摘要
在使用传统神经网络模型进行混凝土坝材料力学参数反演分析的基础上,将正交试验设计理论与BP神经网络模型相结合,对混凝土坝材料力学参数反演模型进行了优化。通过构建三维有限元模型,以拱坝实体工程及其变形监测数据进行了计算分析,反演得到的混凝土和基岩参数,计算结果与设计值相近且有一定程度提升。最后将反演成果作为有限元计算模型的输入,输出成果验证了计算结果的可靠性,从而证明了优化后的方法提高了神经网络模型计算的效率和精确度。
Based on the back analysis of concrete dam mechanical parameters by using traditional neural network model,the BP neural network model is combined with orthogonal experiment design theory,the back analysis model of concrete dam mechanical parameters is optimized.By building a three-dimensional finite element model,the parameters of concrete and bedrock are calculated based on the arch dam and its deformation monitoring data by the back analysis.The calculation result is close to the design value and has a certain degree of improvement.Finally,the back analysis result are taken as the input of the finite element model,and the reliability of the calculation result is verified by the output result.It is proved that the optimized method improves the efficiency and accuracy of the neural network model.
作者
赵骕
李君
朱小琼
ZHAO Su;LI Jun;ZHU Xiaoqiong(Guangdong Architectural Design and Research Institute Group Co.,Ltd.,Guangzhou 510010,Guangdong,China;Guangzhou Hantu Technology Co.,Ltd.,Guangzhou 510060,Guangdong,China;Guangxi Hengxinzhice Surveying&Mapping Technology Co.,Ltd.,Nanning 530023,Guangxi,China)
出处
《水利水电技术(中英文)》
北大核心
2025年第S2期136-143,共8页
Water Resources and Hydropower Engineering
关键词
混凝土坝
反演分析
正交设计
神经网络
concrete dam
back analysis
orthogonal design
neural network
