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This thesis presents the research on direct-fuel-injection (DFI) performance analyses of the two-stroke engine using computational fluid dynamics (CFD). The aims of this research are: (1) to generate a finite volume mesh that can be used to simulate the moving of the piston and opening and closing the ports of the cylinder, (2) to achieve an numerical flow pattern of the scavenging process and (3) to study the DFI process using the mesh and the flow pattern obtained from the first two parts. The three parts in the analyses, therefore, are the engine geometry modelling, scavenging process modelling and DFI modelling. CFD software STAR-CD was used to write the programme and perform the analysis. The geometry model used a moving mesh mechanism with variable openings to simulate the piston motion and port area changes. The scavenging model was constructed to calculate 3D, compressible, turbulent, transient flow with heat transfer and changing volume. Results of the calculation provided a large number of data, including flow patterns, pressure and temperature distributions and fresh-charge concentrations. The DFI process was simulated as a gasliquid two-phase flow. Fuel droplets dispersed in the continuous gas phase were calculated using the Lagrangian model. Four DFI cases that differ in position and number of injectors were simulated. Fuel droplet distribution, including droplet size, velocity, temperature and position, and fuel-vapour concentration were obtained. The result of the geometry modelling shows that the finite volume programme performed well for this particular task. Because of the limitation of the computer hardware used, this programme was restricted to be used for the simulation of the engine process before the ignition, i. e., cold running condition, therefore, combustion process was not included. The findings from the analyses, with very limited resources, would help improve the engine design. The results of all four cases indicate that, even only for the period of engine process before the ignition, the DFI two-stroke engine can significantly reduce hydrocarbon emissions compared with the conventional carburettor engine.

A survey of the literature on the techniques used in and the results obtained from studies of nightglow variability is presented. Three microprocessor controlled instruments (an eight channel tilting filter spectrometer, an earlier six channel version and a CCD based low light level camera) have been constructed with the aim of studying variations in the nightglow, especially of the type associated with the passage of gravity waves through the emitting layers. The final stages of development of the eight channel spectrometer are described, including the design of automatic dark count and reference light systems, a temperature control system for the filters and an interface for transferring the spectrometer data into a computer. Calibration experiments to determine the wavelength, line shape and intensity response of this spectrometer are described. The development of suites of computer programmes for analysing the data from both spectrometers and the camera is then discussed. For the spectrometers, these perform the functions of subtraction of dark count, reduction of the calibration data to a form suitable for use in the analysis of data spectra in terms of a set of line shapes and continuum response functions, and execution of this analysis to produce plots of the emission intensities and OH rotational temperature versus time. For the camera, software was produced to allow separation of stellar images from the airglow emission; stellar image intensities were analysed in an attempt to characterise atmospheric absorption. Software was also written to correct airglow intensities for absorption and the van Rhijn effect and finally to reproject the images in the form of a map of the emitting layer. Observations made with the instruments working separately and in conjunction are described and the results are presented as an example of the performance of the instruments and the software.

Master of Science / Department of Statistics / Michael J. Higgins / There have been a wave of recent interest in understanding the dynamics of vehicular emissions in university towns. Using data from a recent survey of Kansas State University students, faculty, and staff-which includes a detailed itinerary of a day’s worth of travel -I assess spatial and temporal trends of emissions at Kansas State University. By combining the survey data with secondary sources of data, including vehicular emissions data from Fueleconony.gov and trip distance information from Google, I obtain improved measure for the quantity of emissions produced during each trip. After an extensive cleaning of the data, I develop heat maps for emissions composed of shape files identifying zip-code boundaries and a raster layer. I find that most vehicular emissions are concentrated around campus, with the highest level of emissions occurring during rush hour. Furthermore, faculty and staff appear to, on average, produce more emissions than students. I also investigate how proposed methods for reducing emissions will affect these spatio-temporal trends. Specifically, I show that walking or biking short distances instead of driving may lead to a small overall reduction in vehicular emissions.