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| 小湾特高拱坝蓄水初期坝肩抗力体变形特性研究 | |
| 引用本文： | 胡波,廖占勇,刘晓丽.小湾特高拱坝蓄水初期坝肩抗力体变形特性研究[J].西北水电,2011(Z1):30-34. |
| 作者姓名： | 胡波 廖占勇 刘晓丽 |
| 作者单位： | 1. 国网电力科学研究院/南京南瑞集团公司,南京210003;河海大学水利水电学院,南京210098 2. 国网电力科学研究院/南京南瑞集团公司,南京,210003 3. 清华大学水利水电工程系,北京,100084 |
| 基金项目： | 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) |
| 摘 要： | 以原型监测数据为基础,采用综合对比分析、FLAC3D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。 |
| 关 键 词： | 抗力体 位移模式 原型监测 人工神经网络 混合模型 |
Research on deformation characteristic analysis of resistance body at dam abutment in Initial Impoundment,xiaowan hydropower project with ultra-high arch dam |
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| HU Bo,LIAO Zhan-yong,LIU Xiao-li.Research on deformation characteristic analysis of resistance body at dam abutment in Initial Impoundment,xiaowan hydropower project with ultra-high arch dam[J].Northwest Water Power,2011(Z1):30-34. | |
| Authors: | HU Bo LIAO Zhan-yong LIU Xiao-li |
| Affiliation: | HU Bo~(1,2),LIAO Zhan-yong~1,LIU Xiao-li~3 (1,State Grid Electric Power Research Institute/Nanjing Nari Group Company,Nanjing 210003,China,2 Water Resources and Hydropower Engineering School,Hohai University,Nanjing 210098,3.Water Resources and Hydropower Engineering Department,Tsinghua University,Beijing 100084,China) |
| Abstract: | Comprehensive contrast and analysis,FLAC numerical analysis,stepwise regression and artificial neural network are integrated 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 ... |
| Keywords: | resistance body displacement mode prototype monitoring artificial neural network mixing model |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |