纳米SiO_(2)粉煤灰混凝土抗压强度影响及灰熵分析  

Influence of nano-SiO_(2) fly ash on compressive strength of concrete and grey entropy analysis

作　　者：云振军 姚占全[1] 何梁[1] 维利思 李越 YUN Zhenjun;YAO Zhanquan;HE Liang;WEI Lisi;LI Yue(College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia 010018, China)

机构地区：[1]内蒙古农业大学水利与土木建筑工程学院,内蒙古呼和浩特010018

出　　处：《排灌机械工程学报》2022年第5期467-474,共8页Journal of Drainage and Irrigation Machinery Engineering

基　　金：内蒙古农业大学博士科研启动基金资助项目(BJ2014-4)。

摘　　要：为探究纳米SiO_(2)粉煤灰混凝土孔隙结构对抗压强度的影响,取纳米SiO_(2)掺量分别为1%,3%,5%和7%,粉煤灰掺量分别为10%,20%和30%,水胶比为0.35,将两者复掺进行试验.测定混凝土3,7和28 d立方体抗压强度.利用核磁共振技术、场发射扫描电镜和差热-热重技术,综合分析研究孔隙结构及微观形貌特征,通过灰关联熵分析法找出影响混凝土抗压强度的主、次因素,并建立GM(1,4)灰色预测模型.结果表明:两者复掺在混凝土发育阶段起到正耦合作用,宏微观关联分析可知,粉煤灰掺量20%、纳米SiO_(2)掺量3%为最优;建立了混凝土抗压强度与(0,0.01]μm孔径占比、(0.01,0.10]μm孔径占比和束缚流体饱和度的灰色预测模型.GM(1,4)模型3,7和28 d的预测值与试验值的平均相对误差分别为3.58%,4.37%和2.88%,利用孔隙结构预测混凝土抗压强度有较好的精度.该研究可为纳米SiO_(2)和粉煤灰在混凝土工程中的应用提供一定参考.To explore the influence of pore structure of nano-SiO_(2) fly ash concrete on compressive strength,the content of nano-SiO_(2) additional rate 1%,3%,5%and 7%,and fly ash additional rate 10%,20%and 30%,respectively,the water to binder ratio 0.35,and the two were mixed together for the test.Determine the cube microstructure compressive strength 3,7 and 28 day.The pore structure and micro morphology were comprehensively analyzed and studied by nuclear magnetic resonance technology,field emission scanning electron microscope and differential thermal gravimetric technology.The primary and secondary factors affecting the compressive strength of concrete are found out by gray correlation entropy analysis,and the GM(1,4)gray prediction model was established.The results show that the nano-SiO_(2) and fly ash can promote the hydration of concrete,and improve the early compressive strength of concrete,meanwhile the optimal mix proportion is 20%of fly ash and 3%of nano-SiO_(2).The main factors affecting the compressive strength are(0,0.01]μm pore size ratio,(0.01,0.10]μm pore size ratio and bound fluid saturation,which are used to establish a GM(1,4)gray model.The average relative errors between the predicted values of 3,7 and 28 day and the experimental values are 3.58%,4.37%and 2.88%,respectively.Using the pore structure to predict the compressive strength of concrete has better accuracy.This study can provide reference for the application of nano-SiO_(2) and fly ash in concrete engineering.

关 键 词：混凝土 纳米SiO_(2) 粉煤灰 孔隙结构 灰熵 GM(1 4)模型 

分 类 号：S277.9[农业科学—农业水土工程]