摘要
由于地下岩体条件复杂,渗流监测数据缺失现象普遍存在。为了在时间和空间上对地下渗流场进行全面分析,需要对缺失数据进行补充。提出了三类缺失数据的插补方法,对时间序列、空间断面以及区域整体的缺失数据分别用监测统计模型、物理因子修正和反演进行了有效的补充,反映了缺失数据的规律和时间、空间因素对监测数据的影响,最终可得完整、全面的渗流场,并通过反演渗流场对渗透稳定进行判断,为工程评价提供了依据。将该方法用于天荒坪电站缺失数据的插补,结果有效地插补了缺失数据,最终的反演渗流场能够判断渗透破坏可能发生的部位,对工程加固措施具有指导意义。
The underground rock mass condition is very complex.Therefore,the deficiency of seepage monitoring data exists.To comprehensively analyze the underground seepage field in time and space,it is necessary to replenish the missing data.Three types of supplement methods of missing data are proposed:missing data in time sequence can be replenished by creating monitoring statistic model;missing data on spatial sections can be supplemented by regression analysis modified by physical factors;missing data in the whole area can be replenished by back analysis calculation.All these can reflect the regulation of missing data and the influence of chronological and spatial factors on measuring data.Integrated and comprehensive seepage field is obtained,by which seepage stability can be determined,providing reference to project evaluation.These methods are used in Tianhuangping power station.The results show that the complementary piezometric heads and flow rates are in good agreement with the measured data,the back-analyzed seepage field conforms to the engineering practice,and the locations where seepage failure may happen are effectively determined by the back-calculated field.Engineering suggestions are proposed based on the seepage stability,which has instructive meaning to project reinforcement.
作者
徐强
肖明
陈俊涛
倪少虎
XU Qiang;XIAO Ming;CHEN Jun-tao;NI Shao-hu(State Key Laboratory of Water Resources and Hydropower Engineering Science,Wuhan University,Wuhan,Hubei 430072,China;Key Laboratory of Rock Mechanics in Hydraulic Structural Engineering of Ministry of Education,Wuhan University,Wuhan,Hubei 430072,China;PowerChina Huadong Engineering Corporation Limited,Hangzhou,Zhejiang 310014,China)
出处
《岩土力学》
EI
CAS
CSCD
北大核心
2019年第4期1526-1534,共9页
Rock and Soil Mechanics
基金
国家自然科学基金资助项目(No.51409265)
浙江省自然科学基金资助项目(No.LY13E090003)~~
关键词
渗流
数据缺失
统计模型
反演
渗透稳定
seepage
data deficiency
statistical model
back-analysis
seepage stability