Neural network models to predict explosive spalling of PP fiber reinforced concrete under heating

2020 ◽  
Vol 32 ◽  
pp. 101472
Author(s):  
Jin-Cheng Liu ◽  
Zhigang Zhang
2020 ◽  
Vol 10 (7) ◽  
pp. 2324 ◽  
Author(s):  
Peng Zhang ◽  
Luoyi Kang ◽  
Juan Wang ◽  
Jinjun Guo ◽  
Shaowei Hu ◽  
...  

Steel-fiber-reinforced concrete (SFRC) is being increasingly applied to various buildings and civil infrastructure as an advanced cementitious composite. In recent years, the requirements for SFRC in the construction industry have increased. Additionally, the fire resistance of SFRC has attracted attention; therefore, numerous investigations regarding the residual properties of SFRC have been conducted. This paper critically reviews the mechanical properties of SFRC subjected to elevated temperatures, including its residual compressive strength, flexural strength, tensile strength, elastic properties, fracture properties, and stress–strain relationships. The residual mechanical performance of SFRC and the action mechanism of steel fibers are reviewed in detail. Moreover, factors affecting the explosive spalling of concrete at high temperatures as well as the effect of steel fibers on the microstructure of heated concrete are discussed. It is demonstrated that, in general, SFRC exhibits better residual mechanical properties when exposed to elevated temperatures than plain concrete and can prevent the risk of explosive spalling more effectively. The purpose of this literature review is to provide an exhaustive insight into the feasibility of SFRC as a refractory building material; additionally, future research needs are identified.


2014 ◽  
Vol 1035 ◽  
pp. 180-185 ◽  
Author(s):  
Nan Li ◽  
Jun Hai Zhao ◽  
Juan Wang ◽  
Qian Zhu

The complex nonlinear problem exists between the factors which influence the strength of hybrid fiber reinforced concrete. The nonlinear relationship between input variables as the factors and output variables as the strength can be obtained artificial neural network which have the feature of self-adapting, self-studying and nonlinear mapping. RBF and BP neural network models are established in MATLAB in this paper based on experimental values. Compressive strength and flexural strength of hybrid fiber reinforced concrete are predicted respectively and comparing with the measured values, predicted values are analyzed. The results show that the predicted values based on RBF tally with the experimental values, and the strength prediction ability of RBF is higher than BP neural network. The needs of engineering can be meet by this method with accurate prediction ability, a new method for the study of hybrid fiber reinforced concrete strength is provided.


2020 ◽  
Vol 14 (2) ◽  
pp. 6734-6742
Author(s):  
A. Syamsir ◽  
S. M. Mubin ◽  
N. M. Nor ◽  
V. Anggraini ◽  
S. Nagappan ◽  
...  

This study investigated the combine effect of 0.2 % drink cans and steel fibers with volume fractions of 0%, 0.5%, 1%, 1.5%, 2%, 2.5% and 3% to the mechanical properties and impact resistance of concrete. Hooked-end steel fiber with 30 mm and 0.75 mm length and diameter, respectively was selected for this study.  The drinks cans fiber were twisted manually in order to increase friction between fiber and concrete. The results of the experiment showed that the combination of steel fibers and drink cans fibers improved the strength performance of concrete, especially the compressive strength, flexural strength and indirect tensile strength. The results of the experiment showed that the combination of steel fibers and drink cans fibers improved the compressive strength, flexural strength and indirect tensile strength by 2.3, 7, and 2 times as compare to batch 1, respectively. Moreover, the impact resistance of fiber reinforced concrete has increase by 7 times as compared to non-fiber concretes. Moreover, the impact resistance of fiber reinforced concrete consistently gave better results as compared to non-fiber concretes. The fiber reinforced concrete turned more ductile as the dosage of fibers was increased and ductility started to decrease slightly after optimum fiber dosage was reached. It was found that concrete with combination of 2% steel and 0.2% drink cans fibers showed the highest compressive, split tensile, flexural as well as impact strength.    


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