摘要
为研究石膏岩对隧道衬砌结构的腐蚀性,对硫酸盐侵蚀混凝土的机理及影响因素进行了深入分析.设计正交试验,研究硫酸盐对混凝土腐蚀系数的变化规律,结果表明:抗渗等级、C_3A质量分数与腐蚀系数呈二次函数关系,硫酸根质量浓度和时间与腐蚀系数呈对数函数关系,溶液压力与腐蚀系数近似呈线性关系;采用极差与层次分析法对各个因素的影响权重进行解算,各因素按权重大小依次为:C_3A质量分数、硫酸根质量浓度、时间、抗渗等级、溶液压力;综合考虑各个因素,基于BP神经网络建立了混凝土腐蚀后强度变化量的预测模型,并将该模型成功应用在礼让隧道的衬砌设计中.
In order to study the corrosion of gypsum rock to tunnel lining structure, the mechanism and influence factors of sulfate attacking on concrete were analyzed. The orthogonal test was designed to study the sulfate ’ s influence on the changing rule of the concrete corrosion coefficient. The results show that there is a quadratic function between the anti-permeability level and the C3A content and a logarithmic function between the corrosion coefficient, sulfate concentration and time ; however, there is a linear relation between the pressure and the corrosion coefficient. The influence weight of each factor was calculated by using the range and AHP. According to the weight of each factor,it can be listed as C3A content,sulfate concentration, time, anti-permeability level, pressure in order. Considering all the factors, a prediction model on the strength of concrete after concrosion was established based on the BP neural network. This model was applied in the design of Lirang tunnel lining.
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2017年第7期1049-1054,共6页
Journal of Northeastern University(Natural Science)
基金
教育部高等学校博士学科点专项科研基金资助项目(20130191130003)
关键词
石膏岩腐蚀性
正交试验
极差分析
层次分析法
BP神经网络
corrosion of gypsum rock
orthogonal test
range analysis
AHP（analytic hierarchy process）
BP neural network
