Flexural strengthening of corroded steel beams with CFRP by using the end anchorage: Experimental, numerical, and machine learning methods
Source abstract
Abstract
This article presents the mechanical behavior of corroded steel beams that have been strengthened with carbon fiber-reinforced polymer (CFRP) layers in order to mitigate the effects of corrosion. Six beams are analyzed experimentally, including unreinforced and CFRP-reinforced specimens, with regard to the corrosion percentage, location, and shape on strength, ductility, and modes of failure. In the beam with 50% corrosion, reinforcing with CFRP compensated for the strength reduction. In the beam with 100% corrosion, after CFRP reinforcement, the strength was only 4% lower than that of the control beam. A new end anchorage system was developed to avoid CFRP slippage, ensuring full utilization of its tensile capacity. Numerical modeling further validated the experimental results and then numerical specimens were used for parametric and Machine Learning (ML) studies. The results indicated that corrosion in the upper flange gave the most severe strength reduction up to 39.7%, although this was effectively mitigated by CFRP reinforcement. The ML prediction showed that the CatBoost algorithm had the highest accuracy, with an R 2 score of 0.954. Additionally, the feature importance analysis revealed that the location and level of the corrosion are the most influential features affecting the reduction in the capacity of the corroded beam.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Structural Behavior of Reinforced Concrete · Concrete Corrosion and Durability · Structural Load-Bearing Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (72)
Show source-provided references
1. Failure mode analyses of reinforced concrete beams strengthened in flexure with externally bonded fiber-reinforced polymers10.1061/(ASCE)1090-0268(2004)8:2(123) ↗
2. Axially-compressed behavior of deficient short steel columns strengthened with carbon-FRP
3. Effects of horizontal deficiency location on the structural behaviors of steel SHS short columns strengthened using CFRP
4. Effects of vertical deficiency location on the structural behavior of steel SHS short columns
5. Axially-compressed behavior of CFRP strengthening steel short columns having defects
6. Experimental investigation on corroded cold-formed steel beam-columns under compression and major axis bending10.1016/j.jcsr.2020.106026 ↗
7. An experimental, analytical and numerical study of the static behavior of steel beams reinforced by pultruded CFRP strips10.1016/j.compositesb.2005.03.002 ↗
8. Design of short CFRP-reinforced steel tubular columns10.1016/j.jcsr.2010.09.005 ↗
9. Failure analysis and structural behaviour of CFRP strengthened steel I-beams10.1016/j.conbuildmat.2011.11.009 ↗
10. Experimental study on CFST members strengthened by CFRP composites under compression10.1016/j.jcsr.2011.10.014 ↗
11. CFRP strengthening and rehabilitation of degraded steel welded RHS beams under combined bending and bearing
12. Flexural strength of hybrid steel I-beams based on slenderness10.1016/j.engstruct.2015.03.029 ↗
13. Experimental study on the fatigue behaviour of cracked steel beams repaired with CFRP plates10.1016/j.engfracmech.2015.04.009 ↗
14. Theoretical and experimental study on notched steel beams strengthened with CFRP plate10.1016/j.compstruct.2015.10.024 ↗
15. Performance of steel beams strengthened with pultruded CFRP plate under various exposures10.12989/scs.2016.20.5.999 ↗
16. Experimental and analytical investigations on the flexural behavior of CFRP-strengthened composite girders10.1016/j.jcsr.2016.01.010 ↗
17. Rehabilitation of corroded steel beams using BFRP Fabric10.1016/j.istruc.2018.06.006 ↗
18. Experimental study on CFRP-strengthened steel beams10.1016/j.compositesb.2018.04.060 ↗
19. Flexural strength of steel I-beams reinforced with CFRP sheets at tension flange10.1016/j.jcsr.2018.05.038 ↗
20. Flexural rehabilitation of steel beam with CFRP and BFRP fabrics – A comparative study10.1016/j.acme.2019.04.004 ↗
21. Experimental and theoretical investigation on flexural behavior of corroded steel beams strengthened by CFRP plate10.1007/s12205-020-2140-5 ↗
22. Corroded steel beams with various corrosion aspect ratios – A rehabilitation technique using basalt fibre fabric10.1016/j.engstruct.2020.111075 ↗
23. Retrofitting of steel beams using low-modulus carbon fiber reinforced polymer laminates10.1016/j.jcsr.2019.105825 ↗
24. CFRP-reinforced circular steel tubes with cutout under axial loading10.1016/j.jcsr.2019.105775 ↗
25. Numerical investigation on strengthening of steel beams for corrosion damage or web openings using carbon fiber reinforced polymer sheets10.3390/buildings14041069 ↗
26. Experimental study on CFRP reinforcement and static performance of CHS KT-joints10.1016/j.jcsr.2024.108618 ↗
27. Analytical study of CFRP strengthening steel plates with a semi-elliptical surface crack10.1016/j.jcsr.2023.108408 ↗
28. Insights into enhanced shear ductility and toughness of RC beam with fiber reinforced polymer-rubber support composite (FRP-RSC) strengthening system10.1016/j.engstruct.2024.118312 ↗
29. Analysis of shear behavior of RC beams strengthened using carbon fiber-reinforced polymer rubber support composites (CFRP-RSC) system under different shear span to depth ratios10.1016/j.engstruct.2024.119186 ↗
30. Steel corrosion induced shear performance deterioration of RC beams: experimental investigation and numerical simulation
31. Experimental investigation on fatigue behavior of wide-flange steel I-beams strengthened using different CFRP end cutting shapes10.1007/s13296-018-0160-5 ↗
32. ISO 630-2: Structural steels, Part 2: Technical delivery conditions for structural steels for general purposes. 2021.
33. Experimental study on failure modes of MF-CFRP strengthened steel beams10.1016/j.jcsr.2019.03.027 ↗
34. Variation of steel loss and its effect on the ultimate flexural capacity of RC beams corroded and repaired under load10.1016/j.conbuildmat.2009.11.012 ↗
35. Rotation capacity of H-section members as determined by local buckling10.1016/0143-974X(89)90008-4 ↗
36. Deformation capacity of steel structures10.1016/0143-974X(90)90024-B ↗
37. Mazzolani F., Piluso V. Evaluation of the rotation capacity of steel beams and beam-columns. 1992..
38. A study on local buckling behavior of hybrid beams
39. Georgescu D., Mazzolani F. The influence of the unsymmetrical post elastic properties of the structural steel on the rotation capacity of the beams. 1996..
40. Inelastic local and lateral buckling in design codes10.1061/(ASCE)0733-9445(1996)122:4(374) ↗
41. I interaction of plastic local and lateral buckling10.1061/(ASCE)0733-9445(1985)111:10(2181) ↗
42. Variation of ductility capacity of steel beam-columns10.1061/(ASCE)0733-9445(1994)120:7(1941) ↗
43. Construction AI of S · 2002
44. Mazzolani F., Piluso V. Member behavioural classes of steel beams and beam-columns. 1993..
45. Classification of I-section flexural members based on member ductility10.1016/j.jcsr.2013.12.004 ↗
46. Plastic mechanism analysis of unstiffened steel I-section beams strengthened with CFRP under 3-point bending
47. Fernando · 2010
48. Available rotation capacity of wide-flange beams and beam-columns Part 1. Theoretical approaches10.1016/S0143-974X(97)00044-8 ↗
49. Inelastic beams under moment gradient10.1061/JSDEAG.0001589 ↗
50. Structural performance of CFRP strengthened SHS beam-column connections subjected to monotonic loading: a numerical simulation10.1016/j.istruc.2024.106030 ↗
51. Numerical investigation of carbon fiber reinforced polymer confined concrete-filled steel tube columns under eccentric load
52. Strengthening reinforced concrete beams through integration of CFRP bars, mechanical anchorage system, and concrete jacketing10.3390/ma17122794 ↗
53. Machine learning for structural engineering: a state-of-the-art review10.1016/j.istruc.2022.02.003 ↗
54. Emerging artificial intelligence methods in structural engineering10.1016/j.engstruct.2018.05.084 ↗
55. A review of vibration-based damage detection in civil structures: from traditional methods to machine learning and deep learning applications10.1016/j.ymssp.2020.107077 ↗
56. Optimizing compressive strength prediction in eco-friendly recycled concrete via artificial intelligence models10.1007/s41939-024-00641-x ↗
57. Axial compressive strength predictive models for recycled aggregate concrete filled circular steel tube columns using ANN, GEP, and MLR
58. Structural damage detection in the wooden bridge using the fourier decomposition, time series modeling and machine learning methods
59. An integrated optimization and ANOVA approach for reinforcing concrete beams with glass fiber polymer
60. Bond strength prediction of externally bonded reinforcement on groove method (EBROG) using MARS-POA
61. Data-driven prediction of axial compression capacity of GFRP-reinforced concrete column using soft computing methods
62. Machine learning (ML) based models for predicting the ultimate bending moment resistance of high strength steel welded I-section beam under bending
63. Neural networks for inelastic distortional buckling capacity assessment of steel I-beams
64. Predicting the buckling behaviour of thin-walled structural elements using machine learning methods
65. Neural network application for distortional buckling capacity assessment of castellated steel beams10.1016/j.istruc.2020.07.027 ↗
66. Load-carrying capacity of locally corroded steel plate girder ends using artificial neural network
67. Artificial intelligence, machine learning, and deep learning in structural engineering: a scientometrics review of trends and best practices10.1007/s11831-022-09793-w ↗
68. Extremely randomized trees10.1007/s10994-006-6226-1 ↗
69. Advanced predictive modeling of shear strength in stainless-steel column web panels using explainable AI insights10.1016/j.rineng.2024.103454 ↗
70. A comparative analysis of gradient boosting algorithms10.1007/s10462-020-09896-5 ↗
71. Gradient boosting machines, a tutorial10.3389/fnbot.2013.00021 ↗
72. Chen · 2016 · 785