A new formulation for prediction of the shear capacity of FRP in strengthened reinforced concrete beams

The use of fiber-reinforced polymer (FRP) to strength the concrete beams is an efficient method in retrofitting of preexisting structures. The application of FRP sheets makes to have higher shear strength, but the common equations in determining the shear strength are no longer effective. In this paper, a new formulation is presented to predict the shear contribution of FRP in strengthened reinforced concrete beams. The formula is produced using the multigene genetic programming (MGP) machine. For this purpose, a set of experimental data is collected from the literature. The shear capacity of FRP in reinforced concrete (RC) beams is considered as the output data, while other variables are considered as the input data. MGP is trained with the experimental data and a formula is produced. The results of the proposed formula are compared with the experimental data to show the ability of the proposed formula. Also, these results are compared with those obtained from the available formulas, approximation models and published researches. Results show that the proposed formula is able to predict the shear capacity of FRP in strengthened RC beams with a higher precision than the other evaluated methods such as CIDAR, Fib.TG9.3, ACI and CSA. The mean absolute percentage error for the MGP formula was reduced about 74% in comparison with the CIDAR equations. Also, the root-mean-squared-error of the MGP formula was decreased near 71% in comparison with the Fib.TG9.3 equations.

[1]  J. Barros,et al.  Near surface mounted CFRP laminates for shear strengthening of concrete beams , 2006 .

[2]  Samaher AlJanabi,et al.  Multi Objectives Optimization to Gas Flaring Reduction from Oil Production , 2019, Big Data and Networks Technologies.

[3]  Omar Chaallal,et al.  Shear Strengthening of RC Beams with Externally Bonded FRP Composites: Effect of Strip-Width-to-Strip-Spacing Ratio , 2011 .

[4]  L. Lorenzis,et al.  Comparative Study of Models on Confinement of Concrete Cylinders with Fiber-Reinforced Polymer Composites , 2003 .

[5]  C. Leung,et al.  Shear Span–Depth Ratio Effect on Behavior of RC Beam Shear Strengthened with Full-Wrapping FRP Strip , 2016 .

[6]  D. Mertz,et al.  Shear Strengthening of Reinforced Concrete Beams Using Externally Applied Composite Fabrics , 1995 .

[7]  Laith Mohammad Abualigah,et al.  A combination of objective functions and hybrid Krill herd algorithm for text document clustering analysis , 2018, Eng. Appl. Artif. Intell..

[8]  A. C. Filho,et al.  IBRACON Structural Journal CFRP Composites on the Shear Strengthening of Reinforced Concrete Beams Compósitos de CFRP no Reforço ao Cisalhamento de Vigas de Concreto Armado , 2005 .

[9]  Laith Mohammad Abualigah,et al.  Unsupervised text feature selection technique based on hybrid particle swarm optimization algorithm with genetic operators for the text clustering , 2017, The Journal of Supercomputing.

[10]  Alex Li,et al.  Shear strengthening effect by bonded composite fabrics on RC beams , 2002 .

[11]  Markus Brameier,et al.  On linear genetic programming , 2005 .

[12]  Riadh Al-Mahaidi,et al.  Strength of Cfrp-steel double strap joints under impact loads using genetic programming , 2017 .

[13]  Samaher Hussein Ali,et al.  A novel tool (FP-KC) for handle the three main dimensions reduction and association rule mining , 2012, 2012 6th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT).

[14]  Laith Mohammad Abualigah,et al.  Hybrid clustering analysis using improved krill herd algorithm , 2018, Applied Intelligence.

[15]  Samaher Hussein Ali.  Novel Approach for Generating the Key of Stream Cipher System Using Random Forest Data Mining Algorithm , 2013, 2013 Sixth International Conference on Developments in eSystems Engineering.

[16]  C. Deniaud,et al.  REINFORCED CONCRETE T-BEAMS STRENGTHENED IN SHEAR WITH FIBER REINFORCED POLYMER SHEETS , 2003 .

[17]  Samaher AlJanabi,et al.  Smart system to create an optimal higher education environment using IDA and IOTs , 2018, International Journal of Computers and Applications.

[18]  Laith Mohammad Abualigah,et al.  A new feature selection method to improve the document clustering using particle swarm optimization algorithm , 2017, J. Comput. Sci..

[19]  Ali Nazari,et al.  Genetic programming in the simulation of Frp-to-concrete patch-anchored joints , 2016 .

[20]  Zhichao Zhang,et al.  Shear Strengthening of Reinforced Concrete Deep Beams Using Carbon Fiber Reinforced Polymer Laminates , 2004 .

[21]  Reza Kamgar,et al.  A Fuzzy Inference System in Constructional Engineering Projects to Evaluate the Design Codes for RC Buildings , 2018, Civil Engineering Journal.

[22]  Laith Mohammad Abualigah,et al.  APPLYING GENETIC ALGORITHMS TO INFORMATION RETRIEVAL USING VECTOR SPACE MODEL , 2015 .

[23]  Bernhard Sendhoff,et al.  Structure optimization of neural networks for evolutionary design optimization , 2005, Soft Comput..

[24]  Qing Li,et al.  Robust topology optimization for multiple fiber-reinforced plastic (FRP) composites under loading uncertainties , 2019, Structural and Multidisciplinary Optimization.

[25]  Nadia Nedjah,et al.  Genetic Systems Programming: Theory and Experiences , 2006, Studies in Computational Intelligence.

[26]  Dominic P. Searson,et al.  GPTIPS: An Open Source Genetic Programming Toolbox For Multigene Symbolic Regression , 2010 .

[27]  Alex Li,et al.  Shear strengthening effectiveness with CFF strips , 2003 .

[28]  T. Tanaka,et al.  SHEAR REINFORCING EFFECT OF CARBON FIBER SHEET ATTACHED TO SIDE OF REINFORCED CONCRETE BEAMS , 1996 .

[29]  Alireza Maheri,et al.  Seismic performance of ordinary RC frames retrofitted at joints by FRP sheets , 2010 .

[30]  B. Binici,et al.  Improving seismic performance of deficient reinforced concrete columns using carbon fiber-reinforced polymers , 2008 .

[31]  G. Monti,et al.  Tests and design equations for FRP-strengthening in shear , 2007 .

[32]  A. Gandomi,et al.  Nonlinear modeling of shear strength of SFRC beams using linear genetic programming , 2011 .

[33]  B. B. Adhikary,et al.  BEHAVIOR OF CONCRETE BEAMS STRENGTHENED IN SHEAR WITH CARBON-FIBER SHEETS , 2004 .

[34]  Sudhirkumar V. Barai,et al.  Effect of transverse steel on the performance of RC T-beams strengthened in shear zone with GFRP sheet , 2013 .

[35]  Ilker Fatih Kara,et al.  Prediction of shear strength of FRP-reinforced concrete beams without stirrups based on genetic programming , 2011, Adv. Eng. Softw..

[36]  C. Deniaud,et al.  Shear Behavior of Reinforced Concrete T-Beams with Externally Bonded Fiber-Reinforced Polymer Sheets , 2001 .

[37]  P. R. Walker,et al.  Shear strengthening of reinforced concrete beams using different configurations of externally bonded carbon fibre reinforced plates , 2003 .

[38]  N.H. Kaghed,et al.  Design and Implementation of Classification System for Satellite Images based on Soft Computing Techniques , 2006, 2006 2nd International Conference on Information & Communication Technologies.

[39]  Samaher Al-Janabi,et al.  Soft Mathematical System to Solve Black Box Problem through Development the FARB Based on Hyperbolic and Polynomial Functions , 2017, 2017 10th International Conference on Developments in eSystems Engineering (DeSE).

[40]  Laith Mohammad Abualigah,et al.  Feature Selection and Enhanced Krill Herd Algorithm for Text Document Clustering , 2018, Studies in Computational Intelligence.

[41]  Abang Abdullah Abang Ali,et al.  Shear capacity of precracked and non-precracked reinforced concrete shear beams with externally bonded bi-directional CFRP strips , 2008 .

[42]  A. Nanni,et al.  IMPROVING SHEAR CAPACITY OF EXISTING RC T-SECTION BEAMS USING CFRP COMPOSITES , 2000 .

[43]  Hosein Naderpour,et al.  A proposed model to estimate shear contribution of FRP in strengthened RC beams in terms of Adaptive Neuro-Fuzzy Inference System , 2017 .

[44]  Samaher Al-Janabi,et al.  A nifty collaborative analysis to predicting a novel tool (DRFLLS) for missing values estimation , 2019, Soft Computing.

[45]  O. Chaallal,et al.  Mechanisms of Shear Resistance of Concrete Beams Strengthened in Shear with Externally Bonded FRP , 2008 .

[46]  John R. Koza,et al.  Genetic programming as a means for programming computers by natural selection , 1994 .

[47]  S. H. Ali,et al.  Miner for OACCR: Case of medical data analysis in knowledge discovery , 2012, 2012 6th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT).

[48]  Omar Chaallal,et al.  Effect of transverse steel and shear span on the performance of RC beams strengthened in shear with CFRP , 2006 .

[49]  C. W. Dolan,et al.  Prestressed Concrete Beams Using Non-Metallic Tendons and External Shear Reinforcement , 1993 .

[50]  J. A. D. Sousa,et al.  Estruturas de Concreto Reforçadas com PRFC Parte II: Análise dos Modelos de Cisalhamento , 2010 .

[51]  H. M. Tanarslan,et al.  An approach for estimating the capacity of RC beams strengthened in shear with FRP reinforcements using artificial neural networks , 2012 .

[52]  P. Hamelin,et al.  Effect of external FRP retrofitting on reinforced concrete short columns for seismic strengthening , 2009 .

[53]  Chin-Hyung Lee,et al.  Prediction of shear strength of FRP-reinforced concrete flexural members without stirrups using artificial neural networks , 2014 .

[54]  H. Tanarslan.  Predicting the Capacity of RC Beams Strengthened in Shear with Side-Bonded FRP Reinforcements Using Artificial Neural Networks , 2011 .

[55]  Laith Mohammad Abualigah,et al.  Modified Krill Herd Algorithm for Global Numerical Optimization Problems , 2018, Advances in Nature-Inspired Computing and Applications.

[56]  Shoichi Inoue,et al.  SHEAR BEHAVIOR OF REINFORCED CONCRETE BEAM STRENGTHENED WITH CFRP SHEET , 1998 .

[58]  Guangming Chen,et al.  Behavior of RC Beams Shear Strengthened with Bonded or Unbonded FRP Wraps , 2009 .

[59]  B. Täljsten,et al.  Are Available Models Reliable for Predicting the FRP Contribution to the Shear Resistance of RC Beams , 2009 .

[60]  Jean-Daniel Berset.  Strengthening of reinforced concrete beams for shear using FRP composites , 1992 .

[61]  J. Teng,et al.  Debonding in RC Beams Shear Strengthened with Complete FRP Wraps , 2005 .

[62]  A. Gandomi,et al.  A data mining approach to compressive strength of CFRP-confined concrete cylinders , 2010 .

[63]  Samaher Al-Janabi,et al.  Evaluation prediction techniques to achievement an optimal biomedical analysis , 2019 .

[64]  Amjad J. Aref,et al.  A genetic algorithm-based multi-objective optimization for hybrid fiber reinforced polymeric deck and cable system of cable-stayed bridges , 2015, Structural and Multidisciplinary Optimization.

[65]  Vistasp M. Karbhari.  Rehabilitation of pipelines using fiber-reinforced polymer (FRP) composites , 2015 .

[66]  Stephanie L. Walkup,et al.  Guide for the Design and Construction of Externally Bonded FRP Systems for Strengthening Concrete Structures (ACI 440.2R-02) , 2005 .

[67]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[68]  F. Colomb,et al.  Seismic retrofit of reinforced concrete short columns by CFRP materials , 2008 .