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New approach to predict shear capacity of reinforced concrete beams strengthened with NSM technique

机译:NSM技术增强钢筋混凝土梁抗剪承载力的新方法

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摘要

Understanding the shear behavior of a concrete beam is still a challenging task due to several complex mechanisms involved. The Modified Compression Field Theory (MCFT) demonstrated an ability to predict, with good accuracy, the shear capacity of reinforced concrete (RC) members. Due to its iterative nature, the MCFT is not a straightforward design methodology, and a simplified MCFT (SMCFT) approach of this method was proposed to overcome this aspect. This model takes into account the tensile stress installed in the cracked concrete and inclination of the diagonal compressive strut, and requires a smaller number of model parameters than MCFT. This paper presents a new approach to predict the shear capacity of RC beams shear strengthened with fiber-reinforced polymer (FRP) laminates/rods applied according to the near-surface-mounted (NSM) technique. The new approach is based on the SMCFT and considers the relevant features of the interaction between NSM FRP systems and surrounding concrete, such as debonding of FRP laminate/rod and fracture of surrounding concrete of FRP. The experimental results of 100 beams strengthened with different configurations and shear strengthening ratio of FRP reinforcements are used to appraise the predictive performance of the developed approach. By evaluating the ratio between the experimental results to the analytical predictions (Vexp./Vana.), an average value of 1.09 is obtained for the developed approach with a coefficient of variation of 11%.
机译:由于涉及多种复杂机制,因此了解混凝土梁的剪切性能仍然是一项艰巨的任务。修正压缩场理论(MCFT)证明了能够以较高的精度预测钢筋混凝土(RC)构件的剪切能力。由于其迭代性质,MCFT并不是一种简单的设计方法,因此提出了一种简化的MCFT(SMCFT)方法来克服此问题。该模型考虑了安装在开裂混凝土中的拉应力和对角压缩支柱的倾角,并且与MCFT相比,需要较少的模型参数。本文提出了一种新方法来预测根据近表面安装(NSM)技术应用的纤维增强聚合物(FRP)层压板/棒增强的RC梁的抗剪承载力。该新方法基于SMCFT,并考虑了NSM FRP系统与周围混凝土之间相互作用的相关特征,例如FRP层压板/棒的剥离和FRP周围混凝土的断裂。用100种不同构型和FRP加固的抗剪加固率的梁的试验结果来评价该方法的预测性能。通过评估实验结果与分析预测之间的比率(Vexp./Vana。),对于已开发的方法,变异系数为11%,平均值为1.09。

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