摘要
以原型监测数据为基础,采用综合对比分析、FLAC^(3D)数值计算、逐步回归、人工神经网络等多手段相结合的方法,对小湾特高拱坝坝肩抗力体蓄水初期变形特性进行分析和评价。定性分析成果表明,截至1160 m高程库水位,坝肩抗力体在蓄水过程中变形量级非常小,随着水位的上升,坝肩抗力体整体上微微有向下游和向山体内变形的趋势,且变形逐渐收敛。基于有限元计算成果、实测值的混合模型分析成果表明,库水位是分析时段内引起抗力体变形的最主要因素,在1160 m蓄水位条件下,抗力体处于稳定状态。根据模型预测1170 m水位工况条件下,抗力体变形也将处于可控状态。
Comprehensive contrast and analysis, FLACTM numerical analysis, stepwise regression and artificial neural network are integrat- ed to analyze and assess the deformation characteristics of resistance body at dam abutment in initial impoundment, Xiaowan Hydropower Project with ultra-high arch dam. The qualitative analysis results show that, as of EL. 1160m, the deformation value of resistance body at dam abutment in initial impoundment is very small, and the resistance body totally intends to slightly move to downstream and into the banks with water level rising. And the deformation is gradually becoming convergence. From the analyzing results through the mixing model based on finite element calculation and measured values, it shows that the reservoir water level is the main influence factor of deformation during the analysis period. The resistance body is stable at EL. 1160 m. Based on the model, it predicts that the deformation of resistance body will be under control at EL. 1170 m.
出处
《西北水电》
2011年第B09期30-34,共5页
Northwest Hydropower
基金
人力资源与社会保障部留学人员科技活动项目择优资助项目(2009003)
江苏省自然科学基金(BK2009479)
关键词
抗力体
位移模式
原型监测
人工神经网络
混合模型
resistance body
displacement mode
prototype monitoring
artificial neural network
mixing model
