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The subject of this work is 3D numerical simulations of combustion and soot emissions for a passenger car diesel engine. The CFD code STAR-CD version 3.26 [1] is used to resolve the flowfield. Soot is modeled using a detailed kinetic soot model described by Mauss [2]. The model includes a detailed description of the formation of polyaromatic hydrocarbons. The coupling between the turbulent flowfield and the soot model is achieved through a flamelet library approach, with transport of the moments of the soot particle size distribution function as outlined by Wenzel et al. [3]. In this work we extended this approach by considering acetylene feedback between the soot model and the combustion model. The model was further improved by using new gas-phase kinetics and new fitting procedures for the flamelet soot library.

Methanol is today considered a viable green fuel for combustion engines because of its low soot emissions and the possibility of it being produced in a CO2-neutral manner. Methanol as a fuel for combustion engines have attracted interest throughout history and much research was conducted during the oil crisis in the seventies. In the beginning of the eighties the oil prices began to decrease and interest in methanol declined. This paper presents the emission potential of methanol. T-Φ maps were constructed using a 0-D reactor with constant pressure, temperature and equivalence ratio to show the emission characteristics of methanol. These maps were compared with equivalent maps for diesel fuel. The maps were then complemented with engine simulations using a stochastic reactor model (SRM), which predicts end-gas emissions. The SRM was validated using experimental results from a truck engine running in Partially Premixed Combustion (PPC) mode at medium loads.

Large two-stroke marine Diesel engines have special injector geometries, which differ substantially from the configurations used in most other Diesel engine applications. One of the major differences is that injector orifices are distributed in a highly non-symmetric fashion affecting the spray characteristics. Earlier investigations demonstrated the dependency of the spray morphology on the location of the spray orifice and therefore on the resulting flow conditions at the nozzle tip. Thus, spray structure is directly influenced by the flow formation within the orifice. Following recent Large Eddy Simulation resolved spray primary breakup studies, the present paper focuses on spray secondary breakup modelling of asymmetric spray structures in Euler-Lagrangian framework based on previously obtained droplet distributions of primary breakup.

A novel 0-D Probability Density Function (PDF) based approach for the modelling of Diesel combustion using tabulated chemistry is presented. The Direct Injection Stochastic Reactor Model (DI-SRM) by Pasternak et al. has been extended with a progress variable based framework allowing the use of a pre-calculated auto-ignition table. Auto-ignition is tabulated through adiabatic constant pressure reactor calculations. The tabulated chemistry based implementation has been assessed against the previously presented DI-SRM version by Pasternak et al. where chemical reactions are solved online. The chemical mechanism used in this work for both, online chemistry run and table generation, is an extended version of the scheme presented by Nawdial et al. The main fuel species are n-decane, α-methylnaphthalene and methyl-decanoate giving a size of 463 species and 7600 reactions.

Several models for ignition, combustion and emission formation under diesel engine conditions for multi-dimensional computational fluid dynamics have been proposed in the past. It has been recognized that the use of a reasonably detailed chemistry model improves the combustion and emission prediction especially under low temperature and high exhaust gas recirculation conditions. The coupling of the combustion chemistry and the turbulent flow can be achieved with different assumptions. In this paper we investigate a selection of n-heptane spray experiments published by the Engine Combustion Network (ECN spray H) with three different combustion models: well-stirred reactor model, transient interactive flamelet model and progress variable based conditional moment closure. All models cater for the use of detailed chemistry, while the turbulence-chemistry interaction modeling and the ability to consider local effects differ.

Today numerical models are a major part of the diesel engine development. They are applied during several stages of the development process to perform extensive parameter studies and to investigate flow and combustion phenomena in detail. The models are divided by complexity and computational costs since one has to decide what the best choice for the task is. 0D models are suitable for problems with large parameter spaces and multiple operating points, e.g. engine map simulation and parameter sweeps. Therefore, it is necessary to incorporate physical models to improve the predictive capability of these models. This work focuses on turbulence and mixing modeling within a 0D direct injection stochastic reactor model. The model is based on a probability density function approach and incorporates submodels for direct fuel injection, vaporization, heat transfer, turbulent mixing and detailed chemistry.

The solution mapping method Adaptive Polynomial Tabulation (APT) for complex chemistry is presented. The method has the potential of reducing the computational time required for stochastic reactor model simulations of the HCCI combustion process. In this method the solution of the initial value chemical rate equation system is approximated in real-time with zero, first and second order polynomial expressions. These polynomials are algebraic functions of a progress variable, pressure and total enthalpy. The chemical composition space is divided a priori into block-shaped regions (hypercubes) of the same size. Each hypercube may be divided in real-time into adaptive hypercubes of different sizes. During computations, initial conditions are stored in the adaptive hypercubes. Two concentric Ellipsoids of Accuracy (EOA) are drawn around each stored initial condition.