| Summary: | A Master of Science thesis in Civil Engineering by Abdullah Mohsin Sagher entitled, "Shear Strength of Reinforced Concrete Beams Made with Recycled Coarse Aggregate," submitted in July 2016. Thesis advisor is Dr. Sami Tabsh. Soft and hard copy available. The Bee'ah's Waste Management Complex in the Emirate of Sharjah, UAE, has been producing aggregate from construction and demolition wastes for quite some time. However, such a product has not been utilized in structural applications. This research focuses on the concrete shear strength, which is a major component of the total shear resistance of reinforced concrete elements. Therefore, the objectives of this study are to investigate the behavior and develop design recommendations for the shear strength of reinforced concrete beams made with locally produced coarse aggregate. To do that, laboratory experiments on fifteen half-scale beams and associated theoretical predictive methods are utilized. The experimental part of the study addresses beams with different concrete compressive strengths, recycled coarse aggregate replacement percentages in the concrete mix, shear span-to-depth ratios and effective flexural steel reinforcement ratios. The experimental results are compared with corresponding findings from reinforced concrete beams employing natural aggregate. The theoretical part of the study considers available codified procedures for predicting the shear strength of concrete beams, such as the ACI 318 and CSA 23.3, as well as the strut-and-tie procedure, modified compression field theory and fracture mechanics approach. Results of the study showed that North American codes can adequately predict the shear strength provided by concrete when the shear span-to-depth ratio is large, but over-estimates it when the applied load is very close to the support. The strut-and-tie model predicted the shear strength of the tested beams much better than the other methods. The recycled concrete beams showed lower shear strength when the coarse aggregate replacement ratio ...
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