摘要
混凝土抗渗性能影响其结构的耐久性,通过正交试验数据,采用广义回归神经分析方法,研究混凝土的氯离子扩散系数与混凝土配合比6个参数之间的非线性映射关系,建立了混凝土抗渗性能评估的广义回归网络模型,该研究成果可以减少混凝土试配次数,节约大量的人力、物力和时间,为高性能混凝土的研究发展奠定了基础。结果表明此模型的可靠度很高,可以用于混凝土渗透性的设计及评估。为混凝土抗渗性能的预测提供了一条新的途径。
Concrete permeability have a direct impact on its durability,and the tradition test consume large amount of time surely.According or-thogonal test data,the relationship between the chloride diffusion coefficient and six parameters on the impermeable performance was presented.Based on general regression neural network nonlinear analysis method,a intelligent information analysis of nonlinear general regression neural network method,an artificial intelligence information model for predicting impermeability of concrete was established.Result indicates that pro-jection pursuit regression model is reliable enough to concrete＇s virtual design.It provides a new way to predict impermeability of concrete.
出处
《混凝土》
CAS
CSCD
北大核心
2011年第2期46-48,127,共4页
Concrete
关键词
正交试验
氯离子扩散系数
广义回归神经网络
抗渗性能
orthogonal test
chloride ion diffusion coefficient
general regression neural network
impermeability
