摘要
表征混凝土坝服役性态变化的监测效应量,其变化客观反映了大坝的工作性态变化,为确保大坝的安全运行,需对相应的监测效应量拟定安全监控指标,传统的方法在假定一定失效概率的前提下拟定监控指标,人为因素影响较大。经对传统方法不足的分析,基于典型小概率方法和层次分析法的思想,提出了混凝土坝服役性态评价等级属性不等区间的划分方法,在此基础上,综合运用最大熵原理,构建反映混凝土坝服役性态变化的监测效应量概率密度函数,提出拟定对应大坝服役性态评价不同等级属性的监测效应量安全监控指标的方法,并通过工程实例验证了所提出方法的可行性和有效性。
The variation of the monitoring effect quantity characterized the service behavior change of a concrete dam objectively reflects the working behavior variation of the dam.In order to ensure the safe operation of the dam,it is necessary to draw up the safety monitoring index of the corresponding monitoring effect quantity.Traditional method formulates the safety monitoring index under the assumption of certain failure probability,which is affected by the human factor.Aimingat the shortcomings of traditional approaches,integrated the idea of typical small probability method and analytic hierarchy process,the method of dividing the unequal range of evaluation grade attributes of concrete dam service behavior is proposed.The probability density function of monitoring effect quantity is constructed based on the principle of maximum information entropy,the method for formulating safety monitoring index of monitoring effect quantity corresponding to different grade attributes of dam behavior performance evaluation is put forward.The feasibility and effectiveness of the proposed method is verified by an engineering project.
作者
顾昊
曹文翰
汪程
顾冲时
黄潇霏
GU Hao;CAO Wenhan;WANG Cheng;GU Chongshi;HUANG Xiaofei(College of Agricultural Science and Engineering,Hohai University,Nanjing 210098,China;College of Water Conservancy and Hydropower Engineering,Hohai University,Nanjing 210098,China;Shanghai Municipal Engineering Design and Research Institute(Group)Co.,Ltd.,Shanghai 200092,China;Hohai UniversityLibrary,Hohai University,Nanjing 210098,China)
出处
《水利水电科技进展》
CSCD
北大核心
2021年第1期30-34,48,共6页
Advances in Science and Technology of Water Resources
基金
国家自然科学基金(51909173)
国家大坝安全工程技术中心开放基金(CX2020B)
河海大学自由探索专项(B200201058)。
关键词
混凝土坝
服役性态评价
监测效应量
最大熵概率密度
安全监控指标
concrete dam
dam behavior evaluation in service
monitoring effect quantity
maximum information entropy probability density
safety monitoring index
