Comparative Study in Design of Fiber-Reinforced Concrete at Elevated Temperatures by Numerical Evaluation through Developed Hybrid Metaheuristic Algorithms
Fibrous concrete has good properties such as high ductility, high strength, suitable energy absorption and cracking resistance, which can be useful in many applications. This type of concrete is one of the best materials used in the construction of impact-resistant masonries, such as burial masonry...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-08-01
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| Series: | Buildings |
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| Online Access: | https://www.mdpi.com/2075-5309/13/8/2045 |
| _version_ | 1797585255806271488 |
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| author | Lihua Chen Harry Far Mina Mortazavi Adham E. Ragab |
| author_facet | Lihua Chen Harry Far Mina Mortazavi Adham E. Ragab |
| author_sort | Lihua Chen |
| collection | DOAJ |
| description | Fibrous concrete has good properties such as high ductility, high strength, suitable energy absorption and cracking resistance, which can be useful in many applications. This type of concrete is one of the best materials used in the construction of impact-resistant masonries, such as burial masonry structures, and explosive masonry warehouses. In this study, an artificial intelligence assessment based on the experimental test data from a laboratory has been performed on the fibrous concrete to evaluate the behavior of the samples at elevated temperatures and determine the most governing parameter on the mechanical properties of the fibrous concrete at elevated temperatures. For the first time, a hybrid intelligence algorithm has been developed based on the neural network structure using both genetic and swarm optimization algorithms. The ANFIS-PSO-GA (APG) algorithm was trained with experimental data and evaluated the flexural load and deflection of the samples. In order to detect the most prominent feature in the fire resistance of the fibrous concrete, five different subdatasets were designed. The results of the APG algorithm have been challenged with the ANFIS-PSO algorithm, which is a well-known hybrid numerical evaluation algorithm. As per the results, the newly designed APG algorithm has been successfully performed on both deflection and flexural prediction phases. Based on the numerical achievements, fiber features such as the fiber content and fiber mechanical properties are governing factors on the fibrous concrete resistance at elevated temperatures. |
| first_indexed | 2024-03-11T00:04:29Z |
| format | Article |
| id | doaj.art-8e1107cf6eb140e4ac3f32df5cb24db7 |
| institution | Directory Open Access Journal |
| issn | 2075-5309 |
| language | English |
| last_indexed | 2024-03-11T00:04:29Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Buildings |
| spelling | doaj.art-8e1107cf6eb140e4ac3f32df5cb24db72023-11-19T00:30:28ZengMDPI AGBuildings2075-53092023-08-01138204510.3390/buildings13082045Comparative Study in Design of Fiber-Reinforced Concrete at Elevated Temperatures by Numerical Evaluation through Developed Hybrid Metaheuristic AlgorithmsLihua Chen0Harry Far1Mina Mortazavi2Adham E. Ragab3Chongqing Vocational Institute of Engineering, Chongqing 402260, ChinaSchool of Civil and Environmental Engineering, Faculty of Engineering and Information Technology, University of Technology Sydney (UTS), Ultimo, NSW 2007, AustraliaSchool of Civil and Environmental Engineering, Faculty of Engineering and Information Technology, University of Technology Sydney (UTS), Ultimo, NSW 2007, AustraliaIndustrial Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi ArabiaFibrous concrete has good properties such as high ductility, high strength, suitable energy absorption and cracking resistance, which can be useful in many applications. This type of concrete is one of the best materials used in the construction of impact-resistant masonries, such as burial masonry structures, and explosive masonry warehouses. In this study, an artificial intelligence assessment based on the experimental test data from a laboratory has been performed on the fibrous concrete to evaluate the behavior of the samples at elevated temperatures and determine the most governing parameter on the mechanical properties of the fibrous concrete at elevated temperatures. For the first time, a hybrid intelligence algorithm has been developed based on the neural network structure using both genetic and swarm optimization algorithms. The ANFIS-PSO-GA (APG) algorithm was trained with experimental data and evaluated the flexural load and deflection of the samples. In order to detect the most prominent feature in the fire resistance of the fibrous concrete, five different subdatasets were designed. The results of the APG algorithm have been challenged with the ANFIS-PSO algorithm, which is a well-known hybrid numerical evaluation algorithm. As per the results, the newly designed APG algorithm has been successfully performed on both deflection and flexural prediction phases. Based on the numerical achievements, fiber features such as the fiber content and fiber mechanical properties are governing factors on the fibrous concrete resistance at elevated temperatures.https://www.mdpi.com/2075-5309/13/8/2045predictionartificial intelligenceANFISmechanical propertiesfiberconcrete |
| spellingShingle | Lihua Chen Harry Far Mina Mortazavi Adham E. Ragab Comparative Study in Design of Fiber-Reinforced Concrete at Elevated Temperatures by Numerical Evaluation through Developed Hybrid Metaheuristic Algorithms Buildings prediction artificial intelligence ANFIS mechanical properties fiber concrete |
| title | Comparative Study in Design of Fiber-Reinforced Concrete at Elevated Temperatures by Numerical Evaluation through Developed Hybrid Metaheuristic Algorithms |
| title_full | Comparative Study in Design of Fiber-Reinforced Concrete at Elevated Temperatures by Numerical Evaluation through Developed Hybrid Metaheuristic Algorithms |
| title_fullStr | Comparative Study in Design of Fiber-Reinforced Concrete at Elevated Temperatures by Numerical Evaluation through Developed Hybrid Metaheuristic Algorithms |
| title_full_unstemmed | Comparative Study in Design of Fiber-Reinforced Concrete at Elevated Temperatures by Numerical Evaluation through Developed Hybrid Metaheuristic Algorithms |
| title_short | Comparative Study in Design of Fiber-Reinforced Concrete at Elevated Temperatures by Numerical Evaluation through Developed Hybrid Metaheuristic Algorithms |
| title_sort | comparative study in design of fiber reinforced concrete at elevated temperatures by numerical evaluation through developed hybrid metaheuristic algorithms |
| topic | prediction artificial intelligence ANFIS mechanical properties fiber concrete |
| url | https://www.mdpi.com/2075-5309/13/8/2045 |
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