Reliability Analysis of Rock Wedge Stability: Knowledge-Based Clustered Partitioning Approach

Lee, Ya Fen; Yao, Yasuhiro; Juang, C. Hsein; Lee, Der Her

doi:10.1061/(asce)gt.1943-5606.0000618

Cited by 38 publications

(6 citation statements)

References 22 publications

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“…Lee et al 17 developed a Knowledge-based Clustered Partitioning (KCP) technique for determining reliability index and failure probability of rock wedge. Also in their research, the computed reliability index with this KCP technique was compared with those using other approaches such as the Excel solver-based method.…”

Section: Introductionmentioning

confidence: 99%

System reliability analysis of rock wedge stability considering correlated failure modes using sequential compounding method

Johari

Lari

2016

International Journal of Rock Mechanics and Mining Sciences

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Section: Introductionmentioning

confidence: 99%

System reliability analysis of rock wedge stability considering correlated failure modes using sequential compounding method

Johari

Lari

2016

International Journal of Rock Mechanics and Mining Sciences

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“…Furthermore, the COVs of COV[c], COV [u], and q c,u are assumed to be 0.17, 0.12, and 0.25, respectively. Meanwhile, these random variables are assumed to follow a normal distribution, and therefore the ranges of COV[c], COV [u], and q c,u can roughly cover the typical ranges reported in the literature (Low 2008;Lee et al 2011;Wang et al 2013). Thus, among the statistics of the noise factors, COV[c], COV [u], and q c, u are treated as uncertain variables, while the remainder are treated as fixed values as given in Table 1 in this reliability-based RGD of a rock slope.…”

Section: And LImentioning

confidence: 99%

Reliability-based robust geotechnical design using Monte Carlo simulation

Peng

Cao

et al. 2016

Bull Eng Geol Environ

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The reliability-based robust geotechnical design (RGD) approach provides an effective tool to deal with the uncertainty in the estimated statistics of geotechnical parameters in a reliability-based design. However, the existing reliability-based RGD approach is not straightforward to apply as it involves multiple concepts. In this paper, the applicability of the existing reliability-based RGD approach is improved by utilizing Monte Carlo simulation (MCS). Here, an MCS-based weighted technique is used to evaluate the failure probability of a geotechnical system. With the aid of this weighted technique, the variation in the failure probability, caused by the uncertainty in the estimated statistics of geotechnical parameters, is computed using MCS. To further improve the efficiency of the RGD method, a series of singleobjective optimizations are used in lieu of a multi-objective optimization in the robust design optimization process. The proposed MCS-based RGD approach is illustrated through an example of rock slope design. Compared with the existing reliability-based RGD approach, the MCS-based RGD approach is not only more intuitive and easier to follow, but also more computationally efficient.

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“…The approach has been applied to perform wedge failure reliability assessment (Einstein & Low, 1992;Jimenez-Rodriguez, Sitar, & Chacón, 2006;Low, 1997;Low & Einstein, 2013). The reliability of wedges has also been studied considering multiple correlated failure modes and knowledge-based clustered partitioning approach (Lee et al, 2012).…”

Section: Wedge Stability Modelmentioning

confidence: 99%

Updating the probability of failure of rock wedges

Hernández-Carrillo

Beltrán

2019

Earth sci. res. j.

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In hard rock masses, discontinuities control the slope stability, rather than block matrix breakage. The relative position of joints and slope face defines the most likely mechanisms of failure. Among these mechanisms, the wedge failure is one of the most common ways of failure in which joint sets dip and dip direction, slope geometry and direction, external forces (including water pressure and earthquake) and rock and joints mechanical properties control the stability. The determination of these input parameters is not straightforward, mainly due to their variability and the limited amount of information available. Besides, in most projects, input parameters come from different sources (e.g., expert opinion, back-calculation, laboratory tests, field test or different project stages). Therefore, this limited information from different sources should be appropriately incorporated into the stability analysis to assist the design and decision-making process. In this context, random sets arise as a powerful tool to combine different sources of information and to perform a reliability assessment under limited information. This feature makes it possible to update the probability of failure as new evidence is available. With this framework, this paper presents a reliability assessment of wedge stability in a rock slope of a sandstone quarry, located in Une Cundinamarca, where information on mechanical and geometrical parameters has been collected for 20 years.

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Reliability Analysis of Rock Wedge Stability: Knowledge-Based Clustered Partitioning Approach

Cited by 38 publications

References 22 publications

System reliability analysis of rock wedge stability considering correlated failure modes using sequential compounding method

System reliability analysis of rock wedge stability considering correlated failure modes using sequential compounding method

Reliability-based robust geotechnical design using Monte Carlo simulation

Updating the probability of failure of rock wedges

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