Chopped Basalt Fiber Reinforced Photocatalytic Recycled Concrete Components

The disposal of construction and demolition waste（C&DW）by traditional landfill consumes land resources and causes air and water pollution.The C&DWs including recycled clay brick,recycled glass and recycled concrete are thereby crushed and sieved into recycled coarse and fine aggregates with different particle sizes.These recycled aggregates are then utilized to replace natural aggregates to prepare prefabricated components which are expected to reduce the emission of construction waste and meet the need of the construction industrialization of China.The prefabricated component consists of two layers,namely,the surface layer of photocatalytic mortar and the base layer of recycled concrete.The surface layer is the photocatalytic mortar prepared by recycled sands based composite photocatalysts,whilst the base layer is the recycled concrete reinforced by chopped basalt fiber.Regarding to this double-layer prefabricated component,the preparation and performance of recycled sand based composite photocatalysts,the preparation and performance of photocatalytic mortar,the preparation and performance of chopped basalt fiber reinforced recycled concrete,and the overall preparation and performance of components are studied.At length,some mathematical models based on the response surface methodology and the artificial neural network algorithm are established to fit and predict the experimental data.The innovation of the dissertation is mainly reflected by the followings.（1）Recycled sands were used to carry nanoscale titanium dioxide and to prepare composite photocatalystsRecycled aggregates were obtained from crushed and sieved C&DWs.The recycled aggregate with particle size ranging from 0.6 mm to 4.75 mm was defined as the recycled sand that contained the recycled clay brick sand,the recycled glass sand and the recycled concrete sand.It was proposed that the composite photocatalyst could be prepared by loading the nanoscale titanium dioxide（NT）onto recycled sands.The loading method meant to soak the recycled sand in the NT solution and to prepare the end product via a series of steps including soaking,placing,drying and sieving.Regarding to the composite photocatalyst,the optimal preparation process was determined and the effects of aggregate size,color and properties of parent concrete on the photocatalytic degradation of nitroxides and sulfur oxides were investigated.It was found that:1)the optimum concentration of nano-titanium dioxide solution for soaking recycled sands was 1%,and the optimal ratio of recycled sands to NT solution was80 vs.100.The optimal preparation condition of composite photocatalysts was ultrasonic vibration under 20k Hz for 1 h plus soaking for 48 h.2)through the observation of micro-morphology and the quantitative analysis by weighing method,about 1.3×10^-3 g to 4.6×10^-3 g nano-Ti O₂ was effectively loaded onto the surface or into the internal pores of per gram composite photocatalysts after drying and sieving.3)the photocatalytic efficiency of composite photocatalyst slumped with the increase of particle size.Under the same preparation condition,the photocatalytic efficiency of 0.6-1.18 mm photocatalyst was the highest,while that of 2.36-4.75 mm photocatalyst was the lowest,with the latter only 56%of the former.4)for recycled glass sands with varied colors,the photocatalytic efficiency slipped gradually with the deepening of color,and the transparent color had the highest photocatalytic efficiency.Its photocatalytic efficiency for sulfur dioxide of 1000 ppb was about twice as high as that of composite photocatalyst prepared by the black glass sands.5)the composite photocatalyst had a significant reuse performance and still maintained more than 90%photocatalytic efficiency after 5 photocatalytic cycles.（2）Composite photocatalysts were used to replace natural river sands and to prepare the surface layer of the photocatalytic mortarThe composite photocatalysts were,with a mass substitution rate of 0%,25%,50%,75%and 100%,to replace the natural river sand and to prepare the photocatalytic mortar.The substitution method was divided into the separate substitution and the compound substitution.The former referred to the replacement of natural river sand by the same type of composite photocatalyst,and latter meant overall replacement of natural river sand by two kinds of composite photocatalysts with three proportions of 0:100,25:75 and 50:50.It was found that,in comparison to the traditional direct mixing method,the recycled clay brick sand-based composite photocatalyst and the recycled glass sand-based composite photocatalyst replacing natural river sand at 75:25 lifted the photocatalytic efficiency of photocatalytic mortar by 71.7%and declined the cost by 80%.The composite photocatalyst of recycled glass sand and recycled clay brick sand improved the rheological property of recycled photocatalytic mortar.The yield stress and plastic viscosity of fresh mortar decreased by 35.38%and 28.73%respectively.In addition,the recycled clay brick powder was used to substitute metakaolin and then to inhibit the alkali aggregate reaction triggered by glass sands.When 30%of the cement was replaced by recycled clay brick powder,the 14-d expansion rate of mortar is 0.024%which was lower than the national standard limit of 0.03%.（3）Chopped basalt fiber was used to reinforce the recycled concreteThe optimal proportion of chopped basalt fiber reinforced recycled concrete was studied.Two dimensions,viz.the content of chopped basalt fiber and the replacement rate of recycled aggregate,at three levels were taken into consideration.The fiber content was 0%、0.25%and0.5%,whilst the substitution rate of recycled aggregate to natural aggregate was 0%,50%and100%.It was found that the optimum volume content of the chopped basalt fiber is 0.25%.Setting the performance of the concrete with 100%natural coarse aggregates as the benchmark,the compressive strength,the flexural strength,the splitting tensile strength,the specific strength and the compressive to flexural ratio of 100%recycled coarse aggregate concrete reinforced by 0.25%chopped basalt fiber were 96.93%,108.6%,106.63%,110.5%and112.04%,respectively.Main properties of the fiber reinforced recycled concrete thereby approached or even exceeded that of the natural concrete.Considering that the component was expected to hold a long-term and stable photocatalytic performance in practical use,the dissertation also studied the photocatalytic durability under the superimposed environmental effect and time effect.It was found that the degradation rate of nitrogen oxides slumped with the increase of curing time under both standard curing and carbonization curing conditions.Compared with the standard curing,carbonization curing had a more significant effect upon the photocatalytic efficiency in almost every phase.When the curing time was more than 56-d,the degradation rate of nitrogen oxides under the standard curing did not slip any more,but the photocatalytic efficiency under carbonization curing still slumped.In addition,under the extreme conditions such as the sandpaper polishing,the retained photocatalytic efficiency of the component could still reach above 90%.（4）Mathematical models established by the trend surface analysis,the artificial neural network algorithm and the adaptive neuro fuzzy inference system were used to analyze experimental dataThe mathematical models were established by the three-dimensional trend surface-based response surface methodology,the back propagation based artificial neural network method and the adaptative network based fuzzy inference system.The independent variables were the flow rate and the initial concentration of pollutants,whilst the dependent variable was the photocatalytic efficiency.It was found that,in comparison to the traditional one factor at one time method,the response surface model intuitively and clearly illustrated the synergistic effect.Nevertheless,limiting to the fitting equation that was established by the polynomial,the accuracy was relatively lower than that of the artificial neural network model and the statistical reliability was also lower than the latter.Due to the complex transfer function and the assigned weights and bias of different variables,the artificial neural network model decreased the deviation between the predicted value and the real value and also smoothed the fluctuation of the deviation.Nevertheless,the adaptative network based fuzzy inference system that was both intuitionistic and statistically accurate was fount the best to build the model.Basing on the model,the photocatalytic efficiency was negatively affected by both the initial concentration and the flow rate of the pollutant.