Study On The Mechanical Performance Of PBL Shear Connection Based On Steel Fiber Reinforced Concrete

Steel-concrete composite structure combines the advantages of steel and concrete structure,and is more and more used in modern bridge engineering.Perfobond Leiste(PBL)shear connector is an important force transfer component of steel-concrete composite beam that connects the steel structure and the reinforced concrete wing plate as a whole,to ensure that there is no relative slip between them.The mechanical performance of PBL shear connector is one of the key factors affecting the service life and reliability of steel-concrete composite structure.The study on the mechanical properties,fracture mechanism and interaction mechanism of steel fiber reinforced concrete(SFRC)and PBL shear connector is not only helpful to improve the understanding of its force transfer mechanism and failure process,but also has important significance for practical engineering applications.In this paper,theoretical analysis and experimental research are combined to carry out the research.Firstly,the fracture mechanism and mechanical properties of steel fiber reinforced concrete are studied based on Boundary Effect Model(BEM).The material failure characteristics at different stages in the fracture process of steel fiber reinforced concrete are analyzed,and the two important material parameters of tensile strength and fracture toughness are determined by three-point bending test.Then,the mesoscopic numerical model,equivalent numerical model and macro-mesoscopic multiscale numerical model of steel fiber reinforced concrete are established by different methods respectively.The finite element simulations are carried out and compared with the experimental results,and the characteristics and rationality of each numerical model were discussed,which lay the foundation for the numerical simulation of PBL shear connector.Furthermore,numerical models of the PBL shear connector are established.Through simulation and experimental comparison,the failure mode of PBL shear connector is explored and the influence of various factor on the ultimate shear capacity and relative slip of PBL shear connector is analyzed respectively based on the single factorn method.Finally,an Improved Adaptive Genetic Algorithm(IAGA)is proposed to optimize the Back Propagation Neural Network(BPNN),and then the IAGA-BPNN prediction model is established to predict the ultimate shear capacity of PBL shear connector with an average error of only 1.69%.In summary,four fracture stages of steel fiber concrete are obtained,and the law of crack propagation of steel fiber reinforced concrete is revealed by experimental method.A method for determine the tensile strength and fracture toughness of steel fiber reinforced concrete using small notched three-point-bend specimens under laboratory conditions is found.The feasibility of the numerical simulation method of steel fiber reinforced concrete and PBL shear connector is analyzed by using finite element simulation.Based on this,four main factors affecting the ultimate shear capacity of PBL shear connector are obtained.In addition,the successful application of the IAGA-BPNN prediction model demonstrates the superiority of machine learning combined with intelligent optimization algorithms in predicting the ultimate shear capacity of PBL shear connector,which provides a valuable reference for engineering applications.