| 低模数水玻璃对橡胶轻骨料混凝土力学性能的影响 |
| |
| 引用本文： | 马快乐,王海龙,刘思盟,杨虹,张佳豪,王辉.低模数水玻璃对橡胶轻骨料混凝土力学性能的影响[J].排灌机械工程学报,2021,39(7):685-691. |
| |
| 作者姓名： | 马快乐 王海龙 刘思盟 杨虹 张佳豪 王辉 |
| |
| 作者单位： | 内蒙古农业大学水利与土木工程学院, 内蒙古 呼和浩特 010018 |
| |
| 摘 要： | 为了了解不同掺量水玻璃对RLC(橡胶轻骨料混凝土)力学性能的影响,在RLC中加入水玻璃,并用20%粉煤灰代替水泥,制作水玻璃掺量分别为0,2%,4%,6%,8%的混凝土试块.通过核磁共振试验研究其微观孔隙变化及强度形成机理;进行对数函数曲线预测和BP神经网络强度预测,判断其可靠性并对比优劣.结果表明:水玻璃的掺入使RLC抗压强度呈现先增大后减小的趋势,其水玻璃最优掺量出现在2%;适量水玻璃的加入可提高80 目RLC力学性能,使其与最优组(20 目RLC组)28 d力学性能基本相同;水玻璃加入后混凝土孔隙度呈现出先减小后增大趋势,说明适量水玻璃的掺入可优化混凝土孔隙结构,提高混凝土强度;建立曲线拟合和BP-神经网络预测模型,2种预测模型都可用于混凝土龄期强度预测,但BP-神经网络预测模型的稳定性、可靠性及参数的全面性要优于曲线拟合模型.
|
| 关 键 词： | 橡胶 水玻璃 核磁共振 BP神经网络 预测模型 |
| 收稿时间： | 2020-12-15 |
Effect of low modulus sodium silicate on mechanical properties of rubber lightweight aggregate concrete |
| |
| MA Kuaile,WANG Hailong,LIU Simeng,YANG Hong,ZHANG Jiahao,WANG Hui.Effect of low modulus sodium silicate on mechanical properties of rubber lightweight aggregate concrete[J].Journal of Drainage and Irrigation Machinery Engineering,2021,39(7):685-691. |
| |
| Authors: | MA Kuaile WANG Hailong LIU Simeng YANG Hong ZHANG Jiahao WANG Hui |
| |
| Institution: | Water Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia 010018, China |
| |
| Abstract: | In order to understand the influence of different dosages of sodium silicate on the mechanical performance of Rubber Lightweight Concrete(RLC), sodium silicate was added into rubber lightweight aggregate concrete(RLC)and 20% fly ash was used instead of cement. The concrete blocks with content of 0, 2%, 4%, 6% and 8% sodium silicate were prepared. Through NMR to study the microscopic change and strength formation mechanism. The logarithmic function curve prediction and BP neural network strength prediction were carried out to judge the reliability and compare the advantages and disadvantages. The results show that the compressive strength of RLC increases first and then decreases with the addition of sodium silicate, and the best content of sodium silicate is 2%. The mechanical properties of 80-mesh RLC are almost the same as the optimal group(20-mesh RLC group)with 28 d, and the mechanical properties can be improved by adding appropriate amount of sodium silicate. After the addition of sodium silicate, the porosity shows a tendency of first decreasing and then increasing, which indicates that the addition of appropriate content of sodium silicate can optimize the pore structure of concrete and improve the strength of concrete. The prediction models of curve fitting and BP Neural Network are established. Both models can be used to predict the concrete age strength, but the stability, reliability and comprehensiveness of parameters of the BP-neural network prediction model are better than those of curve fitting models. |
| |
| Keywords: | rubber sodium silicate nuclear magnetic resonance BP neural network prediction models |
|
| 点击此处可从《排灌机械工程学报》浏览原始摘要信息 |
| 点击此处可从《排灌机械工程学报》下载免费的PDF全文 |
|
