Shear Strength Prediction of Steel-Fiber-Reinforced Concrete Beams Using the M5P Model
This article presents a mathematical model developed using the M5P tree to predict the shear strength of steel-fiber-reinforced concrete (SFRC) for slender beams using soft computing techniques. This method is becoming increasingly popular for addressing complex technical problems. Other approaches,...
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MDPI AG
2023-04-01
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| author | Nadia Moneem Al-Abdaly Mahdi J. Hussein Hamza Imran Sadiq N. Henedy Luís Filipe Almeida Bernardo Zainab Al-Khafaji |
| author_facet | Nadia Moneem Al-Abdaly Mahdi J. Hussein Hamza Imran Sadiq N. Henedy Luís Filipe Almeida Bernardo Zainab Al-Khafaji |
| author_sort | Nadia Moneem Al-Abdaly |
| collection | DOAJ |
| description | This article presents a mathematical model developed using the M5P tree to predict the shear strength of steel-fiber-reinforced concrete (SFRC) for slender beams using soft computing techniques. This method is becoming increasingly popular for addressing complex technical problems. Other approaches, such as semi-empirical equations, can show known inaccuracies, and some soft computing methods may not produce predictive equations. The model was trained and tested using 332 samples from an experimental database found in the previous literature, and it takes into account independent variables such as the effective depth <i>d</i>, beam width <i>b<sub>w</sub></i>, longitudinal reinforcement ratio <i>ρ</i>, concrete compressive strength <i>f<sub>c</sub></i>, shear span to effective depth ratio <i>a</i>/<i>d</i>, and steel fiber factor <i>F<sub>sf</sub></i>. The predictive performance of the proposed M5P-based model was also compared with the one of existing models proposed in the previous literature. The evaluation revealed that the M5P-based model provided a more consistent and accurate prediction of the actual strength compared to the existing models, achieving an R<sup>2</sup> value of 0.969 and an RMSE value of 37.307 for the testing dataset. It was found to be a reliable and also straightforward model. The proposed model is likely to be highly helpful in assessing the shear capacity of SFRC beams during the pre-planning and pre-design stages and could also be useful to help for future revisions of design standards. |
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| issn | 2079-6439 |
| language | English |
| last_indexed | 2024-03-11T03:44:25Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Fibers |
| spelling | doaj.art-22b6991e152d45d3a0d6a7f5d9328d702023-11-18T01:18:40ZengMDPI AGFibers2079-64392023-04-011153710.3390/fib11050037Shear Strength Prediction of Steel-Fiber-Reinforced Concrete Beams Using the M5P ModelNadia Moneem Al-Abdaly0Mahdi J. Hussein1Hamza Imran2Sadiq N. Henedy3Luís Filipe Almeida Bernardo4Zainab Al-Khafaji5Department of Civil Engineering, Najaf Technical Institute, Al-Furat Al-Awsat Technical University, Najaf Munazira Str., Najaf 54003, IraqConstruction and Building Engineering Technologies Department, Najaf Engineering Technical College, Al-Furat Al-Awsat Technical University, Najaf Munazira Str., Najaf 54003, IraqDepartment of Environmental Science, College of Energy and Environmental Science, Alkarkh University of Science, Baghdad 10081, IraqDepartment of Civil Engineering, Mazaya University College, Nasiriya City 64001, IraqDepartment of Civil Engineering and Architecture, University of Beira Interior, 6201-001 Covilhã, PortugalBuilding and Construction Techniques Engineering Department, Al-Mustaqbal University College, Hillah 51001, IraqThis article presents a mathematical model developed using the M5P tree to predict the shear strength of steel-fiber-reinforced concrete (SFRC) for slender beams using soft computing techniques. This method is becoming increasingly popular for addressing complex technical problems. Other approaches, such as semi-empirical equations, can show known inaccuracies, and some soft computing methods may not produce predictive equations. The model was trained and tested using 332 samples from an experimental database found in the previous literature, and it takes into account independent variables such as the effective depth <i>d</i>, beam width <i>b<sub>w</sub></i>, longitudinal reinforcement ratio <i>ρ</i>, concrete compressive strength <i>f<sub>c</sub></i>, shear span to effective depth ratio <i>a</i>/<i>d</i>, and steel fiber factor <i>F<sub>sf</sub></i>. The predictive performance of the proposed M5P-based model was also compared with the one of existing models proposed in the previous literature. The evaluation revealed that the M5P-based model provided a more consistent and accurate prediction of the actual strength compared to the existing models, achieving an R<sup>2</sup> value of 0.969 and an RMSE value of 37.307 for the testing dataset. It was found to be a reliable and also straightforward model. The proposed model is likely to be highly helpful in assessing the shear capacity of SFRC beams during the pre-planning and pre-design stages and could also be useful to help for future revisions of design standards.https://www.mdpi.com/2079-6439/11/5/37machine learningsteel fiber reinforced concrete (SFRC)slender beamsshear strengthMP5 |
| spellingShingle | Nadia Moneem Al-Abdaly Mahdi J. Hussein Hamza Imran Sadiq N. Henedy Luís Filipe Almeida Bernardo Zainab Al-Khafaji Shear Strength Prediction of Steel-Fiber-Reinforced Concrete Beams Using the M5P Model Fibers machine learning steel fiber reinforced concrete (SFRC) slender beams shear strength MP5 |
| title | Shear Strength Prediction of Steel-Fiber-Reinforced Concrete Beams Using the M5P Model |
| title_full | Shear Strength Prediction of Steel-Fiber-Reinforced Concrete Beams Using the M5P Model |
| title_fullStr | Shear Strength Prediction of Steel-Fiber-Reinforced Concrete Beams Using the M5P Model |
| title_full_unstemmed | Shear Strength Prediction of Steel-Fiber-Reinforced Concrete Beams Using the M5P Model |
| title_short | Shear Strength Prediction of Steel-Fiber-Reinforced Concrete Beams Using the M5P Model |
| title_sort | shear strength prediction of steel fiber reinforced concrete beams using the m5p model |
| topic | machine learning steel fiber reinforced concrete (SFRC) slender beams shear strength MP5 |
| url | https://www.mdpi.com/2079-6439/11/5/37 |
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