乐昌峡水利枢纽工程右岸坝肩边坡渗流场边界反演分析  

Back Analysis on Slope Seepage Boundary of Right Bank Abutment of Lechangxia Hydro-Junction Project

作　　者：李成[1,2] 李毅[2] 

机构地区：[1]广东省水利电力勘测设计研究院,广东广州510635 [2]长沙理工大学水利工程学院,湖南长沙410076

出　　处：《广东水利水电》2014年第7期8-13,27,共7页Guangdong Water Resources and Hydropower

摘　　要：以确定乐昌峡水电站右岸坝肩边坡地下水位边界为目的,首先以现场监测资料为基础,通过非线性方法拟合各类地下水位边界条件,其次建立三维有限元边坡模型并结合遗传神经网络对地下水边界条件进行反演,最后通过有限元方法计算得到边坡渗流场。计算结果与实测水头较为接近,表明构造的非线性地下水位边界与遗传神经网络反演相结合的方法能够解决复杂渗流场边界水头的确定问题,研究成果对乐昌峡工程的渗流分析以及类似工程具有一定的指导意义。Determining the underground water boundary condition of right bank abutment slope of Lechangxia hydro-junction project is the purpose of this paper. Firstly, nonlinear fitting method is used to fit several types of underground water boundary condition based on site monitoring data; secondly, three-dimensional FEM model of the slope is modeled and genetic neural network is introduced to back analyze underground water boundary condition; Finally, seepage field is obtained by FEM calculation. Method used in this paper is proved suitable to solve complex seepage boundary condition since calculating results fit well with site monitoring da- ta. It provides certain guiding significance to Lechangxia project and some similar projects.

关 键 词：渗流 有限元 反演分析 遗传神经网络 边坡 

分 类 号：TV139.14[水利工程—水力学及河流动力学]