Alternative Approaches to Predict Shear Strength of Slender RC Beams Strengthened with Externally Bonded Fiber-Reinforced Polymer Laminates

2020 ◽  
Vol 24 (2) ◽  
pp. 04020002
Author(s):  
Hadi Baghi ◽  
Fatmir Menkulasi
2017 ◽  
Vol 112 ◽  
pp. 125-136 ◽  
Author(s):  
Garyfalia G. Triantafyllou ◽  
Theodoros C. Rousakis ◽  
Athanasios I. Karabinis

2020 ◽  
pp. 136943322098169
Author(s):  
Muhanad M Majed ◽  
Mohammadreza Tavakkolizadeh ◽  
Abbas A Allawi

This study aimed at evaluating the torsional capacity of reinforced concrete (RC) beams externally wrapped with fiber reinforced polymer (FRP) materials. An analytical model was described and used as a new computational procedure based on the softened truss model (STM) to predict the torsional behavior of RC beams strengthened with FRP. The proposed analytical model was validated with the existing experimental data for rectangular sections strengthened with FRP materials and considering torque-twist relationship and crack pattern at failure. The confined concrete behavior, in the case of FRP wrapping, was considered in the constitutive laws of concrete in the model. Then, an efficient algorithm was developed in MATLAB environment to accomplish the analysis, solve the appropriate equations, and calculate the torsional moment and angle of twist at all points. The parametric study considered the effect of effective fiber strain to reach a better prediction for the full torsional behavior. The model was able to predict the torsional behavior of the RC beams strengthened with FRP materials before and after cracking stages with reasonable accuracy.


2021 ◽  
pp. 136943322110499
Author(s):  
Riyam J Abed ◽  
Mohammed A Mashrei ◽  
Ali A Sultan

The externally bonded reinforcement on grooves (EBROG) method is increasingly recognized as an alternative strengthening method that can overcome the debonding problem. This study aims to experimentally investigate the effectiveness of EBROG as compared to the conventional externally bonded reinforcement (EBR) method in strengthening reinforced concrete (RC) beams. Twelve RC beams have been tested under four point load bending. One of these beams has been designated as a reference beam, seven beams have been strengthened with carbon fiber reinforced polymer (CFRP) sheets, and four beams have been strengthened with CFRP laminates using EBROG or EBR methods. The effect of CFRP type, number of layers, as well as the type of strengthening methods on the flexural performance have been also investigated. The load, deflection, stiffness, and failure modes were recorded and discussed intensively. Overall, test results indicated that the flexural strength and stiffness of the strengthened specimens using EBR or EBROG methods increased compared to the control beam, where the increase in the load carrying capacity of beams strengthened using the EBR method ranged between 24.8 and 48.2% and by the EBROG method ranged between 31.7 and 76.7% of the control beam. The most interesting result obtained is that the failure mode of beams has been changed from debonding of CFRP material to rupture of CFRP in some samples strengthened by EBROG, which demonstrates the superior behavior of this strengthening technique as compared to the traditional strengthening using EBR.


2020 ◽  
Vol 47 (7) ◽  
pp. 875-883 ◽  
Author(s):  
A. Zarifian ◽  
R.A. Izadi fard ◽  
A. Khalighi

With regard to the expansion of the use of carbon fiber reinforced polymer (CFRP) in strengthening civil engineering structures due to its high positive points (like high tensile strength and low thickness) as well as its weaknesses in high temperatures especially in buildings and weak points of existing thermal insulators, the experiments mentioned in this article have been carried out to investigate the post-fire conditions of CFRP retrofitting systems using the externally bonded reinforcement technique which resulted from the need to use insulation for this type of reinforcement system to improve its heat performance, as well as the weak points of common insulations. In the first phase, 12 samples of reinforced concrete (RC) beams strengthened with externally bonded carbon fiber reinforced polymer (UD200) were heated at 400 °C, 500 °C, 600 °C, and 800 °C and loaded after cooling, then they were compared with the results of the second phase of the tests which have been explained completely, consisting of 11 RC beams strengthened with CFRP having exactly the same properties as those in the first phase. They were also thermally insulated with intumescent paint that had some advantages like low thickness (1.1 mm) and the speed and ease of implementation and restoration. These results have clearly shown that the new insulating layer not only can maintain the positive feature of common insulations, but also unlike other common insulators, does not add to the thickness of the specimens. Moreover, the application of the intumescent paint both increased the performance of the specimens at high temperatures and covered the weaknesses of CFRP reinforcement system against heat so that the CFRP sheets unlike the ones on the non-insulated specimens did not completely disappear at the highest temperature.


2021 ◽  
Vol 1047 ◽  
pp. 207-213
Author(s):  
Nour Alrouh ◽  
Mohamed Maalej ◽  
Samer Barakat

Externally strengthening reinforced concrete (RC) structures has been a desired practice in both research community and the industry over the last few decades. This application entails bonding composites to the surfaces of RC members to upgrade their strength, stiffness, and ductility. This study will attempt to use Machine Learning (ML) techniques to study and predict the shear strength of RC beams strengthened in shear with externally-bonded fiber-reinforced polymer (EB-FRP) laminates. An extensive database consisting of 511 tested specimens and 17 test parameters were collected. An appropriate artificial neural network (ANN)-based model was used to predict the shear capacities (Vu) of the FRP-strengthened beams, including the specific contributions of the EB-FRP (Vf) to these shear capacities. The obtained results indicate that the ANN-based model provided reasonable predictions for both and Vu and Vf.


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