scholarly journals Performance comparison of neural network training algorithms in the modeling properties of steel fiber reinforced concrete

Heliyon ◽  
2019 ◽  
Vol 5 (1) ◽  
pp. e01115 ◽  
Author(s):  
T.F. Awolusi ◽  
O.L. Oke ◽  
O.O. Akinkurolere ◽  
A.O. Sojobi ◽  
O.G. Aluko
2017 ◽  
Vol 59 (7-8) ◽  
pp. 653-660 ◽  
Author(s):  
Wang Yan ◽  
Ge Lu ◽  
Chen Shi Jie ◽  
Zhou Li ◽  
Zhang Ting Ting

2021 ◽  
pp. 136943322098165
Author(s):  
Hossein Saberi ◽  
Farzad Hatami ◽  
Alireza Rahai

In this study, the co-effects of steel fibers and FRP confinement on the concrete behavior under the axial compression load are investigated. Thus, the experimental tests were conducted on 18 steel fiber-reinforced concrete (SFRC) specimens confined by FRP. Moreover, 24 existing experimental test results of FRP-confined specimens tested under axial compression are gathered to compile a reliable database for developing a mathematical model. In the conducted experimental tests, the concrete strength was varied as 26 MPa and 32.5 MPa and the steel fiber content was varied as 0.0%, 1.5%, and 3%. The specimens were confined with one and two layers of glass fiber reinforced polymer (GFRP) sheet. The experimental test results show that simultaneously using the steel fibers and FRP confinement in concrete not only significantly increases the peak strength and ultimate strain of concrete but also solves the issue of sudden failure in the FRP-confined concrete. The simulations confirm that the results of the proposed model are in good agreement with those of experimental tests.


1984 ◽  
Vol 21 (3) ◽  
pp. 108-111
Author(s):  
V. S. Sterin ◽  
V. A. Golubenkov ◽  
G. S. Rodov ◽  
B. V. Leikin ◽  
L. G. Kurbatov

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