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The aim of this study is to evaluate the existing chemical kinetic mechanism reduction techniques. From here, an appropriate reduction scheme was developed to create compact yet comprehensive surrogate models for both diesel and biodiesel fuels for diesel engine applications. The reduction techniques applied here were Directed Relation Graph (DRG), DRG with Error Propagation, DRG-aided Sensitivity Analysis, and DRG with Error Propagation and Sensitivity Analysis. Nonetheless, the reduced mechanisms generated via these techniques were not sufficiently small for application in multi-dimensional computational fluid dynamics (CFD) study. A new reduction scheme was therefore formulated. A 68-species mechanism for biodiesel surrogate and a 49-species mechanism for diesel surrogate were successfully derived from the respective detailed mechanisms.

This work is an extension to a previously reported work on chemical kinetic mechanism reduction scheme for large-scale mechanisms. Here, Perfectly Stirred Reactor (PSR) was added as a criterion of data source for mechanism reduction instead of using only auto-ignition condition. As a result, a reduced n-hexadecane mechanism with 79 species for diesel fuel surrogate was successfully derived from the detailed mechanism. Following that, the reduced n-hexadecane mechanism was validated under auto-ignition and PSR conditions using zero-dimensional (0-D) closed homogeneous batch reactor in CHEMKIN-PRO software. Agreement was achieved between the reduced and detailed mechanisms in ignition timing predictions and the reduced n-hexadecane mechanism was able to reproduce species concentration profiles with a maximum error of 40%. Accordingly, two-dimensional (2-D) Computational Fluid Dynamic (CFD) simulations were performed to study the spray combustion phenomena within a constant volume bomb.

This work presents the experimental investigation of Diesel Particulate Filter (DPF) regeneration and a calibration procedure of a 1D DPF simulation model based on the commercial software AVL BOOST v. 5.1. Model constants and parameters are fitted on the basis of a number of steady state DPF experiments where the DPF is exposed to real engine exhaust gas in a test bed. The DPF is a silicon carbide filter of the wall flow type without a catalytic coating. A key task concerning the DPF model calibration is to perform accurate DPF experiments because measured gas concentrations, temperatures and soot mass concentrations are used as model boundary conditions. An in-house-developed raw exhaust gas sampling technique is used to measure the soot concentration upstream the DPF which is also needed to find the DPF soot burn rate.

This paper reports the developmental work of skeletal biodiesel surrogate mechanisms specifically for integration with computational fluid dynamics (CFD) solvers. The fuels of interests here were methyl esters of coconut, palm and soybean. Their combustion kinetics were collectively represented by a detailed mechanism with appropriate components of a biodiesel surrogate (methyl decanoate/methyl-9-decenoate) and a diesel surrogate (n-heptane). As a result of computational complexity induced by the detailed mechanism with 3299 species and 10806 reactions, several mechanism reduction methods were employed such as directed relation graph, isomer lumping and temperature sensitivity analysis. Three different skeletal mechanisms, with the inclusion of low- and high-temperature chemistries, were built as a result of different governing reaction pathways in each fuel.

Development of numerical tools for quantitatively assessing biofuel combustion in Internal Combustion Engines and facilitating the identification of optimum operating parameters and emission strategy are challenges of engine combustion research. Biofuels obtained through e.g. a Fischer-Tropsch process (FT) are complex mixtures of wide ranges of high molecular weight hydrocarbons in the diesel and naphtha boiling range dominated by C10-C18 hydrocarbons in n-alkane, iso-alkane, alkenes, aromatic and oxygenate classes. In this paper modeling of combustion in a rapid compression machine has been performed using model compounds from a given FT biofuel distribution as surrogate fuels. Furthermore, the detailed mechanism has been reduced by applying an automatic necessity analysis removing redundant species from the detailed model.

This work concerns the modelling of soot formation process in diesel spray combustion under engine-like conditions. The key aim is to investigate the soot formation characteristics at different ambient temperatures. Prior to simulating the diesel combustion, numerical models including a revised multi-step soot model is validated by comparing to the experimental data of n-dodecane fuel in which the associated chemistry is better understood. In the diesel spray simulations, a single component n-heptane mechanism and the multi-component Diesel Oil Surrogate (DOS) model are adopted. A newly developed C16-based model which comprises skeletal mechanisms of n-hexadecane, heptamethylnonane, cyclohexane and toluene is also implemented. Comparisons of the results show that the simulated liftoff lengths are reasonably well-matched to the experimental measurement, where the relative differences are retained to below 18%.