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Abstrakt
In this paper, the feed-forward backpropagation neural network (FFBPNN) is used to propose a new formulation for predicting the compressive strength of fiber-reinforced polymer (FRP)-confined concrete cylinders. A set of experimental data has been considered in the analysis. The data include information about the dimensions of the concrete cylinders (diameter, length) and the total thickness of FRP layers, unconfined ultimate concrete strength, ultimate confinement pressure, ultimate tensile strength of the FRP laminates and the ultimate concrete strength of the concrete cylinders. The confined ultimate concrete strength is considered as the output data, while other parameters are considered as the input data. These parameters are mostly used in existing FRP-confined concrete models. Soft computing techniques are used to estimate the compressive strength of FRP-confined concrete cylinders. Finally, a new formulation is proposed. The results of the proposed formula are compared to the existing methods. To verify the proposed method, results are compared with other methods. The results show that the described method can forecast the compressive strength of FRP-confined concrete cylinders with high precision in comparison with the existing formulas. Moreover, the mean percentage of error for the proposed method is very low (3.49%). Furthermore, the proposed formula can estimate the ultimate compressive capacity of FRP-confined concrete cylinders with a different type of FRP and arbitrary thickness in the initial design of practical projects.
Cytowania
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Web of Science
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Autorzy (5)
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Reza Kamgar
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Hosein Naderpour
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Houman Ebrahimpour Komeleh
Cytuj jako
Pełna treść
- Wersja publikacji
- Accepted albo Published Version
- DOI:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.3390/app10051769
- Licencja
-
otwiera się w nowej karcie
Słowa kluczowe
Informacje szczegółowe
- Kategoria:
- Publikacja w czasopiśmie
- Typ:
- artykuły w czasopismach
- Opublikowano w:
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Applied Sciences-Basel
nr 10,
ISSN: 2076-3417 - Język:
- angielski
- Rok wydania:
- 2020
- Opis bibliograficzny:
- Kamgar R., Naderpour H., Komeleh H. E., Jakubczyk-Gałczyńska A., Jankowski R.: A Proposed Soft Computing Model for Ultimate Strength Estimation of FRP-Confined Concrete Cylinders// Applied Sciences-Basel -Vol. 10,iss. 5 (2020), s.1769-
- DOI:
- Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.3390/app10051769
- Źródła finansowania:
-
- COST_FREE
- Weryfikacja:
- Politechnika Gdańska
wyświetlono 99 razy
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