In this research, the flexural and shear behavior of five locally developed ultra-high-performance fiber-reinforced concrete beams was experimentally investigated. Four-point loading tests were carried out on concrete specimens which were further compared with five normal-strength concrete beams constructed at the laboratory. The objective of this study is to assess the flexural and shear behavior of ultra-high-performance fiber-reinforced concrete beams and compare them with that of normal-strength beams and available equations in the literature. Results indicate underestimation of shear (up to 2.71 times) and moment capacities (minimum 1.27 times, maximum 3.55 times) by most of the equations in beams with low-reinforcement ratios. Finally, results reveal that the experimental flexural and shear capacities of ultra-high-performance fiber-reinforced concrete specimens are up to 3.5 times greater than their normal-strength counterpart specimens.
This article compares the flexural responses of ultrahigh-performance fiber-reinforced concrete (UHPFRC) specimens and their normal-strength concrete (NSC) counterparts through an experimental study. Four UHPFRC specimens reinforced with 2 % steel fiber (by total volume of concrete) with a length of 13 mm and a diameter of 0.2 mm were used with longitudinal steel rebars at different reinforcement ratios to determine their flexural responses. For comparative purposes, three NSC beams were also tested. Results were compared with relevant equations in the literature. Moreover, the fracture energy of the specimens was compared to provide a better understanding of the ductility in the two types of beams. Results showed better performance of UHPFRCs in terms of peak load, fracture energy, and moment capacity as compared with their NSC counterparts. Failure in UHPFRC specimens with high reinforcement ratios was dominated by shear-flexure patterns, while flexure patterns were dominant in specimens with low reinforcement ratios. Failure of NSC specimens, on the other hand, was characterized by shear, regardless of reinforcement ratio. Additionally, available equations for moment capacity of ultrahigh-performance concretes (UHPCs) appear too conservative, especially for higher reinforcement ratios. Lastly, statistical models were proposed to predict the load–displacement curves of UHPFRC dogbone and beam specimens, which fitted well with experimental results with correlations over 0.90.
In this paper, an optimization approach was presented for the flexural strength and stiffness design of reinforced concrete beams. Surrogate modeling based on machine learning was applied to predict the responses of the structural system in three-point flexure tests. Three design input variables, the area of steel bars in the compression zone, the area of steel bars in the tension zone, and the area of steel bars in the shear zone, were adopted for the dataset and arranged by the Box-Behnken design method. The dataset was composed of thirteen specimens of reinforced concrete beams. The specimens were tested under three-points flexure loading at the age of 28 days and both the failure load and the maximum deflection values were recorded. Compression and tension tests were conducted to obtain the concrete data for the analysis and numerical modeling. Afterward, finite element modeling was performed for all the specimens using the ATENA program to verify the experimental tests. Subsequently, the surrogate models for the flexural strength and the stiffness were constructed. Finally, optimization was conducted, supporting the factorial method for the predicted responses. The adopted approach proved to be an excellent tool to optimize the design of reinforced concrete beams for flexure and stiffness. In addition, experimental and numerical results were in very good agreement in terms of both the failure type and the cracking pattern.
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