Reliability-based analysis of the flexural strength of concrete beams reinforced with hybrid BFRP and steel rebars

• Published in: Archives of Civil and Mechanical Engineering Vol. 22; no. 4; p. 171
• Main Authors: Zhang, Wei, Liu, Xiang, Huang, Yiqun, Tong, Ming-Na
• Format: Journal Article
• Language: English
• Published: London Springer London 28.07.2022; Springer Nature B.V
• Subjects: Algorithms; Basalt; Civil Engineering; Concrete; Concrete structures; Corrosion; Corrosion resistance; Cracks; Deformation; Ductility; Engineering; Failure modes; Fiber reinforced plastics; Fiber reinforced polymers; Finite element analysis; Flexural strength; High rise buildings; Mathematical models; Mechanical Engineering; Metal fatigue; Model accuracy; Modulus of elasticity; Numerical models; Original Article; Performance tests; Prediction models; Rebar; Reinforced concrete; Reinforcing steels; Reliability analysis; Structural forms; Structural Materials; Tensile strength; Reliability; Hybrid reinforced; BFRP; Monte Carlo simulation; Linear moment; Flexural
• ISSN: 2083-3318; 1644-9665; 2083-3318
• DOI: 10.1007/s43452-022-00493-7

The durability of reinforced concrete structures has always been an important problem in civil engineering because steel rebars rust easily. Therefore, fiber-reinforced polymer (FRP) rebars possessing good corrosion resistance, low weight, and easy construction has become a substitute for reinforcement. However, since FRP rebar has a low elastic modulus and is a brittle failure material, large deflections and cracks occur in the FRP concrete beam with no obvious warning before failure. A hybrid reinforced concrete beam that combines the advantages of steel rebar and FRP rebar is a good structural form. The reliability of hybrid reinforced beams must be analyzed to ensure their safety. A flexural performance test of the hybrid basalt FRP (BFRP)–steel-reinforced beam was performed, the failure mode was explored, and the numerical models were established. The accuracy of the models was verified by comparing them with the test results. The numerical models were used to establish a database (630 cases) that was combined with existing research results (33 cases), to obtain the statistics of the uncertainty of the prediction model. Reliability analysis of a large-scale design space was conducted to calibrate the BFRP. Finally, the average deviation from the target reliability index suggested that the values of the partial coefficient of the materials range from 1.2 to 1.4.