[an error occurred while processing this directive] Global Geology 2019, 22(3) 152-158 DOI:   10.3969/j.issn.1673-9736.2019.03.02  ISSN: 1673-9736 CN: 22-1371/P
本期目录 | 下期目录 | 过刊浏览 | 高级检索                                                            [打印本页]   [关闭]
论文
扩展功能
本文信息
Supporting info
PDF(434KB)
[HTML全文]
参考文献[PDF]
参考文献
服务与反馈
把本文推荐给朋友
加入我的书架
加入引用管理器
引用本文
Email Alert
文章反馈
浏览反馈信息
本文关键词相关文章
slope reliability analysis
high-dimension
sparse grid
Monte Carlo simulation
本文作者相关文章
PubMed
Slope reliability analysis based on Monte Carlo simulation and sparse grid method
WU Guoxue1, PENG Yijin1, LIU Xuesong1, HU Tao2, WU Hao2
1. College of Earth Sciences, Jilin University, Changchun 130026, China;
2. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
摘要： In order to solve the problem of the reliability of slope engineering due to complex uncertainties, the Monte Carlo simulation method is adopted. Based on the characteristics of sparse grid, an interpolation algorithm, which can be applied to high dimensional problems, is introduced. A surrogate model of high dimensional implicit function is established, which makes Monte Carlo method more adaptable. Finally, a reliability analysis method is proposed to evaluate the reliability of the slope engineering, and is applied in the Sau Mau Ping slope project in Hong Kong. The reliability analysis method has great theoretical and practical significance for engineering quality evaluation and natural disaster assessment.
关键词： slope reliability analysis   high-dimension   sparse grid   Monte Carlo simulation  
Slope reliability analysis based on Monte Carlo simulation and sparse grid method
WU Guoxue1, PENG Yijin1, LIU Xuesong1, HU Tao2, WU Hao2
1. College of Earth Sciences, Jilin University, Changchun 130026, China;
2. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Abstract: In order to solve the problem of the reliability of slope engineering due to complex uncertainties, the Monte Carlo simulation method is adopted. Based on the characteristics of sparse grid, an interpolation algorithm, which can be applied to high dimensional problems, is introduced. A surrogate model of high dimensional implicit function is established, which makes Monte Carlo method more adaptable. Finally, a reliability analysis method is proposed to evaluate the reliability of the slope engineering, and is applied in the Sau Mau Ping slope project in Hong Kong. The reliability analysis method has great theoretical and practical significance for engineering quality evaluation and natural disaster assessment.
Keywords: slope reliability analysis   high-dimension   sparse grid   Monte Carlo simulation  
收稿日期 2019-03-12 修回日期 2019-04-15 网络版发布日期  
DOI: 10.3969/j.issn.1673-9736.2019.03.02
基金项目:

Supported by projects of China Ocean Research Mineral Resources R & D Association (COMRA) Special Foundation (DY135-R2-1-01, DY135-46), and the Province/Jilin University Co-Construction Project-Funds for New Materials (SXGJSF2017-3).

通讯作者: WU Hao
作者简介:
作者Email: moxingkong@hust.edu.cn
参考文献：
Barthelmann V, Novak E, Ritter K, et al. 2000. High dimension polynomial interpolation on sparse grids.Advances in Computational Mathematics,12(4):273-288.
Dubourg V, Sudret B, Bourinet J M,et al. 2011. Reliability based design optimization using kriging surrogates and subset simulation.Structural and Multidisciplinary Optimization,44(5):673-690.
Gerstner T, Griebel M. 1998. Numerical integration using sparse grids.Numerical Algorithms,18:209-232.
Gerstner T, Griebel M. 2003. Dimension-adaptive tensor-product quadrature.Computing,71(1):65-87.
Hu C, Youn B D. An asymmetric dimension-adaptive tensor-product method for reliability analysis.Structural Safety,33(3):218-231.
Jia B, Xin M, Cheng Y,et al. 2012. Sparse-grid quadrature nonlinear filtering.Automatica,48(2):327-341.
Klimke A, Willner K, Wohlmuth B,et al. 2004. Uncertainty modeling using fuzzy arithmetic based on sparse grids. International Journal of Uncertainty, Fuzziness and Knowdge-Based Systems,12(6):745-759.
Klimke A, Wohlmuth B. 2005. Piecewise multilinear hierarchical sparse grid interpolation in MATLAB.ACM Transactions on Mathematical Software,31(4):561-579.
Li D Q, Chen Y F, Lu W B,et al. 2011. Stochastic response surface method for reliability analysis of rock slopes involving correlated non-normal variables.Computers and Geotechnics,38(1):58-68.
Low B K. 2007. Reliability analysis of rock slopes involving correlated nonnormals.International Journal of Rock Mechanics and Mining Sciences,44(6):922-935.
Low B K. 2012. Roles of FORM, system-FORM, SORM, and RSM in geotechnical reliability analysis//Proceedings of the 5th Asian-Pacific Symposium on Structural Reliability and its Applications. Singapore:Research Publishing.
Ma X, Zabaras N. 2009. An adaptive hierarchical sparse grid collocation algorithm for the solution of stochastic differential equations,Journal of Computational Physics,228(8):3084-3113.
Sekhavatian A, Choobbasti A J. 2018. Reliability analysis of deep excavations by RS and MCS methods:case study. Innovative Infrastructure Solutions,3(1):https://doi.org/10.1007/s41062-018-0166-z
Vanem E. 2018.3-dimensional environmental contours based on a direct sampling method for structural reliability analysis of ships and offshore structures.Ships and Offshore Structures, 14:74-85.
Xiong F F, Greene S, Chen W,et al. 2010. A new sparse grid based method for uncertainty propagation.Structural and Multidisciplinary Optimization,41(3):335-349.
Yang X L, Zhou T, Li W T,et al. 2018. Reliability analysis of tunnel roof in layered Hoek-Brown rock masses.Computers and Geotechnics,104:302-309.
Zabaras N. 2007. Spare grid collocation schemes for stochastic natural convection problems.Journal of Computational Physics,225(1):652-685.
Zhang M. 2009. Structural reliability analysis-methods and procedures. Beijing:Science Press, 1-253. (in Chinese)
本刊中的类似文章
1．LIU Lipan, MO Xiuwen, ZHANG Youshuo, ZHANG Weifeng.Monte Carlo simulation for pulsed neutron-neutron loggingin fractured and cavernous carbonate formation[J]. Global Geology, 2020,23(1): 32-37
Copyright by Global Geology