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个人信息Personal Information
教授
博士生导师
硕士生导师
性别:男
毕业院校:河海大学
学位:博士
所在单位:水利工程系
学科:水工结构工程. 防灾减灾工程及防护工程. 岩土工程
联系方式:QQ:2129832315
电子邮箱:schchi@dlut.edu.cn
Back Analysis of the Permeability Coefficient of a High Core Rockfill Dam Based on a RBF Neural Network Optimized Using the PSO Algorithm
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论文类型:期刊论文
发表时间:2015-01-01
发表刊物:MATHEMATICAL PROBLEMS IN ENGINEERING
收录刊物:SCIE、EI、Scopus
卷号:2015
ISSN号:1024-123X
摘要:It is important to determine the seepage field parameters of a high core rockfill dam using the seepage data obtained during operation. For the Nuozhadu high core rockfill dam, a back analysis model is proposed using the radial basis function neural network optimized using a particle swarm optimization algorithm (PSO-RBFNN) and the technology of finite element analysis for solving the saturated-unsaturated seepage field. The recorded osmotic pressure curves of osmometers, which are distributed in the maximum cross section, are applied to this back analysis. The permeability coefficients of the dam materials are retrieved using the measured seepage pressure values while the steady state seepage condition exists; that is, the water lever remains unchanged. Meanwhile, the parameters are tested using the unstable saturated-unsaturated seepage field while the water level rises. The results show that the permeability coefficients are reasonable and can be used to study the real behavior of a seepage field of a high core rockfill dam during its operation period.