The Activity Of Fly Ash To Stimulate Experimental Research, With High Volume Fly Ash Concrete

In this paper, the activation of fly-ash and the feasibility of high volume fly ash concrete in underground engineering lining were discussed. Combining practical condition of our laboratory, the synthesis performance of fresh concrete and mechanical property of hardening concrete was analyzed. Synthesizing research document of the fly-ash early activation, the composite activator of sodium sulfate and hydrate lime was ascertained. First, transiting high volume fly-ash cement mortar strength test, the optimization composite activator mass was ascertained preliminary. Subsequent, the test was designed by orthogonal way. The five factors of the orthogonal test are the ratio of water to cementitious material, the mass of fly-ash, silicon fume, sodium sulfate and hydrate lime. Through visual and variance analysis, the rules worked on 3d, 7d, 28d, 91d strength of the fly-ash concrete by its related factors was analyzed. Early (3d~7d) concrete strength acquire apparent enhance comparatively, 28d and later 91d strength exceed the reference concrete strength. By analysis of mechanical property, the high volume fly-ash concrete can meet the requirement of the underground concrete lining. Especially, the underground concrete demands higher cracking resistance, so the draw-press ratio of 7d and 28d were analyzed, in the concrete, adding fly-ash and silicon fume can reduce pores and intensifies the cracking resistance of concrete. Lastly, complex equilibrium the effect of the relative factors on the concrete each age strength, the broaden test of adding 60% fly-ash was ascertained. By test, the optimum mix proportions of C40, C45 and C50 strength concrete were determined.In the multivariable linear regression analysis, the 3d, 7d, 28d, 91d cube strength are looked as function differently and the five factors of test were viewed as independent variables. Using the SPSS statistical analysis application software, the optimum regression equation was deduced by stepwise method. The concrete strengths predicted by the optimum regression equation were compared with the actual value; the optimum regression equation can predict concrete strength perfectly.