基于D-最优设计方法预测超高性能混凝土的湿堆积密实度及力学性能  

Prediction of wet packing density and mechanical properties of Ultra-High Performance Concrete by D-Optimal Design method

作　　者：刘潇 范定强 胡锋 苏琪琦 王雄江[1] LIU Xiao;FAN Ding-qiang;HU Feng

机构地区：[1]武汉理工大学土木工程与建筑学院,湖北武汉430070 [2]武汉理工大学材料科学与工程学院,湖北武汉430070

出　　处：《节能》2020年第7期99-104,共6页Energy Conservation

基　　金：武汉理工大学2019年自主创新研究基金本科生项目(项目编号:2019-TJ-B1-04)。

摘　　要：基于D-最优设计方法超高性能混凝土试验配合比,采用"湿堆积法"测得不同配合比的湿堆积密实度,测定不同配合比在水胶比为0.20时的抗压强度、抗折强度,分别建立了UHPC的湿堆积密实度预测模型及抗压、抗折强度预测模型并进行了预测精度评价。结果表明:预测模型拟合度高,自变量因素之间交互作用显著。对于湿堆积密实度预测模型,因子的影响程度排序为硅灰>水泥>石灰石粉>河砂;对于抗压强度预测模型,因子影响程度排序为硅灰>河砂>水泥>石灰石粉;对于抗折强度预测模型,因子影响程度排序为硅灰>石灰石粉>水泥>河砂。Based on the experimental mix ratios of UHPC by D-Optimal Design method, the "wet packing method" was used to measure the wet packing density of different ratios. Together with the measured compressive strength and flexural strength of different mix ratios(W/C ratio=0.20) to establish the wet packing density prediction model and the mechanical property prediction model respectively. And the prediction accuracy was evaluated. The results show that the prediction models fit well and the interaction between independent variables is significant. For the prediction model of wet packing density, the influence degree of factors was ranked as silica fume > cement > limestone powder > river sand. For the prediction model of compressive strength, the influence degree of factors was ranked as silica fume > river sand > cement > limestone powder. For the prediction model of flexural strength, the influence degree of factors was ranked as silica fume > limestone powder > cement > river sand.

关 键 词：D-最优设计 超高性能混凝土 湿堆积法 湿堆积密实度预测 抗压强度预测 抗折强度预测 

分 类 号：TU528[建筑科学—建筑技术科学]