摘要
基于响应曲面法中的中心复合试验法(RSM-CCD)设计13组试验,以自燃煤矸石粉细度和掺量为影响因素,研究其对混合砂浆流动性、不同水化龄期抗压强度和抗折强度的影响.结果表明:自燃煤矸石粉细度和掺量对砂浆流动性和强度影响显著,特别是两者交互作用对砂浆抗折强度的影响极为显著,对抗压强度的影响随着水化龄期的延长而递增,所建立的回归模型相关系数(R^(2))大于0.96,表明模型的合理性和拟合性较好;当自燃煤矸石粉细度为8.00μm、掺量为15.49%时,砂浆流动度为182 mm,28、56 d抗压强度为43.8、50.2 MPa,抗折强度为8.4、8.7 MPa;自燃煤矸石粉具有微集料和活性效应,可以作为混凝土掺合料.
13 groups of test were designed based on the central composite design(RSM-CCD)in the response surface methodology.The fineness and content of spontaneous combustion coal gangue powder were taken as the influencing factors to study the influence of spontaneous combustion coal gangue powder on the fluidity,compressive strength,and flexural strength of prepared mixed mortar at different hydration ages as the response values.The results show that the effects of fineness and content of spontaneous combustion coal gangue powder on mortar fluidity and strength are significant,the effect of interaction on flexural strength are also significant,and the effects on compressive strength anhance with the extension of age.The established regression model(R^(2))is greater than 0.96,indicating that each model has good rationality and fitting.When the fineness is 8.00μm and the content is 15.49%,the mortar fluidity is 182 mm,the compressive strength is 43.8,50.2 MPa,and the flexural strength is 8.4,8.7 MPa at 28,56 d respectively.The spontaneous combustion coal gangue powder has the micro-aggregate and active effect,which is feasible to be used as a concrete admixture.
作者
张凯
周梅
李超
刘艳
彭磊
ZHANG Kai;ZHOU Mei;LI Chao;LIU Yan;PENG Lei(School of Civil Engineering,Liaoning Technical University,Fuxin 123000,China;Liaoning Provincial Key Laboratory of Coal Gangue Resource Utilization and Energy-Saving Building Materials,Liaoning Technical University,Fuxin 123000,China)
出处
《建筑材料学报》
EI
CAS
CSCD
北大核心
2023年第3期299-309,共11页
Journal of Building Materials
基金
国家自然科学基金资助项目(U1261122)
辽宁省教育厅科学技术项目(LJ2019FL006)
辽宁工程技术大学学科创新团队资助项目(LNTU20TD-12)。
关键词
自燃煤矸石粉
响应曲面法
砂浆
强度
回归模型
最优配比
spontaneous combustion coal gangue powder
response surface methodology
mortar
strength
regression model
optimal proportion
