Predicting Crack Width in CFRP-Strengthened RC One-Way Slabs Using Hybrid Grey Wolf Optimizer Neural Network Model
This study deploys a hybrid Grey Wolf Optimizer Neural Network Model for predicting the crack width in reinforced concrete slabs strengthened with carbon fiber-reinforced polymers (CFRP). Reinforced concrete (RC) one-way slabs (1800 × 400 × 120 mm in size) were strengthened with CFRP with various le...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Buildings |
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| Online Access: | https://www.mdpi.com/2075-5309/12/11/1870 |
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| author | Seyed Vahid Razavi Tosee Iman Faridmehr Moncef L. Nehdi Vagelis Plevris Kiyanets A. Valerievich |
| author_facet | Seyed Vahid Razavi Tosee Iman Faridmehr Moncef L. Nehdi Vagelis Plevris Kiyanets A. Valerievich |
| author_sort | Seyed Vahid Razavi Tosee |
| collection | DOAJ |
| description | This study deploys a hybrid Grey Wolf Optimizer Neural Network Model for predicting the crack width in reinforced concrete slabs strengthened with carbon fiber-reinforced polymers (CFRP). Reinforced concrete (RC) one-way slabs (1800 × 400 × 120 mm in size) were strengthened with CFRP with various lengths (1800, 1100, and 700 mm) and subjected to four-point bending. The experimental results were compared to corresponding values for conventional RC slabs. The observed crack width results were recorded, and subsequently examined against the expression recommended by Eurocode 2. To estimate the crack width of CFRP-reinforced slabs, ANN combined with the Grey Wolf Optimizer algorithm was employed whereby the applied load, CFRP width/length, X/Y crack positions, and stress in steel reinforcement and concrete were defined as the input parameters. Experimental results showed that the larger the length and width of the carbon fiber, the smaller the maximum crack width in the tensile area of the slab at the final load step. On average, the crack width in slabs retrofitted with CFRP laminates increased by around 80% compared to a slab without CFRP. The results confirm that the equation provided by Eurocode 2 provides an unconservative estimation of crack widths for RC slabs strengthened with CFRP laminates. On the other hand, the results also confirm that the proposed informational model could be used as a reliable tool for estimating the crack width in RC slabs. The findings provide valuable insight into the design approaches for RC slabs and rehabilitation strategies for existing deficient RC slabs using CFRP. |
| first_indexed | 2024-03-09T19:12:53Z |
| format | Article |
| id | doaj.art-09959e1b17f646b3b9f7c4b2f07b34ed |
| institution | Directory Open Access Journal |
| issn | 2075-5309 |
| language | English |
| last_indexed | 2024-03-09T19:12:53Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Buildings |
| spelling | doaj.art-09959e1b17f646b3b9f7c4b2f07b34ed2023-11-24T03:58:59ZengMDPI AGBuildings2075-53092022-11-011211187010.3390/buildings12111870Predicting Crack Width in CFRP-Strengthened RC One-Way Slabs Using Hybrid Grey Wolf Optimizer Neural Network ModelSeyed Vahid Razavi Tosee0Iman Faridmehr1Moncef L. Nehdi2Vagelis Plevris3Kiyanets A. Valerievich4Department of Civil Engineering, Jundi-Shapur University of Technology, Dezful 18674-64616, IranDepartment of Building Construction and Structural Theory, South Ural State University, 76 pr. Lenina, 454080 Chelyabinsk, RussiaDepartment of Civil Engineering, McMaster University, Hamilton, ON L8S 4M6, CanadaDepartment of Civil and Architectural Engineering, College of Engineering, Qatar University, Doha P.O. Box 2713, QatarDepartment of Building Construction and Structural Theory, South Ural State University, 76 pr. Lenina, 454080 Chelyabinsk, RussiaThis study deploys a hybrid Grey Wolf Optimizer Neural Network Model for predicting the crack width in reinforced concrete slabs strengthened with carbon fiber-reinforced polymers (CFRP). Reinforced concrete (RC) one-way slabs (1800 × 400 × 120 mm in size) were strengthened with CFRP with various lengths (1800, 1100, and 700 mm) and subjected to four-point bending. The experimental results were compared to corresponding values for conventional RC slabs. The observed crack width results were recorded, and subsequently examined against the expression recommended by Eurocode 2. To estimate the crack width of CFRP-reinforced slabs, ANN combined with the Grey Wolf Optimizer algorithm was employed whereby the applied load, CFRP width/length, X/Y crack positions, and stress in steel reinforcement and concrete were defined as the input parameters. Experimental results showed that the larger the length and width of the carbon fiber, the smaller the maximum crack width in the tensile area of the slab at the final load step. On average, the crack width in slabs retrofitted with CFRP laminates increased by around 80% compared to a slab without CFRP. The results confirm that the equation provided by Eurocode 2 provides an unconservative estimation of crack widths for RC slabs strengthened with CFRP laminates. On the other hand, the results also confirm that the proposed informational model could be used as a reliable tool for estimating the crack width in RC slabs. The findings provide valuable insight into the design approaches for RC slabs and rehabilitation strategies for existing deficient RC slabs using CFRP.https://www.mdpi.com/2075-5309/12/11/1870crack widthCFRPartificial intelligenceneural networksconcrete slab |
| spellingShingle | Seyed Vahid Razavi Tosee Iman Faridmehr Moncef L. Nehdi Vagelis Plevris Kiyanets A. Valerievich Predicting Crack Width in CFRP-Strengthened RC One-Way Slabs Using Hybrid Grey Wolf Optimizer Neural Network Model Buildings crack width CFRP artificial intelligence neural networks concrete slab |
| title | Predicting Crack Width in CFRP-Strengthened RC One-Way Slabs Using Hybrid Grey Wolf Optimizer Neural Network Model |
| title_full | Predicting Crack Width in CFRP-Strengthened RC One-Way Slabs Using Hybrid Grey Wolf Optimizer Neural Network Model |
| title_fullStr | Predicting Crack Width in CFRP-Strengthened RC One-Way Slabs Using Hybrid Grey Wolf Optimizer Neural Network Model |
| title_full_unstemmed | Predicting Crack Width in CFRP-Strengthened RC One-Way Slabs Using Hybrid Grey Wolf Optimizer Neural Network Model |
| title_short | Predicting Crack Width in CFRP-Strengthened RC One-Way Slabs Using Hybrid Grey Wolf Optimizer Neural Network Model |
| title_sort | predicting crack width in cfrp strengthened rc one way slabs using hybrid grey wolf optimizer neural network model |
| topic | crack width CFRP artificial intelligence neural networks concrete slab |
| url | https://www.mdpi.com/2075-5309/12/11/1870 |
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