In this study, an artificial neural network (ANN) model for studying the strength properties of steel fiber reinforced concrete (SFRC) containing fly ash was devised. The mixtures were prepared with 0 wt%, 15 wt%, and...In this study, an artificial neural network (ANN) model for studying the strength properties of steel fiber reinforced concrete (SFRC) containing fly ash was devised. The mixtures were prepared with 0 wt%, 15 wt%, and 30 wt% of fly ash, at 0 vol.%, 0.5 vol.%, 1.0 vol.% and 1.5 vol.% of fiber, respectively. After being cured under the standard conditions for 7, 28, 90 and 365 d, the specimens of each mixture were tested to determine the corresponding compressive and flexural strengths. The pa- rameters such as the amounts of cement, fly ash replacement, sand, gravel, steel fiber, and the age of samples were selected as input variables, while the compressive and flexural strengths of the concrete were chosen as the output variables. The back propagation learning algorithm with three different variants, namely the Levenberg-Marquardt (LM), scaled conjugate gradient (SCG) and Fletcher-Powell conjugate gradient (CGF) algorithms were used in the network so that the best approach can be found. The results obtained from the model and the experiments were compared, and it was found that the suitable algorithm is the LM algorithm. Furthermore, the analysis of variance (ANOVA) method was used to determine how importantly the experimental parameters affect the strength of these mixtures.展开更多
Due to the inherent property of concrete being very weak in tension, efforts have been made to overcome this deficiency by adding various type of fibers like carbon fiber reinforced polymer (CFRP), glass fiber reinfor...Due to the inherent property of concrete being very weak in tension, efforts have been made to overcome this deficiency by adding various type of fibers like carbon fiber reinforced polymer (CFRP), glass fiber reinforced polymer (GFRP), polypropylene fiber (PPF) and stainlesssteel fiber (SSF) smeared into the concrete mix. The present study involves experimental investigation on the use of GFRP, CFRP and SSF fibers alone or as combination to improve the mechanical properties of concrete. Furthermore, concrete cylinders were cast and tested for compression and tension using 10% fly ash as cement replacement in all specimens. Besides fiber material types, fiber reinforcement ratios of 1% and 1.5% were tested to investigate the mechanical properties of concrete. In all concrete cylinder tests, the fiber reinforcement ratio of 1% had a significant contribution in increasing the tensile strength as oppose to compressive strength. As a result, the tensile and compressive strengths were increased by 26% and 11%, respectively as compared to the control specimen. Increasing the fiber reinforcement ratio from 1% to 1.5%, resulted in diminishing the mechanical properties of concrete. However, reduction in concrete compressive strength was more prominent than the tensile strength. Furthermore, it was observed that, the crack propagation was decreased with the increase of fiber content when compared to the control specimen.展开更多
文摘In this study, an artificial neural network (ANN) model for studying the strength properties of steel fiber reinforced concrete (SFRC) containing fly ash was devised. The mixtures were prepared with 0 wt%, 15 wt%, and 30 wt% of fly ash, at 0 vol.%, 0.5 vol.%, 1.0 vol.% and 1.5 vol.% of fiber, respectively. After being cured under the standard conditions for 7, 28, 90 and 365 d, the specimens of each mixture were tested to determine the corresponding compressive and flexural strengths. The pa- rameters such as the amounts of cement, fly ash replacement, sand, gravel, steel fiber, and the age of samples were selected as input variables, while the compressive and flexural strengths of the concrete were chosen as the output variables. The back propagation learning algorithm with three different variants, namely the Levenberg-Marquardt (LM), scaled conjugate gradient (SCG) and Fletcher-Powell conjugate gradient (CGF) algorithms were used in the network so that the best approach can be found. The results obtained from the model and the experiments were compared, and it was found that the suitable algorithm is the LM algorithm. Furthermore, the analysis of variance (ANOVA) method was used to determine how importantly the experimental parameters affect the strength of these mixtures.
文摘Due to the inherent property of concrete being very weak in tension, efforts have been made to overcome this deficiency by adding various type of fibers like carbon fiber reinforced polymer (CFRP), glass fiber reinforced polymer (GFRP), polypropylene fiber (PPF) and stainlesssteel fiber (SSF) smeared into the concrete mix. The present study involves experimental investigation on the use of GFRP, CFRP and SSF fibers alone or as combination to improve the mechanical properties of concrete. Furthermore, concrete cylinders were cast and tested for compression and tension using 10% fly ash as cement replacement in all specimens. Besides fiber material types, fiber reinforcement ratios of 1% and 1.5% were tested to investigate the mechanical properties of concrete. In all concrete cylinder tests, the fiber reinforcement ratio of 1% had a significant contribution in increasing the tensile strength as oppose to compressive strength. As a result, the tensile and compressive strengths were increased by 26% and 11%, respectively as compared to the control specimen. Increasing the fiber reinforcement ratio from 1% to 1.5%, resulted in diminishing the mechanical properties of concrete. However, reduction in concrete compressive strength was more prominent than the tensile strength. Furthermore, it was observed that, the crack propagation was decreased with the increase of fiber content when compared to the control specimen.
