Zhao Liuyuan, Huang Yu. 2020. Advances in stochastic dynamic analysis of slopes under earthquakes[J]. Journal of Engineering Geology, 28(3): 584-596. doi: 10.13544/j.cnki.jeg.2020-078.
    Citation: Zhao Liuyuan, Huang Yu. 2020. Advances in stochastic dynamic analysis of slopes under earthquakes[J]. Journal of Engineering Geology, 28(3): 584-596. doi: 10.13544/j.cnki.jeg.2020-078.

    ADVANCES IN STOCHASTIC DYNAMIC ANALYSIS OF SLOPES UNDER EARTHQUAKES

    • The uncertainties are great challenges for seismic design of slope engineering. This paper reviews the recent researches on random dynamic analysis methods of slope, and discusses the application prospect of those methods in engineering seismic design. Firstly, this paper reviews previous researches on dynamic stability of slopes and analyses the uncertainty problems involved in slope engineering. Secondly, it summarizes the processes of slope random dynamic analysis. It introduces a framework of slope random dynamic analysis based on probability density evolution. Then, it introduces the research on the uncertainty of ground motions, where the recorded waves of a typical station are used to explain the existence of the ground motion uncertainty, and a random ground motion model based on the site characteristics is discussed. On this basis, the paper identifies the specific contents of random dynamic analysis of slope. They include(1)random dynamic response analysis of slope, (2)dynamic reliability analysis of slope, (3)seismic fragility analysis of slope, (4)dynamic instability and risk assessment of slope, (5)optimal design of seismic performance of slope. At last, the paper briefly introduces some advances of slope random dynamic analysis method, analyses the achievements and prospects. The research of slope seismic is extended from the deterministic analysis to the uncertainty analysis. The paper provides a theoretical reference for the aseismic design of slope engineering. However, it still needs to be further improved in the aspects of random ground motion simulation, multi random factors coupling, and support structure optimization design.
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