考虑相互作用影响的堆石料动力参数反演  

Back analysis of dynamic parameters of rock-fill materials considering interaction effects

作　　者：王茂华 迟世春[1,2] 刘振平 WANG Mao-hua;CHI Shi-chun(State Key Laboratory of Coastal and Offshore Engineering,Dalian University of Technology,Dalian 116024,China;Institute of Earthquake Engineering,School of Hydraulic Engineering,Faculty of Infrastructure Engineering,Dalian University of Technology,Dalian116024,China;School of Civil and Architecture Engineering,Heilongjiang Institute of Technology,Harbin 150050,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]大连理工大学建设工程学部水利工程学院工程抗震研究所,辽宁大连116024 [3]黑龙江工程学院土木与建筑工程学院,黑龙江哈尔滨150050

出　　处：《岩土工程学报》2019年第10期1967-1976,共10页Chinese Journal of Geotechnical Engineering

基　　金：国家自然科学基金项目(51379029)

摘　　要：通过黏弹性人工边界及相关的等效结点力法实现了半无限域的地震动输入,采用多种群遗传算法和径向基神经网络构建参数反演平台,建立了考虑坝基相互作用及辐射阻尼影响的土石坝动力参数反演分析模型。多种群遗传算法优化得到坝体堆石料动力参数,可有效避免传统遗传算法的早熟问题;经过训练的径向基神经网络描述模型参数和加速度反应谱值之间的映射关系,节省参数反演的计算时间。对鲤鱼潭大坝动力参数的反演结果表明,测点加速度与实测值吻合较好。考虑相互作用的反演得到堆石料最大动剪模量系数C值最大,刚性地基模型反演结果居中,室内动三轴试验值最小,工程应用时室内试验值应予以修正。A back analysis model considering interaction and radiation damping effects is proposed for dynamic parameters of earth-rock dams.In the model, the viscous-elastic artificial boundary combined with the equivalent node force method of ground motion input is used for achieving the wave motion input of semi-infinite site, and the multiple population genetic algorithm (MPGA) and the radial basis function neural network (RBF) are adopted.Using MPGA to optimize the dynamic parameters of the dam can effectively avoid the prematurity of the traditional genetic algorithm.The trained RBF is used to describe the mapping relationship between the model parameters and the response spectra of acceleration so as to reduce the computing time of parametric inversion.The inversion results of Liyutan dam in China show that the calculated settlements agree well with the measured data.The proposed model is feasible in back-analysis of dynamic parameters of earth-rock dams. The study shows that the dynamic shear modulus coefficient of the dam materials obtained from the rigid foundation model inversion and the indoor dynamic triaxial tests is small.The value of the indoor tests is much smaller and should be revised.

关 键 词：相互作用 动力参数 反演 黏弹性边界 多种群遗传算法 径向基神经网络 

分 类 号：TU435[建筑科学—岩土工程]