为探究3种因素钢纤维、聚乙烯醇(polyvinyl alcohol,PVA)纤维和矿粉对钢-PVA混杂纤维高性能混凝土(hybrid fiber high performance concrete,HFHPC)高温后残余力学性能的影响.对钢纤维、PVA纤维和矿粉3种因素各取3个水平,采用L9(33)方案进行正交设计,测试HFHPC遭受高温作用后的立方体抗压强度、劈裂抗拉强度和抗折强度,并进行极差与方差分析.结果表明:钢纤维体积分数为2.0％时可以有效提高HFHPC的各项强度.PVA纤维能够抑制混凝土爆裂,与钢纤维混杂可体现优势互补.800 ℃时,当钢纤维体积分数为2.0％、PVA纤维体积分数为0.3％、矿粉掺量为10％时,HFHPC的抗压强度残余率与劈拉强度残余率达到最高,分别为60.23％和74.5％.当矿粉掺量大于10％时,HFHPC抗压强度可显著提高,而劈拉强度与抗折强度略有下降.最后分别建立了 HFHPC立方体抗压强度、劈裂抗拉强度和抗折强度的预测模型.
Experimental Study on the Residual Mechanical Properties of Steel-PVA Hybrid Fiber High Performance Concrete after High Temperature
To investigate the effects of steel fiber,polyvinyl alcohol(PVA)fiber and slag powder on the residual mechanical properties of steel-PVA hybrid fiber high performance concrete(HFHPC)after high temperature,three levels of steel fiber,PVA fiber and slag powder were selected,and the orthogonal design of L9(33)scheme was adopted to test the cube compressive strength,splitting tensile strength and flexural strength of HFHPC subjected to high temperature,and extreme difference and ANOVA were performed.The results show that the steel fiber volume fraction of 2.0％could effectively improve all the strengths of HFHPC.The PVA fiber could inhibit the concrete bursting,and the mixing with steel fiber could reflect the complementary advantages.At 800 ℃,when the volume fraction of steel fiber is 2.0％,the volume fraction of PVA fiber is 0.3％,and the blending amount of slag powder is 10％,the residual rate of compressive strength and the residual rate of splitting tensile strength of HFHPC reach the highest,60.23％and 74.5％respectively.The compressive strength of HFHPC can be significantly increased when the slag powder dosing is more than 10％,while the splitting tensile strength and flexural strength are slightly decreased.Finally,the prediction models of compressive strength,splitting tensile strength and flexural strength of HFHPC cubes were established respectively.
steel-PVA hybrid fiberhigh performance concretehigh temperaturemechanical propertiesstrength prediction model
万方数据
维普
