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A stochastic reactor model has been employed to aid the development of a new highly efficient and compact opposing piston, barrel engine. It is desirable to utilize the engine across a broad range of applications and the designers have identified the use of low calorific value fuels derived from low grade biomass gasification in HCCI mode as one possible end use. Biogas from solid fuel gasification can vary largely in composition of main components depending on feedstock and gasification method. Hence, in order to address the engines applicability to run on biogas in general terms, identifying a simple two-component surrogate fuel which can be varied under testing is of great importance. A stochastic reactor model in the form of a commercially available software, LOGEsoft, has been used to examine suitable surrogate gas mixtures which could be used to best simulate the biogas during initial engine testing and development.

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.

Particulate matter (PM) has been sampled from a compression ignition engine using a differential mobility spectrometer (Cambustion DMS 500) and for imaging in a transmission electron microscope (TEM) with the aim of coupling these two measuring techniques. A known issue when coupling these two methods is that a devise like the DMS samples all PM, and the TEM only soot. To help resolve this issue, a thermal denuder was designed and built to remove all volatile organic compounds (VOC) from the sample prior to entering the DMS. For TEM imaging, soot was either collected directly onto a TEM grid using the thermophoretic effect or collected onto quartz filters with the soot then transferred onto the TEM grids. The direct to grid technique did not work after the denuder due to the gas temperature being too low for the thermophoretic effect; hence the reason to collect some soot using the quartz filters. Soot was removed from the filters using an ethanol wash/sonication technique.