Thesis (M.S.)--Auburn University, 2008. / Abstract. Vita. Includes bibliographical references (p. 166-174).

Thesis (M.S.)--Auburn University, 2008. / Abstract. Vita. Includes bibliographical references (p. 207-212).

To maintain the sustainability of cement and concrete production, there is a trend to use wastes in their production. Soda waste, generated by soda ash production process, and beer waste, generated by beer filtration process, are two locally produced wastes in Turkey and many other countries. The nature of these wastes, mostly their fineness, makes them possible to be used in concrete production, especially as a viscosity modifying agent in the self consolidating type of concrete. In this study, the addition of soda and beer wastes to self consolidating mortar (SCM) and self consolidating concrete (SCC), without any treatment but drying, and its effect on their properties were investigated. Mortar and concrete mixes were prepared using these two wastes as cement or aggregate replacement in various amounts. Tests like slump flow, V-Funnel and L-Box for determining the fresh properties, and compressive strength for the hardened properties of the mixtures were carried out to examine the effects of these wastes on the properties of SCM and SCC. The tests revealed that soda waste takes no role in the strength development of the mixes. However, it is possible to use this waste as aggregate replacement to improve the workability and flowability properties of SCM and SCC. The use of beer waste showed contradictive results. A special treatment for this waste before using it in concrete might be required.

Self-consolidating concrete (SCC) has wide use for placement in congested reinforced concrete structures in recent years. SCC represents one of the most outstanding advances in concrete technology during the last two decades. In the current work a great deal of cognizance pertaining to mechanical properties of SCC and comparison of fracture characteristics of notched and unnotched beams of plain concrete as well as using acoustic emission to understand the localization of crack patterns at different stages has been done. An artificial neural network (ANN) is proposed to predict the 28day compressive strength of a normal and high strength of SCC and HPC with high volume fly ash. The ANN is trained by the data available in literature on normal volume fly ash because data on SCC with high volume fly ash is not available in sufficient quantity. Fracture characteristics of notched and unnotched beams of plain self consolidating concrete using acoustic emission to understand the localization of crack patterns at different stages has been done. Considering this as a platform, further analysis has been done using moment tensor analysis as a new notion to evaluate fracture characteristics in terms of crack orientation, direction of crack propagation at nano and micro levels. Analysis of B-value (b-value based on energy) is also carried out, and this has introduced to a new idea of carrying out the analysis on the basis of energy which gives a clear picture of results when compared with the analysis carried out using amplitudes. Further a new concept is introduced to analyze crack smaller than micro (could be hepto cracks) in solid materials. Each crack formation corresponds to an AE event and is processed and analyzed for crack orientation, crack volume at hepto and micro levels using moment tensor analysis based on energy. Cracks which are tinier than microcracks (could be hepto), are formed in large numbers at very early stages of loading prior to peak load. The volume of hepto and micro cracks is difficult to measure physically, but could be characterized using AE data in moment tensor analysis based on energy. It is conjectured that the ratio of the volume of hepto to that of micro could reach a critical value which could be an indicator of onset of microcracks after the formation of hepto cracks.