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In the current investigation, the influence of polyvinyl alcohol (PVA) fibers on flowability and durability of cementitious composite containing fly ash and nano-SiO2 was evaluated. PVA fibers were added into the composite at a volume fraction of 0.3%, 0.6%, 0.9%, and 1.2%. The flowability of the fresh cementitious composite was assessed using slump flow. The durability of cementitious composite includes carbonation resistance, permeability resistance, cracking resistance as well as freezing-thawing resistance, which were evaluated by the depth of carbonation, the water permeability height, cracking resistance ratio of the specimens, and relative dynamic elastic modulus of samples after freeze-thaw cycles, respectively. The results indicated that addition of PVA fibers had a little disadvantageous influence on flowability of cementitious composite, and the flowability of the fresh mixtures decreased with increases in PVA fiber content. Incorporation of PVA fibers significantly improved the durability of cementitious composites regardless of addition of nano-particles. When the fiber content was less than 1.2%, the durability indices of permeability resistance and cracking resistance increased with fiber content. However, the durability indices of carbonation resistance and freezing-thawing resistance began to decrease as the fiber dosage increased from 0.9% to 1.2%. The fiber reinforced cementitious composite exhibited better durability due to addition of nano-SiO2 particles. Nano-SiO2 particle improves microscopic structure of fiber reinforced cementitious composites, and the nano-particles are beneficial for PVA fibers to play the role of reinforcement in cementitious composites.

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In this study, the effects of polyvinyl alcohol (PVA) fiber content and nano-SiO2 (NS) on bending resistance of cementitious composites were investigated including bending strength and toughness. PVA fiber contents from 0.6% to 1.5% were added in the composites. The NS contents was 0% and 2% by mass. The water to binder ratio (w/b) was 0.38 for all composites. The specimens were cured for 28 days under 20∘C and relative humidity of 95% before bending test. The results show that the bending strength was improved with PVA fiber content increasing and the maximum bending strength was obtained at PVA fiber content of 1.5%. Although PVA fiber increased bending resistance regardless of NS addition, the optimal content was 1.2%. When the fiber content was less than 1.2%, the bending resistance of cementitious composites increased with fiber content. However, the toughness began to decrease as PVA fiber content increased from 1.2 % to 1.5%.2% NS addition decreased both bending strength and toughness due to the fact that NS was prone to self-desiccation and flock together, resulting in micro crack and strength loss.

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In this study, a method to optimize the mixing proportion of polyvinyl alcohol (PVA) fiber-reinforced cementitious composites and improve its compressive strength based on the Levenberg-Marquardt backpropagation (BP) neural network algorithm and genetic algorithm is proposed by adopting a three-layer neural network (TLNN) as a model and the genetic algorithm as an optimization tool. A TLNN was established to implement the complicated nonlinear relationship between the input (factors affecting the compressive strength of cementitious composite) and output (compressive strength). An orthogonal experiment was conducted to optimize the parameters of the BP neural network. Subsequently, the optimal BP neural network model was obtained. The genetic algorithm was used to obtain the optimum mix proportion of the cementitious composite. The optimization results were predicted by the trained neural network and verified. Mathematical calculations indicated that the BP neural network can precisely and practically demonstrate the nonlinear relationship between the cementitious composite and its mixture proportion and predict the compressive strength. The optimal mixing proportion of the PVA fiber-reinforced cementitious composites containing nano-SiO2 was obtained. The results indicate that the method used in this study can effectively predict and optimize the compressive strength of PVA fiber-reinforced cementitious composites containing nano-SiO2.