Geopolymer cements present a unique opportunity to make concrete binders almost entirely out of waste stream materials. Geopolymers made from fly ash, a waste product of coal power generation, as the aluminosilicate source and caustic activating solution were the focus of this study. However, the use of waste stream materials presents many challenges. One major stumbling block is that fly ash is inherently variable in composition and difficult to comprehensively characterize. The purpose of this work was to clarify the relationship between fly ash composition and reactivity in geopolymer cements. Ten fly ashes comprising a wide compositional spectrum were selected for the study and were characterized using quantitative x-ray diffraction and multispectral image analysis (MSIA) of x-ray maps coupled with point compositional analysis. The fly ashes were mixed into geopolymer mortars to determine their reactivity when activated as geopolymers. I hypothesized that the fly ashes that performed well under geopolymer formation conditions would have similarities in the glassy phases identified in them. The fly ashes that resulted in geopolymers with high compressive strengths did have several glassy phases in common. The phases were typically high in calcium, high in silicon, and somewhat low in aluminum. To determine whether the common phases were soluble and therefore likely to be dissolved, a dissolution method was used in which fly ash was mixed with concentrated caustic solution and continuously agitated; after 7 d and 28 d, the solid residues from the dissolution were studied using MSIA. The results showed that most of the glassy phases hypothesized to react were reactive, although the results were somewhat complex due to the heterogeneity of fly ash. The MSIA method proposed in previous work was further developed through this study, and a new way of selecting the training classes for phase composition assignment in the images was proposed. / text

M.Ing. / Globally, hazardous weather phenomena such as violent storms, oods, cyclones, tornadoes, snow and hail contribute to signi cant annual xed property damages, loss of movable property and loss of life. The majority of global natural disasters are related to hydro-meteorological events. Hazardous storms are destructive and pose a threat to life and property. Forecasting, monitoring and detecting hazardous storms are complex and demanding tasks, that are however essential. In this study automatic hazardous weather detection utilizing remotely sensed meteorological data has been investigated. Image processing techniques have been analyzed and applied to multispectral meteorological satellite image data obtained from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instruments on-board the Meteosat Second Generation (MSG) geostationary meteorological satellites Meteosat-8 and Meteosat-9. The primary focus of this study is the detection of potentially hazardous hydrometeorological phenomena in South Africa. A methodology for detecting potentially hazardous storms over South Africa using meteorological satellite imagery from MSG/SEVIRI is presented. An index indicative of the hazardous potential of a storm is de ned to aid in the identi cation of a ected geographical areas and to quantify the destructive potential of the detected storm. The Hazardous Potential Index (HPI) is generated through the use of image processing techniques such as cloud masking, cloud tracking and an image-based analysis of the constituent elements of a severe convective storm. A retrospective review was performed with respect to 20 case studies of documented storms which had adversely a ected areas of South Africa. A red-green-blue (RGB) composite image analysis technique, that may be utilized in the identi cation of severe convective storms using SEVIRI image data, was also applied to these case studies.