scholarly journals Diagonal Cracking Capacity and Ultimate Shear Strength of Slender RC Beams without Web Reinforcement

2014 ◽  
Vol 8 (1) ◽  
pp. 97-112 ◽  
Author(s):  
Mohammed Shukri Al-Zoubi ◽  
Keyword(s):  
Shear Strength ◽  
Rc Beams ◽  
Ultimate Shear Strength ◽  
Web Reinforcement

scholarly journals SHEAR STRENGTH OF NATURAL PORCELINITE LIGHTWEIGHT AGGREGATE RC BEAMS WITH WEB REINFORCEMENT

2018 ◽  
Vol 22 (02) ◽  
pp. 135-149
Author(s):  
Mutaz Kadhim Al-Dhalimi ◽  
◽  
Kais Fuad Sarsam ◽  
Keyword(s):  
Shear Strength ◽  
Lightweight Aggregate ◽  
Rc Beams ◽  
Web Reinforcement

Shear strength predicting of FRP-strengthened RC beams by using artificial neural networks

2014 ◽  
Vol 21 (2) ◽  
pp. 239-255 ◽  
Author(s):  
Gunnur Yavuz ◽  
Musa Hakan Arslan ◽  
Omer Kaan Baykan
Keyword(s):  
Neural Networks ◽  
Shear Strength ◽  
Artificial Neural Networks ◽  
Back Propagation ◽  
Fiber Reinforced Polymers ◽  
Rc Beams ◽  
Ann Model ◽  
Ultimate Shear Strength ◽  
Existing Building ◽  
Artificial Neural

AbstractIn this study, the efficiency of artificial neural networks (ANN) in predicting the shear strength of reinforced concrete (RC) beams, strengthened by means of externally bonded fiber-reinforced polymers (FRP), is explored. Experimental data of 96 rectangular RC beams from an existing database in the literature were used to develop the ANN model. Eight different input parameters affecting the shear strength were selected for creating the ANN structure. Each parameter was arranged in an input vector and a corresponding output vector that includes the shear strength of the RC beam. For all outputs, the ANN model was trained and tested using a three-layered back-propagation method. The initial performance of back-propagation was evaluated and discussed. In addition, the accuracy of well-known building codes in predicting the shear strength of FRP-strengthened RC beams was also examined, in a comparable way, using same test data. The study shows that the ANN model gives reasonable predictions of the ultimate shear strength of RC beams (R2≈0.93). Moreover, the study concludes that the ANN model predicts the shear strength of FRP-strengthened RC beams better than existing building code approaches.

scholarly journals Modelling of Shear Strength for Reinforced Concrete Beams Provided with Side-Face Reinforcement in Dependence of Crack Inclination Angle

2019 ◽  
Vol 8 (6) ◽  
pp. 3941-3950
Keyword(s):  
Shear Strength ◽  
Reinforced Concrete ◽  
Inclination Angle ◽  
Concrete Beams ◽  
Concrete Strength ◽  
Reinforced Concrete Beams ◽  
Rc Beams ◽  
Shear Design ◽  
Web Reinforcement ◽  
Side Face

Shear behavior of reinforced concrete beams (RCbeams) is proved to be influenced by different parameters such as web reinforcement, beam size, shear span-to-depth ratio, concrete strength, and longitudinal reinforcement. In addition to these parameters, researches acknowledge the significant contribution of side-face reinforcement (SFR) in shear strength of RC-beams. This paper aims at proposing a new model for predicting shear strength of RC-beams that accounts for the contribution of SFR in shear strength along with the other above-mentioned parameters. An explicit formula is derived based on a mechanical conceptual model that considers the variation of the inclination angle of diagonal shear cracking. The derived formula is verified on the basis of numerical analysis results in addition to the available results from relevant experimental researches in literature. Reliability of the proposed formula is investigated compared to design provisions in different codes. Results demonstrates that the proposed formula is more capable of predicting shear strength of RC-beams provided with SFR rather than shear design codes. Consistency of the proposed formula in predicting shear strength implies that the mechanical concept, on which the proposed formula is derived, is in consistent with the actual mechanical behavior.

scholarly journals Shear strength of RC beams without web reinforcement

2016 ◽  
Vol 17 (1) ◽  
pp. 87-96 ◽  
Author(s):  
Tao Zhang ◽  
Phillip Visintin ◽  
Deric J. Oehlers
Keyword(s):  
Shear Strength ◽  
Rc Beams ◽  
Web Reinforcement
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