System reliability analysis in spatially variable slopes using coupled Markov chain and MARS
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ORIGINAL PAPER
System reliability analysis in spatially variable slopes using coupled Markov chain and MARS Dehui Kong 1 & Qiang Luo 1 & Wensheng Zhang 2 & Liangwei Jiang 1 & Liang Zhang 1 Received: 30 July 2020 / Accepted: 6 October 2020 # Saudi Society for Geosciences 2020
Abstract The soil heterogeneity has a significant impact on the stability of geotechnical structures. The inherent variability of parameters in one soil type comes from different deposition and tectonic conditions. Furthermore, geological uncertainty could be described by the distribution of varying soil types. Therefore, considering both the inherent variability and geological uncertainty of soil parameters, we introduced a coupled Markov chain (CMC) model to simulate the soil heterogeneity utilizing the field borehole data. Additionally, we initiated an extended Multivariate Adaptive Regression Spline (MARS) model-based Monte Carlo simulation (MCS). This technique is used to overcome the limits of the traditional response surface method that assumed both order and type of polynomials to perform the probabilistic analysis, which occurred in slope reliability evaluation. Our results have shown that the proposed MARS-based MCS approach could effectively conduct the probabilistic analysis with enough accuracy. The comparison of the probabilities of failure obtained by the MARS-based MCS and the other methods suggested that both the robustness and high accuracy of the MARS-based MCS have been discussed in different spatially varied soils. Even though the differences between these three approaches are insignificant, the reliability results obtained by the MARS-based MCS agree better with the results of the direct MCS results. Thus, these calibrated results indicated that the proposed MARS-based MCS could perform the system reliability analysis effectively and accurately. Keywords Reliability analysis . Geological uncertainty . Markov chain . Multivariate adaptive regression splines . Monte Carlo simulation
Introduction The heterogeneity of soil has a significant impact on the deformation and stability of geotechnical structures (Elkateb et al. 2003; Qu et al. 2018; Feng et al. 2018). Such soil heterogeneity includes (1) the inherent variability of soil parameters led by soil deposition or post-deposition, which is expressed as the difference in soil parameters at various points in space (Cherubini and Giasi 1999; Wei et al. 2018), and (2) geological uncertainty characterized by the staggering This article is part of the Topical Collection on Big Data and Intelligent Computing Techniques in Geosciences * Qiang Luo [email protected] 1
School of Civil Engineering, Southwest Jiaotong University, Chengdu 610031, China
2
MOE Key Laboratory of High Speed Railway Engineering, Chengdu 610031, China
occurrence of different geotechnical types or the irregular distribution of one soil in another homogeneous soil (Huang et al. 2015; Kasama et al. 2012). Most researches focus on the impact of inherent variability on geostructure reliability, while the effec
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