Experimental Study to Evaluate Antisymmetric Reinforced Concrete Deep Beams with Openings under Concentrated Loading Using Strut and Tie Model

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
The Strut-and-Tie modeling (STM) technique represents an applicable and valuable method for structural engineers to design disturbed regions (D-regions) of reinforced concrete structures where the assumption of plane sections remaining plane after loading is inapplicable. The most important aspect to guarantee the suitable structural and economic performance of the design is finding a suitable truss-analogy model, leading to the use of a more efficient model in structural buildings. The evaluation of the antisymmetric Strut-and-Tie models (STM) with openings under different concentrated external loads has not been comprehensively investigated in the literature. So, to address this gap, the goal of this paper is to achieve the most efficient reinforcement layout design in antisymmetric reinforced concrete deep beams with openings under concentrated loading using the strut and tie model.  The experimental work was conducted and included (3) antisymmetric reinforced concrete deep beams with openings that were tested under different concentrated loadings (25, 35, and 16 kips for Specimens 1, 2, and 3, respectively) using the strut and tie model. The ANSYS FEM software is used for the initial strut and tie analysis, and the RISA-3D structural analysis program is used to find the internal forces for all members under concentrated external loads in each specimen. The findings of this paper show that Specimen 1 had the highest efficiency of 1.67, while Specimen 3 had the lowest efficiency of 1.31. It can be concluded that the efficient reinforcement layout of the strut and tie model leads to the highest efficiency of the model, regardless of the value of the externally applied load.
Language:
English
Published:
International Journal of Engineering, Volume:36 Issue: 12, Dec 2023
Pages:
2272 to 2283
magiran.com/p2629823  
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