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作 者:靳聪聪 迟世春[1,2] JIN Cong-cong;CHI Shi-chun(State Key Laboratory of Coastal and Offshore Engineering,Dalian University of Technology,Dalian 116024,China;School of Hydraulic Engineering,Dalian University of Technology,Dalian 116024,China)
机构地区:[1]大连理工大学海岸与近海工程国家重点实验室,辽宁大连116024 [2]大连理工大学水利工程学院,辽宁大连116024
出 处:《浙江大学学报(工学版)》2020年第7期1390-1400,共11页Journal of Zhejiang University:Engineering Science
基 金:国家重点研发计划资助项目(2016YFB0201001)。
摘 要:采用改进PZC弹塑性模型和动力固结有限元程序SWANDYNEⅡ,对糯扎渡高土石坝进行动力分析,直接得到大坝永久变形,为地震易损性研究提供计算基础.采用坝顶相对震陷率作为易损性性能参数,根据糯扎渡高土石坝所在区域的主要潜在震源区内统计地震情况,从PEER中选取60条吻合较好的地震动记录.基于性能的大坝抗震设防水准和土石坝震害等级,提出适合高土石坝的性能水平划分.引入人工神经网络方法,结合多条带分法,提出基于ANN-MSA的高土石坝地震易损性分析方法.该方法通过对选取的地震动记录调幅处理,利用SWANDYNEⅡ程序对地震动进行分析,得到不同PGA的坝顶相对震陷率,作为训练样本和检验样本.采用RBFNN对训练样本进行训练,利用训练和检验后的模型预测坝顶相对震陷率.结合ANN预测结果和MSA方法,对糯扎渡高土石坝进行地震易损性分析,计算出该大坝的三维地震易损性曲面.The dynamic analysis of Nuozhadu high core earth-rockfill dam was conducted by adopting the improved PZC elastic-plastic model and the dynamic consolidation finite element program SWANDYNE Ⅱ. The permanent deformation of the dam was obtained, and the calculation basis for seismic fragility analysis was provided. The crest relative seismic settlement rate was selected as the fragility performance parameter. The 60 well-matched ground motion records were picked from PEER according to the statistical earthquake situation in the main potential seismic source area of Nuozhadu high core earth-rockfill dam. The grade of performance level of the high core earth-rockfill dam was proposed combined with the performance of the dam anti-seismic level and the earthquake damage grade of core earth-rockfill dams. The seismic fragility analysis approach for the high earth-rockfill dam based on ANN-MSA was provided by introducing the artificial neural network method and combined with multi-strip method. The SWANDYNE Ⅱ program was used to analyze the seismic ground motion by processing the selected seismic records.The relative seismic subsidence rates of the different PGAs can be obtained, which were used as training samples and test samples. RBFNN was utilized to train the training samples. The model through training and testing can well predict the relative seismic settlement rate. The seismic fragility of Nuozhadu high core earth-rockfill dam was analyzed combined with the prediction results of ANN and MSA method, and the three-dimensional seismic fragility surface of the dam was obtained.
关 键 词:改进PZC弹塑性模型 SWANDYNEⅡ程序 ANN方法 MSA方法
分 类 号:TV641[水利工程—水利水电工程]
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