An anticipated shear design method for reinforced concrete beams strengthened with anchoraged carbon fiber‐reinforced polymer by using neural network

Abstract

SUMMARY Using externally bonded carbon fiber‐reinforced polymer (FRP) for strengthening has been turned into a popular decision owing to its mechanical leads. Consequently, design guidelines and researchers have established several analytical equations to predict the contribution of FRP to ultimate shear capacity. The developed analytical equations projected the influence of FRP reinforcements within certain limits. However, not mentioned parameters such as the shear span‐to‐depth ratio and anchorage application influence the ultimate behavior of strengthened specimens. Accordingly, distant predictions between test results and code predictions are observed for the specimens in whom anchorage is applied. As an alternative method, artificial neural network (NN) can be used to predict the contribution of anchoraged carbon FRP to shear strength of deficient reinforced concrete beams. Accordingly, two NN models with back‐propagation are developed in this study. Unlike the existing design codes, the model considers the effect of anchorage and the shear span‐to‐depth ratio at the ultimate state. Artificial NN model is trained, validated and tested using the literature of 79 reinforced concrete beams. Then, NN results are compared with those ‘theoretical’ predictions calculated directly from International Federation for Structural Concrete, the American guideline (ACI 440.2R) and the Australian guideline. Within all theoretical predictions of design guidelines, fib14 provided the best predictions according to experimental results. Consequently, 25% of fib14 predictions are within ±10% of the experimental results, and also, 65% of the fib14 predictions are within ±25% of the measured values. Besides, executed comparisons indicated that the NN model is more exact than the guideline equations with respect to the experimental results and can be applied effectively within the range of parameters covered in this study. Copyright © 2014 John Wiley & Sons, Ltd.

The effects of CFRP orientation on the strengthening of reinforced concrete structures

“…Many researchers have investigated the flexural and shear behaviour of strengthened/retrofitted RC beams, with some review papers also being published (Bakis et al, ; Smith and Teng, ; Pendhari, Kant, and Desai, ; Chin, Shafiq, and Nuruddin, ). Usually, the FRP sheet/laminate is used in the tension side of the beam and perpendicular to cracks; the strength and stiffness increases significantly as compared with situations where fibres are placed oblique to the cracks (Norris, Saadatmanesh, and Ehsani, ; Grace et al, ; Hong et al, ; Altin et al, ; Rahai and Saberi, ; Kim, Kim, and Kim, ; Lu et al, ; Tanarslan, Kumanlioglu, and Sakar, ; zgür Yurdakul and Avşar, ). The effect of FRP on the ultimate capacity of RC beams has been reported in several research outcomes.…”

Shear Strength Prediction of RC Beams Using Adaptive Neuro-Fuzzy Inference System

“…Perera et al (2014) proposed formulations of design equations for RC beams shear strengthened with Near Surface Mounted (NSM) FRP rods using arti cial neural networks, created by backpropagation and the training algorithm of Levenberg-Marquardt, to predict the capacity of the shear strengthened RC beams with NSM-FRP; their results indicated that the ANN could be used for evaluating the shear capacity of RC members strengthened with NSM-FRP [54]. A shear design approach to predicting the contribution of the anchorage FRP reinforcement to the ultimate shear capacity using feed-forward back-propagation algorithm was also proposed by Tanarslan et al (2015) [55]. Furthermore, there are some other investigations based on soft computing methods for estimating the response of concrete structures [56{70].…”

Shear strength prediction of reinforced concrete beams using machine learning

“…They used the proposed ML model that outperformed the design provisions for the shear strength of FRP-reinforced concrete beams suggested by ACI 440-06 and CSA S806-02. Two ANN models with backpropagation were developed by Tanarslan et al to predict the shear strength of reinforced concrete beams externally bonded with carbon fibre reinforced polymer (FRP) sheets [39]. Subsequently, the predictions made by their models were compared with the shear strength calculated from the American guideline (ACI 440.2R) and the Australian guideline to comprehend the effectiveness of the newly developed models.…”