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    Experimental Investigation and Modeling of FRP–Concrete Joint Bond Strength Based on Failure Depth

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    %28ASCE%29CC.1943-5614.0001161.pdf (1.094Mb)
    Date
    12/1/2021
    Author
    Behnaz Arefian
    Davood Mostofinejad
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    Abstract
    The growing interest in fiber-reinforced polymer (FRP) composites in recent years for use in strengthening concrete structures bears witness to their efficiency and ease of use. A major issue in FRP strengthening designs, however, is the determination of the bond strength (ultimate load capacity) of the FRP strips, which is quite dependent on their debonding off the concrete substrate. Identification of the major parameters involved in the FRP–concrete bond capacity forms an important step toward its prediction. The parameters commonly considered in previous models include the geometric and mechanical properties of FRP sheets as well as the properties of both the concrete and the adhesive material used as determinants of bond strength. The present study, however, explores the additional parameter of cement-to-aggregate weight ratio for its effect on the failure plane. In the experimental phase of the study, a wide range of FRP strips is used in three different series of concrete specimens to investigate the failure plane in each. Based on the post-test conditions of the specimens, a novel method is adopted for the first time to measure the failure depth of the externally bonded reinforcement (EBR) strengthening technique. Accordingly, the depth of the failure plane is expressed as a function of the cement-to-aggregates weight ratio. In the second phase, an analytical model is developed that draws upon interfacial fracture energy and in which failure depth is introduced as one of the parameters involved in interfacial fracture energy. The unknown parameters of the new model are then derived based on 196 specimens (85% of the data set) from the experimental results of the present study and the extracted data from previous studies. Finally, the model is validated against three existing well-known ones using 35 random specimens (15% of the data set) of the database to show the satisfactory performance of the proposed model.
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    http://yetl.yabesh.ir/yetl1/handle/yetl/4271826
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