Probabilistic Analysis of Piping in Habdat Earthen Embankment Using Monte Carlo and Subset Simulation: A Case Study

被引:7
|
作者
Shekhar, Sudhanshu [1 ]
Ram, Shri [1 ]
Burman, Avijit [2 ]
机构
[1] Madan Mohan Malaviya Univ Technol, Dept Civil Engn, Gorakhpur 273010, Uttar Pradesh, India
[2] Natl Inst Technol Patna, Dept Civil Engn, Patna 800005, Bihar, India
关键词
Earthen Embankment; Piping; Probability of failure; Monte Carlo simulation; Subset simulation; ORDER RELIABILITY METHOD; STABILITY ANALYSES; SLOPE STABILITY; SURFACE; SOIL;
D O I
10.1007/s40098-022-00614-2
中图分类号
P5 [地质学];
学科分类号
0709 ; 081803 ;
摘要
In recent years, reliability analysis has become an integral part of any design work of engineering structures to establish its success by considering the various uncertainties involved. The sources of uncertainties are generally the variation of material properties throughout the domain of interest, loadings, estimation procedure, mechanical and manual errors, etc. In this paper, the probabilistic analysis of Habdat earthen embankment has been performed using both Monte Carlo (MCS) and Subset Simulation (SS) techniques. The local seepage velocity is considered to carry out piping analysis considering hydraulic permeability (k) of soil as a random variable in an MS-Excel sheet. The performance of horizontal filter at the base of embankment in the prevention of piping is also investigated. It is found that the filter suppresses the phreatic line and provides safety against piping as it helps to increase the flow length of the water and reduce the exit gradient (i(e)). It is further noticed that SS can investigate low probability of failure events up to 0.001 with a smaller number of samples compared to direct MCS. This fact indicates that SS performs better than direct MCS in estimating risk for important engineering structures designed for low P-f values.
引用
收藏
页码:907 / 926
页数:20
相关论文
共 50 条
  • [31] Monte Carlo integration - a case-study for simulation
    Ritter, Stefan
    INTERNATIONAL JOURNAL OF MATHEMATICAL EDUCATION IN SCIENCE AND TECHNOLOGY, 2014, 45 (01) : 131 - 145
  • [32] Probabilistic analysis of flood embankment stability: the case study of the Adige River embankment in Italy
    Amabile, Alessia
    De Polo, Fabio
    Tarantino, Alessandro
    4TH EUROPEAN CONFERENCE ON UNSATURATED SOILS (E-UNSAT 2020), 2020, 195
  • [33] GPU-OpenCL accelerated probabilistic power flow analysis using Monte-Carlo simulation
    Abdelaziz, Morad
    ELECTRIC POWER SYSTEMS RESEARCH, 2017, 147 : 70 - 72
  • [34] Probabilistic analysis of stability of chain pillars in Tabas coal mine in Iran using Monte Carlo simulation
    Najafi, M.
    Jalali, S. M. E.
    Sereshki, F.
    Bafghi, A. R. Yarahmadi
    JOURNAL OF MINING AND ENVIRONMENT, 2016, 7 (01): : 25 - 35
  • [35] Probabilistic Analyses of Root-Reinforced Slopes Using Monte Carlo Simulation
    Pisano, Marilene
    Cardile, Giuseppe
    GEOSCIENCES, 2023, 13 (03)
  • [36] Probabilistic forecasting of distributed river stage conditions using a Monte Carlo simulation
    Smith, Paul James
    Kojiri, Toshiharu
    GIS and Remote Sensing in Hydrology, Water Resources and Environment, 2004, 289 : 66 - 72
  • [37] PROBABILISTIC ANALYSIS AND MONTE-CARLO SIMULATION OF THE KINEMATIC ERROR IN A SPATIAL LINKAGE
    XU, WL
    ZHANG, QX
    MECHANISM AND MACHINE THEORY, 1989, 24 (01) : 19 - 27
  • [38] Probabilistic analysis for mechanical properties of glass/epoxy composites using homogenization method and Monte Carlo simulation
    Lee, Seung-Pyo
    Jin, Ji-Won
    Kang, Ki-Weon
    RENEWABLE ENERGY, 2014, 65 : 219 - 226
  • [39] Probabilistic evaluation of flood hazard in urban areas using Monte Carlo simulation
    Aronica, G. T.
    Franza, F.
    Bates, P. D.
    Neal, J. C.
    HYDROLOGICAL PROCESSES, 2012, 26 (26): : 3962 - 3972
  • [40] Efficient Monte Carlo Simulation of parameter sensitivity in probabilistic slope stability analysis
    Wang, Yu
    Cao, Zijun
    Au, Siu-Kui
    COMPUTERS AND GEOTECHNICS, 2010, 37 (7-8) : 1015 - 1022