Abstract
In this paper, a new model is proposed to predict the ultimate strength of FRP and conventional reinforced concrete confined by lateral steel bars. Accordingly, circular specimens models are developed and investigated using an Artificial Neural Network (ANN) technique. To study the effect of the various parameters, e.g., the strength of unconfined concrete, the diameter of concrete samples, the height of the samples, tensile strength of FRP and conventional lateral steel, the thickness of FRP layers, the diameter of lateral steel stirrups, the strength of lateral steel stirrups, and modulus of elasticity of FRP and lateral steel stirrups, were selected. The proposed model is trained, validated, and tested based on 49 samples collected from the literature. Moreover, based on the developed ANN model, a set of design-based equations and charts is recommended. In addition to the samples utilized in developing the proposed model, further new samples are selected to evaluate the accuracy of the proposed model. The results from both ANN and user-friendly equations and charts show a good agreement with the test results. Moreover, parametric study is conducted to compare the performance of the proposed model against the experiments and numerical models in the literature. The parametric study shows that the ANN models possess better accuracy and performance to predict the ultimate strength of FRP and conventional steel-reinforced concrete confined specimens, for which the influence of important parameters is considered.
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References
ACI Committee 440. (2008). Guide for the design and construction of externally bonded FRP systems for strengthening concrete structures (ACI 440.2R-08). Farmington Hills, MI: American Concrete Institute.
Benzaid, R., Mesbah, H., & Chikh, N. E. (2010). FRP-confined concrete cylinders: Axial compression experiments and strength model. The Journal of Reinforced Plastics and Composites, 29(16), 2469–2488. https://doi.org/10.1177/0731684409355199.
Cevik, A. (2011). Modeling strength enhancement of FRP confined concrete cylinders using soft computing. Expert Systems with Applications, 38(5), 5662–5673. https://doi.org/10.1016/j.eswa.2010.10.069.
Cevik, A., & Guzelbey, I. H. (2008). Neural network modeling of strength enhancement for CFRP confined concrete cylinders. Building and Environment, 43(5), 751–763. https://doi.org/10.1016/j.buildenv.2007.01.036.
Chastre, C., & Silva, M. A. G. (2010). Monotonic axial behavior and modelling of RC circular columns confined with CFRP. Engineering Structures, 32(8), 2268–2277. https://doi.org/10.1016/j.engstruct.2010.04.001.
Eid, R., & Paultre, P. (2008). Analytical model for FRP-confined circular reinforced concrete columns. Journal of Composites for Construction, 12(5), 541–552. https://doi.org/10.1061/(ASCE)1090-0268(2008)12:5(541).
Eid, R., Roy, N., & Paultre, P. (2006). Tests of axially loaded circular reinforced concrete columns strengthened with FRP sheets. CRGP Rep. No. 3.
Elsanadedy, H. M., Al-Salloum, Y. A., Alsayed, S. H., & Iqbal, R. A. (2012). Experimental and numerical investigation of size effects in FRP-wrapped concrete columns. Construction and Building Materials, 29, 56–72. https://doi.org/10.1016/j.conbuildmat.2011.10.025.
Graupe, D. (2007). Principles of artificial neural networks (2nd ed.). Singapore: World Scientific.
Hamid, F. (2015) Concrete confinement with FRP systems. The University of Sheffield.
Harajli, M. H., Hantouche, E., & Soudki, K. (2006). Stress–strain model for fiber-reinforced polymer jacketed concrete columns. ACI Structural Journal, 103(5), 672–682.
Hu, H., & Seracino, R. (2013). Analytical model for FRP-and-steel-confined circular concrete columns in compression. Journal of Composites for Construction, 18(SPECIAL ISSUE: 10th Anniversary of IIFC), 4013012. https://doi.org/10.1061/(ASCE)CC.1943-5614.0000394.
Ilki, A., Peker, O., Karamuk, E., Demir, C., & Kumbasar, N. (2008). FRP retrofit of low and medium strength circular and rectangular reinforced concrete columns. Journal of Materials in Civil Engineering, 20(2), 169–188. https://doi.org/10.1061/(ASCE)0899-1561(2008)20:2(169).
Jalal, M., & Ramezanianpour, A. A. (2012). Strength enhancement modeling of concrete cylinders confined with CFRP composites using artificial neural networks. Composites Part B: Engineering, 43(8), 2990–3000. https://doi.org/10.1016/j.compositesb.2012.05.044.
Kawashima, K., Hosotani, M., & Yoneda, K. (2000) Carbon fiber sheet retrofit of reinforced concrete bridge piers. In Proc. international workshop on annual commemoration of Chi-Chi Earthquake, National Center for Research on Earthquake Engineering, Taipei, Taiwan, ROC (no. 11, pp. 124–135).
Lam, L., & Teng, J. G. (2003). Design-oriented stress–strain model for FRP-confined concrete. Construction and Building Materials, 17(03), 471–489. https://doi.org/10.1016/S0950-0618(03)00045-X.
Lee, W. T., Chiou, Y. J., & Shih, M. H. (2010a). Reinforced concrete beam–column joint strengthened with carbon fiber reinforced polymer. Composite Structures, 92(1), 48–60. https://doi.org/10.1016/j.compstruct.2009.06.011.
Lee, J.-Y., Yi, C.-K., Jeong, H.-S., Kim, S.-W., & Kim, J.-K. (2010b). Compressive response of concrete confined with steel spirals and frp composites. Journal of Composite Materials, 44(4), 481–504. https://doi.org/10.1177/0021998309347568.
Leung, C. K. Y., Ng, M. Y. M., & Luk, H. C. Y. (2006). Empirical approach for determining ultimate FRP strain in FRP-strengthened concrete beams. Journal of Composites for Construction, 10(2), 125–138. https://doi.org/10.1061/(ASCE)1090-0268(2006)10:2(125).
Mander, J. B., Priestley, M. J. N., & Park, R. (1988). Theoretical stress–strain model for confined concrete. Journal of the Structural Engineering. American Society of Civil Engineers, 114(8), 1804–1826.
Mansouri, I., Ozbakkaloglu, T., & Kisi, O. (2016). Predicting behavior of FRP-confined concrete using neuro fuzzy, neural network, multivariate adaptive regression splines and M5 model tree techniques. Materials and Structures. https://doi.org/10.1617/s11527-015-0790-4.
MATLAB. (2018). https://uk.mathworks.com/.
Matthys, S., Toutanji, H., & Taerwe, L. (2006). Stress–strain behavior of large-scale circular columns confined with FRP composites. Journal of the Structural Engineering. American Society of Civil Engineers, 132(1), 123–133.
Naderpour, H., Kheyroddin, A., & Amiri, G. G. (2010). Prediction of FRP-confined compressive strength of concrete using artificial neural networks. Composite Structures, 92(12), 2817–2829. https://doi.org/10.1016/j.compstruct.2010.04.008.
Ozbakkaloglu, T., Lim, J. C., & Vincent, T. (2013). FRP-confined concrete in circular sections: Review and assessment of stress–strain models. Engineering Structures, 49, 1068–1088. https://doi.org/10.1016/j.engstruct.2012.06.010.
Pellegrino, C., & Modena, C. (2010). Analytical model for FRP confinement of concrete columns with and without internal steel reinforcement. Journal of Composites for Construction, 14(6), 693–705. https://doi.org/10.1061/(ASCE)CC.1943-5614.0000127.
Richart, F. E., Brandtzæg, A., & Brown, R. L. (1928). A study of the failure of concrete under combined compressive stresses. University of Illinois at Urbana Champaign, College of Engineering. Engineering Experiment Station.
Shirmohammadi, F., Esmaeily, A., & Kiaeipour, Z. (2015). Stress–strain model for circular concrete columns confined by FRP and conventional lateral steel. Engineering Structures, 84, 395–405. https://doi.org/10.1016/j.engstruct.2014.12.005.
Spoelstra, M. R., & Monti, G. (1999). FRP-confined concrete model. Journal of Composites for Construction, 3(3), 143–150.
Teng, J. G., Lin, G., & Yu, T. (2014). Analysis-oriented stress–strain model for concrete under combined FRP-steel confinement. Journal of Composites for Construction. https://doi.org/10.1061/(ASCE)CC.1943-5614.0000549.
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Hamid, F.L., Jumaa, G.B. & Weli, S.S. Predicting ultimate strength of FRP and lateral steel confined circular concrete columns using Artificial Neural Networks. Asian J Civ Eng 22, 493–503 (2021). https://doi.org/10.1007/s42107-020-00328-x
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DOI: https://doi.org/10.1007/s42107-020-00328-x