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机构地区:[1]吉林大学建设工程学院,吉林长春130026 [2]长江三峡勘测研究院有限公司,湖北武汉430073
出 处:《东北大学学报(自然科学版)》2017年第11期1643-1647,共5页Journal of Northeastern University(Natural Science)
基 金:国家自然科学基金重点项目(41330636);北京市科技计划项目(Z141100003614052);中国博士后科学基金资助项目(2017M611324)
摘 要:利用组合赋权法与云模型对坝基岩体质量分级进行了评价,主要采用6项评价指标:岩石单轴饱和抗压强度、结构面间距、RQD、完整性系数、声波纵波速度和地应力修正系数,以金沙江旭龙水电站坝基岩体作为实例进行了质量评价.通过偏好系数法将优序图法和熵值法组合,利用云数字特征值建立岩体质量各评价因子的云模型,并得出岩体样本各评价因子对应的确定度,综合确定度最大值对应等级为岩体的质量等级.利用云模型的评价结果与传统的BQ分级法和可拓理论的评价结果进行比较验证,云模型具有可操控性和较高分类精度,能够精确地表达出岩体质量的综合确定度.This study focused on the dam foundation rock quality evaluation. Six evaluation indicators involving saturated uniaxial compressive strength, structural plane spacing, RQD, integrality coefficient, acoustic longitudinal wave velocity and ground stress correction coefficient were taken into consideration. Based on the component weighting method and cloud model,the Jinsha Xulong dam foundation rock mass was taken as a case. The optimal sequence diagram method and entropy value method were combined by the preference coefficient method to overcome the disadvantages of using subjective and objective weighting method alone. The rock mass quality evaluation indicators clouds were established based on the digital characteristic values. Then the certainty of each indicator was calculated. The corresponding quality degree is the rock mass quality degree. The cloud model results were compared with traditional BQ method results and the extension theory results. The cloud model has stronger controllability and higher classification accuracy, which is able to express the comprehensive uncertainty of rock quality.
分 类 号:TV223.1[水利工程—水工结构工程]
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