Saudi Cultural Missions Theses & Dissertations
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Item Embargo Comprehensive treatment of strut-and-tie approach across concrete deep beams reinforced with different systems(Kansas State University, 2025) Alqarni, Ali H; Hayder A. RasheedThis dissertation investigates the nonlinear behavior of reinforced concrete deep beams, combining experimental and analytical methodologies to assess the influence of material and geometric variables. The study introduces a matrix truss analysis method for predicting load-deflection behavior at critical stages for different reinforcement materials: conventional steel bars and Glass Fiber Reinforced Polymer (GFRP) bars. The method employs the strut and tie model to enhance the accuracy of nodal displacements and load predictions without postulating the nonlinear strain profile. Further, an experimental evaluation explores the effects of concrete strength and steel reinforcement ratios under monotonic loading, highlighting the impact of shear span-to-depth ratios on beam performance. Finally, a parametric analysis employing the strut and tie method, applied to steel-reinforced concrete deep beams, clarifies the relationships among various structural parameters, revealing strong correlations between the characteristics of deep beams and prediction outcomes. This enhances our understanding of deep beam mechanics and contributes to safer, more effective, and accurate structural designs.22 0Item Restricted Nonlinear Models for Mixture Experiments Including Process Variables(University Of Southampton, 2024) Alzahrani, Shroug; Biedermann, StefanieThis present work is concerned with finding and assessing a class of models that flexibly fits data from mixture experiments and mixture-process variables experiments, and with providing guidelines for how to design mixture experiments and mixture-process variables experiments when these models are fitted. Most models in the literature are either based on polynomials and are therefore not very flexible, or have a large number of parameters that make the response surface interpretation difficult to understand. The modified fractional polynomial models are a recent class of models from the literature that are flexible and parsimonious but quite restrictive. We contribute to mixture experiments by proposing a new class of nonlinear models, the complement mixture fractional polynomial (CMFP) models, by making an additional transformation of the fractional polynomial, which results in less restrictive models while retaining (and indeed exceeding) the advantages of this class. Moreover, we suggest an extended form for the modified fractional polynomial models to fit data from mixture-process variables experiments.13 0