徐斌

个人信息Personal Information

教授

博士生导师

硕士生导师

任职 : 工程抗震研究所副所长

性别:男

毕业院校:大连理工大学

学位:博士

所在单位:水利工程系

学科:水工结构工程. 防灾减灾工程及防护工程. 岩土工程

办公地点:辽宁省大连市高新园区大连理工大学四号实验楼101

联系方式:xubin@dlut.edu.cn

电子邮箱:xubin@dlut.edu.cn

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Seismic reliability assessment of earth-rockfill dam slopes considering strain-softening of rockfill based on generalized probability density evolution method

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论文类型:期刊论文

发表时间:2018-04-01

发表刊物:SOIL DYNAMICS AND EARTHQUAKE ENGINEERING

收录刊物:SCIE、EI

卷号:107

页面范围:96-107

ISSN号:0267-7261

关键字:Earth-rockfill dam slopes; Seismic reliability; Strain softening; GPDEM; Stochastic earthquake excitation; Cumulative time

摘要:This paper investigates the seismic reliability of earth-rockfill dam slopes under stochastic earthquake excitation considering strain-softening behaviour of rockfill materials. A new and efficient methodology that couples a recently developed generalized probability density evolution method (GPDEM) with a spectral representation random function method is presented to assess the seismic reliability. To solve the GPDEM equation, the stochastic seismic responses analysis of a 242-m concrete face rockfill dam (CFRD) is translated into a series of deterministic dynamic calculations. The probability information and seismic reliability of the safety factor demonstrate that the results between the simulations considering unsoftening and softening behaviour of the rockfill materials become increasingly different as the earthquake intensifies, and strain-softening behaviour gradually appear under seismic excitation. Thus, considering the softening characteristic of rockfill materials, is of great significance to analyze the seismic safety of high earth rockfill dams. The traditional index for evaluating dam slope stability with safety factor is compared with a new index the cumulative time of the safety factor less than 1.0 (F-s < 1.0), suggesting that the new index is more reasonable to assess the seismic reliability of dam slopes. The results indicate that the GPDEM is an effective approach to seismic reliability assessment from the stochastic viewpoint and can directly reflect the failure probability.