Prediction of the ultimate strength of reinforced concrete beams FRP-strengthened in shear using neural networks |
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| Authors: | R. Perera M. Barchín A. Arteaga A. De Diego |
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| Affiliation: | 1. Department of Structural Mechanics, Technical University of Madrid, José Gutiérrez Abascal 2, Madrid 28006, Spain;2. Eduardo Torroja Institute for Construction Science, CSIC, Serrano Galvache 4, Madrid 28033, Spain;1. Department of Civil Engineering, Universiti Putra Malaysia, Malaysia;2. The Engineering Affairs Department, Baghdad University, Iraq;1. Department of Structural Mechanics, Technical University of Madrid, Jose Gutierrez Abascal 2, 28006 Madrid, Spain;2. Eduardo Torroja Institute for Construction Science, CSIC, Serrano Galvache 4, 28003 Madrid, Spain;1. School of Mechatronic Engineering, Xi’an Technological University, Xi’an 710021 China;2. Department of Civil Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia;3. Department of Civil Engineering, College of Engineering, Prince Sattam bin Abdulaziz University, Al-kharj 11942, Saudi Arabia;4. Department of Civil Engineering, Al-Qalam University College, Kirkuk, Iraq;5. Research Center, Sulaimani Polytechnic University, Sulaimani 46001, Kurdistan Region, Iraq;6. Department of Computer, College of Science, University of Halabja, Halabja 46018, Kurdistan Region, Iraq;7. Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Viet Nam;8. Faculty of Social Sciences and Humanities, Ton Duc Thang University, Ho Chi Minh City, Viet Nam;9. Institute of Research and Development, Duy Tan University, Da Nang 550000, Viet Nam;10. Department of Civil Engineering, College of Engineering, King Saud University, Riyadh 11362, Saudi Arabia |
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| Abstract: | In the last years, a great number of experimental tests have been performed to determine the ultimate strength of reinforced concrete beams retrofitted in shear by means of externally bonded fibre-reinforced polymers (FRP). Most of design proposals for shear strengthening are based on a regression analysis from experimental data corresponding to specific configurations which makes very difficult to capture the real interrelation among the involved parameters. To avoid this, an artificial neural network has been developed to predict the shear strength of concrete beams reinforced with this method from previous tests. Furthermore, a parametric study has been carried out to determine the influence of some beam and external reinforcement parameters on the shear strength with the purpose of reaching more reliable designs. Finally, some modifications of the design expressions are proposed and checked with experimental results. |
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