixed combustion modes in compression ignition engines are studied as a promising solution to meet fuel economy and increasingly stringent emissions regulations. Nevertheless, PCCI combustion systems are not yet consolidated enough for practical applications. The high complexity of such combustion systems in terms of both air-fuel charge preparation and combustion process control requires the employment of robust and reliable numerical tools to provide adequate comprehension of the phenomena. Object of this work is the development and validation of suitable models to evaluate the effects of charge premixing levels in diesel combustion. This activity was performed using the Lib-ICE code, which is a set of applications and libraries for IC engine simulations developed using the OpenFOAM® technology.

Many new combustion concepts are currently being investigated to further improve engines in terms of both efficiency and emissions. Examples include homogeneous charge compression ignition (HCCI), lean stratified premixed combustion, stratified charge compression ignition (SCCI), and high levels of exhaust gas recirculation (EGR) in diesel engines, known as low temperature combustion (LTC). All of these combustion concepts have in common that the temperatures are lower than in traditional spark ignition or diesel engines. To further improve and develop combustion concepts for clean and highly efficient engines, it is necessary to develop new computational tools that can be used to describe and optimize processes in nonstandard conditions, such as low temperature combustion.

Nowadays, detailed kinetics is necessary for a proper estimation of both flame structure and pollutant formation in compression ignition engines. However, large mechanisms and the need to include turbulence/chemistry interaction introduce significant computational overheads. For this reason, tabulated kinetics is employed as a possible solution to reduce the CPU time even if table discretization is generally limited by memory occupation. In this work the authors applied tabulated homogeneous reactors (HR) in combination with different turbulent-chemistry interaction approaches to model non-premixed turbulent combustion. The proposed methodologies represent good compromises between accuracy, required memory and computational time. The experimental validation was carried out by considering both constant-volume vessel and Diesel engine experiments.

Ducted Fuel Injection (DFI) has the potential to reduce soot emissions in Diesel engines thanks to the enhanced mixing rate resulting from the liquid fuel flow through a small cylindrical pipe located at a certain distance from the nozzle injector hole. A consolidated set of experiments in constant-volume vessel and engine allowed to understand the effects of ambient conditions, duct geometry and shape on fuel-air mixing, combustion and soot formation. However, implementation of this promising technology in compression-ignition engines requires predictive numerical models that can properly support the design of combustion systems in a wide range of operating conditions. This work presents a computational methodology to predict fuel-air mixing and combustion with ducted fuel injection. Attention is mainly focused on turbulence and combustion modelling.

In this study two different simulation approaches to large eddy simulation of spark-ignition engines are compared. Additionally, some of the simulation results are compared to experimentally obtained in-cylinder velocity measurements. The first approach applies unstructured grids with an automated meshing procedure, using OpenFoam and Lib-ICE with a mapping approach. The second approach applies the efficient in-house code PsiPhi on equidistant, Cartesian grids, representing walls by immersed boundaries, where the moving piston and valves are described as topologically connected groups of Lagrangian particles. In the experiments, two-dimensional two-component particle image velocimetry is applied in the central tumble plane of the cylinder of an optically accessible engine. Good agreement between numerical results and experiment are obtained by both approaches.

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.

A numerical methodology to simulate the high pressure spray evolution and the fuel-air mixing in diesel engines is presented. Attention is focused on the employed atomization model, a modified version of the Huh and Gosman, on the definition of a turbulence length scale limiter and of an adaptive local mesh refinement technique to minimize the result grid dependency. All the discussed models were implemented into Lib-ICE, which is a set of libraries and solvers, specifically tailored for engine simulations, which runs under the open-source CFD technology OpenFOAM®. To provide a comprehensive assessment of the proposed methodology, the validation procedure consisted into simulating, with a unique and coherent setup of all models, two different sets of experiments: a non-evaporating diesel fuel spray in a constant-volume vessel with optical access and an evaporating non-reacting diesel fuel spray in an optical engine.

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.

Computational fluid dynamics represents a useful tool to support the design and development of Heavy Duty Engines, making possible to test the effects of injection strategies and combustion chamber design for a wide range of operating conditions. Predictive models are required to ensure accurate estimations of heat release and the main pollutant emissions within a limited amount of time. For this reason, both detailed chemistry and turbulence chemistry interaction need to be included. In this work, the authors intend to apply combustion models based on tabulated kinetics for the prediction of Diesel combustion in Heavy Duty Engines. Four different approaches were considered: well-mixed model, presumed PDF, representative interactive flamelets and flamelet progress variable. Tabulated kinetics was also used for the estimation of NOx emissions.

In this paper, computation fluid dynamics (CFD) simulations are performed to describe the effect of in-cylinder flow structures on the formation and oxidation of soot in a swirl-supported light-duty diesel engine. The focus of the paper is on the effect of swirl motion and injection pressure on late cycle soot oxidation. The structure of the flow at different swirl numbers is studied to investigate the effect of varying swirl number on the coherent flow structures. These coherent flow structures are studied to understand the mechanism that leads to efficient soot oxidation in late cycle. Effect of varying injection pressure at different swirl numbers and the interaction between spray and swirl motions are discussed. The complexity of diesel combustion, especially when soot and other emissions are of interest, requires using a detailed chemical mechanism to have a correct estimation of temperature and species distribution.

Multiple injection strategies are commonly used in conventional Diesel engines due to the flexibility for optimizing heat-release timing with a consequent improvement in fuel economy and engine-out emissions. This is also desirable in low-temperature combustion (LTC) engines since it offers the potential to reduce unburned hydrocarbon and CO emissions. To better utilize these benefits and find optimal calibrations of split injection strategies, it is imperative that the fundamental processes of multiple injection combustion are understood and computational fluid dynamics models accurately describe the flow dynamics and combustion characteristics between different injection events. To this end, this work is dedicated to the identification of suitable methodologies to predict the multiple injection combustion process.

Diesel combustion is a very complex process, involving a reacting, turbulent and multi-phase flow. Furthermore, heavy duty engines operate mainly at medium and high loads, where injection durations are very long and cylinder pressure is high. Within such context, proper CFD tools are necessary to predict mixing controlled combustion, heat transfer and, eventually, flame wall interaction which might result from long injection durations and high injection pressures. In particular, detailed chemistry seems to be necessary to estimate correctly ignition under a wide range of operating conditions and formation of rich combustion products which might lead to soot formation. This work is dedicated to the identification of suitable methodologies to predict combustion in heavy-duty diesel engines using detailed chemistry.

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.

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.

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 this paper, numerical simulations of an automotive-size optical diesel engine have been conducted employing the Reynolds-Averaged Navier-Stokes (RANS) equations with the standard k-ε turbulence model and a reduced n-heptane chemical mechanism implemented in OpenFOAM. The current paper builds on a previous work where the model has been validated for the same engine using optical diagnostic data. The present study investigates numerically the influence of different operating conditions - relevant for modern diesel engines - on the mixture formation development under non-reactive conditions as well as low- and high-temperature ignition behaviour and flame evolution in the presence of strong jet-wall interactions typically encountered in automotive-size diesel engines. Also, emissions of CO and unburned hydrocarbons (UHC) are considered.