Flexural strengthening of corroded steel beams with CFRP by using the end anchorage: Experimental, numerical, and machine learning methods
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...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-12-01
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| Series: | Case Studies in Construction Materials |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214509525007648 |
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| author | Amin Shabani Ammari Younes Nouri Habib Ghasemi Jouneghani Seyed Amin Hosseini Arash Rayegani Mehrdad Ebrahimi Pooria Heydari |
| author_facet | Amin Shabani Ammari Younes Nouri Habib Ghasemi Jouneghani Seyed Amin Hosseini Arash Rayegani Mehrdad Ebrahimi Pooria Heydari |
| author_sort | Amin Shabani Ammari |
| collection | DOAJ |
| description | 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 R2 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. |
| format | Article |
| id | doaj-art-c3cb36ef3bda4fe289d5ace074c98c01 |
| institution | Kabale University |
| issn | 2214-5095 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Case Studies in Construction Materials |
| spelling | doaj-art-c3cb36ef3bda4fe289d5ace074c98c012025-08-20T03:32:14ZengElsevierCase Studies in Construction Materials2214-50952025-12-0123e0496610.1016/j.cscm.2025.e04966Flexural strengthening of corroded steel beams with CFRP by using the end anchorage: Experimental, numerical, and machine learning methodsAmin Shabani Ammari0Younes Nouri1Habib Ghasemi Jouneghani2Seyed Amin Hosseini3Arash Rayegani4Mehrdad Ebrahimi5Pooria Heydari6Faculty of Marine Engineering, Chabahar Maritime University, Shahid Rigi Ave, Chabahar, Iran; Corresponding author.Department of Civil Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, IranDepartment of Civil Engineering, Shahid Rajaee Teacher Training University, Tehran, IranCivil Engineering Department, ISISE, ARISE, University of Coimbra, PortugalDepartment of Civil Engineering, Sharif University of Technology, Tehran, IranDepartment of Civil Engineering, K.N. Toosi University of Technology, Tehran, IranDepartment of Civil Engineering, Isfahan University of Technology (IUT), Isfahan, IranThis 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 R2 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.http://www.sciencedirect.com/science/article/pii/S2214509525007648Corroded steel beamsCFRPFlexural strengtheningEnd anchorage systemFlexural performanceMachine learning methods |
| spellingShingle | Amin Shabani Ammari Younes Nouri Habib Ghasemi Jouneghani Seyed Amin Hosseini Arash Rayegani Mehrdad Ebrahimi Pooria Heydari Flexural strengthening of corroded steel beams with CFRP by using the end anchorage: Experimental, numerical, and machine learning methods Case Studies in Construction Materials Corroded steel beams CFRP Flexural strengthening End anchorage system Flexural performance Machine learning methods |
| title | Flexural strengthening of corroded steel beams with CFRP by using the end anchorage: Experimental, numerical, and machine learning methods |
| title_full | Flexural strengthening of corroded steel beams with CFRP by using the end anchorage: Experimental, numerical, and machine learning methods |
| title_fullStr | Flexural strengthening of corroded steel beams with CFRP by using the end anchorage: Experimental, numerical, and machine learning methods |
| title_full_unstemmed | Flexural strengthening of corroded steel beams with CFRP by using the end anchorage: Experimental, numerical, and machine learning methods |
| title_short | Flexural strengthening of corroded steel beams with CFRP by using the end anchorage: Experimental, numerical, and machine learning methods |
| title_sort | flexural strengthening of corroded steel beams with cfrp by using the end anchorage experimental numerical and machine learning methods |
| topic | Corroded steel beams CFRP Flexural strengthening End anchorage system Flexural performance Machine learning methods |
| url | http://www.sciencedirect.com/science/article/pii/S2214509525007648 |
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