基于剪切波速的土体液化概率判别法∗
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肖诗豪(1997-),男,硕士生。主要从事岩土工程可靠度与风险分析。Email:xiaoshihao@tongji.edu.cn

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P642.22

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Probabilistic Evaluation of Soil Liquefaction Potential based on Shear Wave Velocity
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    摘要:

    采用极大似然法对确定性剪切波速液化判别模型进行了标定,在此基础上提出了基于剪切波速的土体液化概率判别模型。结果表明,由对数正态分布、正态分布、最小耿贝尔分布以及最大耿贝尔分布获得的液化判别曲线在液化概率为5%和15%时有一定差异,在液化概率为35%时区别不大。根据贝叶斯信息准则,由最小耿贝尔模型标定的模型修正系数与液化案例数据库符合程度最好。Andrus和Stokoe液化模型修正系数的均值为0.879,说明该模型获得的安全系数从平均意义上小于真实安全系数;变异系数为0.387,表明该模型具有一定程度的模型不确定性。本文所建立概率模型的液化判别曲线与文献中基于贝叶斯映射函数获得的液化判别曲线较为一致,与文献基于逻辑回归方法获得的液化判别曲线在高循环应力比区域有较大差异。

    Abstract:

    Soil liquefaction is a common natural disaster during earthquakes. In recent years, the evaluation of soil liquefaction potential based on shear wave velocity has received increasing attention. In this paper, the maximum likelihood method is used to calibrate the worldwide used deterministic liquefaction evaluation model based on shear wave velocity proposed by Andrus and Stokoe. On this basis, a probabilistic evaluation model of soil liquefaction potential based on shear wave velocity is proposed. The results show that the liquefaction evaluation curves obtained from lognormal distribution, normal distribution, minimum Gumbel distribution and maximum Gumbel distribution have some differences when the liquefaction probability is 5% and 15%, and little difference when the liquefaction probability is 35%. The model correction coefficient calibrated by the minimum Gumbel model is mostly supported by the liquefaction case database according to the Bayesian information criterion. The mean value of the model correction coefficient is 0.879, indicating that the factor of safety obtained by the model proposed by Andrus and Stokoe is smaller than the true factor of safety in the average sense. The coefficient of variation is 0.387, indicating that the model error involves some uncertainties. The liquefaction evaluation curve of the probability model established in this paper is consistent with that obtained by Bayesian mapping function in the literature, and is quite different from that obtained based on logistic regression method in the high cyclic stress ratio range in the literature.

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肖诗豪,张洁,葛一荀,孔明.基于剪切波速的土体液化概率判别法∗[J].防灾减灾工程学报,2020,(4):490-497

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  • 在线发布日期:2020-09-20
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