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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.

This study presents diagnostic development of diffuse back-illuminated extinction imaging of soot. The method provides high temporal and spatial resolution of the line-of-sight optical density of soot (KL) in compression-ignited fuel sprays relevant to automotive applications. The method is subjected to two major sources of error, beam steering effects and broadband flame luminosity effects. These were investigated in detail in a direct injection combustion chamber with diesel fuel, under high and low sooting conditions. A new method for correcting flame luminosity effects is presented and involves measuring the flame luminosity using a separate high-speed camera via a beam splitter. The new method and existing methods are applied and the resulting flame luminosity correction errors are compared. The new method yields 50% lower errors than the most promising method (optical flow method).

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.

Using ammonia as fuel in retrofitted large marine vessels or heavy-duty vehicles has the potential to reduce CO2 emissions. However, ammonia is hard to burn in an internal combustion engine (ICE) due to its poor combustion properties, i.e. having high autoignition temperatures and low flame speeds. This results in the need for a highly reactive secondary fuel or an improved ignition system for achieving complete and stable combustion. This study investigates a radical technology for the ignition of a fuel-air mixture using carbon nanotubes. The technology consists of injecting a mixture of multi-walled carbon nanotubes and ferrocene (CNT-Fe) into a fuel-air mixture and subjecting the particles to a bright flash of light. Due to the photochemical properties of CNT-Fe particles, the absorbed light initiates ignition.

In internal combustion engines, fuel injection timing, injection rate and pressure is optimized to ensure suitable combustion and reduce emissions. Injectors are complex systems where mechanical, electromagnetic, and fluid dynamics interact together. Numerical model development of injectors allows for investigating different conditions, as well as optimization of the system in a safe manner. In this study, a 1-dimensional (1D) mathematical model of a direct gasoline injector (GDI) is presented, supported by computational fluid dynamics (CFD) in-nozzle flow simulations. The described system is a commercially available injector where the internal geometry was captured using silicone molds of the nozzle. The model includes the representation and interaction of the different components across several domains using the bond graph methodology. In the injector, the needle is magnetic and is lifted when an electromagnetic field is activated.