Coupled flexural-shear design of R/C beams strengthened with FRP

Tensile stress-strain relaxation as a failure precursor for FRP-strengthened RC beams

“…Where the brittle failure of the FRP-strengthened RC element is governed by several large shear cracks of the mixed Mode I and II, the overall trend of the strain increments and the order of their magnitude can still be captured but the final failure strains could be grossly under-estimated. In the authors opinion, the traditional shear design methods that limit the effective tensile strains on the FRP strips [23][24][25] are still the most convenient for shear strengthening design.…”

“…For shear strengthening of RC beams, the application of vertical or diagonal side-bonded FRP strips [19][20][21][22] led to the development of traditional design methods [23][24][25][26]. To prevent or delay brittle plate-end failures, 'U'-shaped side-bonded FRP strips were also simultaneously applied to RC beams strengthened in flexure with FRP plates [27][28][29][30][31] and this has become a common construction practice [32,33].…”

Shear capacity of reinforced concrete members strengthened in shear with FRP by using strut-and-tie models and genetic algorithms

“…Aprile and Benedetti [23] extended the variable angle truss model to the case of RC beams with additional FRP reinforcement. Following the compression field theory presented by Collins [21] and by introducing some modifications, the local inclination of the compression strut was determined.…”

Artificial intelligence techniques for prediction of the capacity of RC beams strengthened in shear with external FRP reinforcement

“…Although the number of input parameters should be large enough to represent the system properly, a large number might reduce the efficiency and accuracy of the training process in case of using a small training set. For this particular problem, 46 U-wrapping beams [11,14,15] were used for the configuration and learning of the NN. The choice of the input parameters has been guided based on the predictions obtained with the shear capacity equations of different design proposals [16][17][18][19].…”

“…In contrast with the usual regression analysis of experimental data [7,9,10] and with the classical strut-and-tie models [11] employed to predict the capacity of an FRP shear-strengthened RC beam, this paper outlines an understanding of how artificial intelligence systems, in particular neural networks and genetic algorithms, can be used to improve the predictive capacity.…”