水泥基混凝土孔隙结构演变特征对强度影响的灰色关联熵分析

Grey relational entropy analysis of influence of cement-based concrete pore structure evolution characteristics on strength

为研究水泥基混凝土孔隙结构对其抗压强度的影响,通过其孔隙结构参数预测抗压强度。对C30混凝土进行宏观抗压强度试验、微观电子显微镜试验(SEM)、微观核磁共振试验(NMR),研究混凝土孔隙结构对混凝土抗压强度的影响,利用灰色关联熵分析方法建立抗压强度与孔隙结构关系的数学基础模型。试验结果表明:随着养护龄期的增长,有害孔与多害孔占比逐渐减少,无害孔占比逐渐增加;混凝土的横向弛豫时间T2谱呈现"大峰带小峰"的构造,谱面积随养护龄期增长而减小;对抗压强度影响最大的两种因素为束缚流体饱和度(IFS)和半径大于10μm的孔隙占比,其灰熵关联度分别为0.997 1和0.997 2;以抗压强度与束缚流体饱和度(IFS)及半径大于10μm的孔隙占比建立GM(1,3)模型,模型预测值与试验值的平均相对误差为5.11%,并利用强度预测模型对多处混凝土的孔隙结构参数进行强度模拟,相对误差最小为0.4%,最大为7.75%,表明预测模型可以作为混凝土强度检测的公式依据。

In order to study the influence of the pore structure of cement-based concrete on its compressive strength, the compressive strength was predicted through its pore structure parameters. Macroscopic compressive strength test, scanning electron microscope test(SEM) and microscopic nuclear magnetic resonance test(NMR) were conducted of C30 concrete to study the influence of concrete pore structure on concrete compressive strength, and the compressive strength and the grey relational entropy analysis method was used to establish the mathematical basic model of the relationship between compressive strength and pore structure. The test results show that with the increase of the curing age, the proportion of harmful holes gradually decreases, and the proportion of harmless holes gradually increases;the transverse relaxation time T2 graph of concrete shows a structure of "large peaks with small peaks", and the spectrum area decreases with the increase of the curing age;the two factors that have the greatest impact on the compressive strength are the bound fluid saturation(IFS) and the ratio of pores with a diameter greater than 10μm, and the gray entropy correlation is 0.997 1 and 0.997 2 respectively. The GM(1,3) model was established based on the compressive strength and the infinite fluid saturation(IFS) and the ratio of pores with a diameter greater than 10μm. The average relative error between the predicted value of the model and the experimental value was 5.11%, and the strength prediction model was used to simulate the strength of the pore structure parameters of the concrete. The minimum relative error was 0.4% and the maximum was 7.75%, indicating that the prediction model can be used as a formula basis for concrete strength testing.