In order to predict the compressive strength and to optimize the mix design of ultra high performance concrete(UHPC)incorporated with coarse aggregates,168 mix proportions and corresponding compressive strength of UHPC after 28 days standard curing were collected from domestic and foreign literature.Charts of frequency distribution of each material component and compressive strength were given,and correlations between each material component and compressive strength were analyzed based on grey relational analysis(GRA)method.Through parameter analysis,the back propagation(BP)neural network based on genetic algorithm(GA)was established,which achieved better prediction accuracy and generalization ability than common BP neural network.Finally,based on the established GA-BP neural network,the recommended ranges of coarse aggregates-binder ratio,volume fraction of steel fiber and sand-binder ratio were given in the mix design for preparing UHPC incorporated with coarse aggregates of different strength grades.
关键词
超高性能混凝土/抗压强度/粗骨料/前馈神经网络/遗传算法
Key words
ultra high performance concrete(UHPC)/compressive strength/coarse aggregates/back propagation neural network/genetic algorithm
维普
万方数据