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堤防管涌险情主要影响因素的敏感性分析
引用本文:宁丹麦,罗玉龙,詹美礼,盛金昌.堤防管涌险情主要影响因素的敏感性分析[J].长江科学院院报,2019,36(10):45-48.
作者姓名:宁丹麦  罗玉龙  詹美礼  盛金昌
作者单位:河海大学 水利水电学院,南京,210098;河海大学 水利水电学院,南京,210098;河海大学 水利水电学院,南京,210098;河海大学 水利水电学院,南京,210098
基金项目:国家重点研发计划项目(2017YFC1502603)
摘    要:针对管涌破坏模式,建立了双层地基堤防概化模型,选取了堤内外水位差、警戒水位持续天数、弱透水覆盖层厚度及强弱透水层渗透系数比值4个主要评估指标,开展了大量敏感性分析,确定了各评估指标对管涌发生影响的客观权重。研究表明:堤内外水位差和弱透水覆盖层厚度(<2 m)2个评估指标对管涌发生的影响权重相对比较大;同时,对于警戒水位持续天数、弱透水覆盖层厚度及强弱透水层渗透系数比值3个评估指标,需要分区间确定客观权重,不同区间,各指标的客观权重不同。研究成果为后续建立堤防安全评估方法提供了依据。

关 键 词:堤防管涌  弱透水覆盖层  强透水覆盖层  渗透系数比值  权重敏感性  双层地基堤防  概化模型
收稿时间:2019-07-23

Sensitivity Analysis on Weights of Main Influence Factors ofPiping Failure of Dyke
NING Dan-mai,LUO Yu-long,ZHAN Mei-li,SHENG Jin-chang.Sensitivity Analysis on Weights of Main Influence Factors ofPiping Failure of Dyke[J].Journal of Yangtze River Scientific Research Institute,2019,36(10):45-48.
Authors:NING Dan-mai  LUO Yu-long  ZHAN Mei-li  SHENG Jin-chang
Affiliation:College of Water Conservancy and Hydropower, Hohai University, Nanjing 210098, China
Abstract:In this paper a generalized double-layer foundation levee model is built to conduct sensitivity analysis on four major assessment indicators. These indicators include the water head difference between both sides of levee, the duration of warning water level, the thickness of less permeable layer, and the ratio of permeability of strongly permeable layer to that of less permeable layer. The objective weights of these four indicators influencing backward erosion piping are determined. Results indicate that the water head difference and the thickness of less permeable layer (less than 2 m) are two important indicators with relatively large weights. Meanwhile, the objective weights of three indicators, namely, the duration of warning water level, the thickness of less permeable layer, and the ratio of permeability coefficient, vary in different ranges.
Keywords:piping danger of levee  weakly permeable strata  strongly permeable layer  ratio of permeability coefficient  sensitivity of weight  dyke with dual foundation layers  generalized model  
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