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作 者:杜建刚 徐佳成[1] 罗显枫 李昕 DU Jiangang1, XU Jiacheng1, LUO Xianfeng2, LI Xin2(1. China International Engineering Consulting Corporation, Beijing 100048, China ;2. Dalian University of Technology , Dalian 116023, Chin)
机构地区:[1]中国国际工程咨询公司能源业务部,北京100048 [2]大连理工大学建设工程学部,辽宁大连116023
出 处:《中国水利水电科学研究院学报》2018年第1期62-69,共8页Journal of China Institute of Water Resources and Hydropower Research
基 金:国家“973”计划项目(No.2013CB036404); 大连理工大学国家重点实验室开放基金(LP1615); 湖北省教育厅科研计划项目(B2017258)
摘 要:针对蒙特卡罗随机有限元方法求解土石坝边坡小概率失效问题计算时间过长这一弊端,提出了基于链表筛分法和Kriging代理模型的混合子集模拟法。首先,利用链表筛分法计算初始样本点,并以初始样本点作为Kriging代理模型的训练样本点。然后在子集模拟法的分层模拟中采用Kriging代理模型预测条件样本点的响应值,从而可计算出土石坝边坡失效概率。最后,通过一个土石坝边坡算例来说明本方法相比其他方法所需要的计算时间更少,更适合计算土石坝边坡小概率失效问题。A hybrid subset simulation approach based on the linked-list sifting method and Kriging surro-gate model is proposed to overcome the drawback that it takes long time for the Monte-Carlo-based sto-chastic finite element method to calculate small failure probability in slopes of earth dams. First, thelinked-list sifting method is adopted to calculate initial sample points that can be used for training theKriging surrogate model. Next,the Kriging surrogate model is used to predict the response values of condi-tional sample points at different levels of subset simulation,which are used to determine the slope failureprobability. Finally,a slope example of an earth dam is given to illustrate that the proposed approachcosts less time than other approaches, which is more suitable to calculate small failure probability inslopes of earth dams.
关 键 词:子集模拟法 链表筛分法 边坡可靠度 Kriging代理模型
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