Improved coupled Markov chain method for simulating geological uncertainty

Zhang, Jinzhang; Liu, Zhongqiang; Zhang, Dongming; Huang, Hongwei; Phoon, Kok‐Kwang; Xue, Yadong

doi:10.1016/j.enggeo.2022.106539

Cited by 46 publications

(7 citation statements)

References 58 publications

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“…The traditional CMC model proposed by Elfeki and Dekking 41,42 is widely used for characterizing the stratigraphic uncertainty. Based on the traditional CMC model, researchers proposed several improved CMC models to overcome the limitations of CMC model 43–46 . To solve the difficulty of estimating the HTPM, Cao et al 47 .…”

Section: Methodsmentioning

confidence: 99%

“…Based on the traditional CMC model, researchers proposed several improved CMC models to overcome the limitations of CMC model. [43][44][45][46] To solve the difficulty of estimating the HTPM, Cao et al 47 proposed an enhanced CMC model with an analytical HTPM estimation method based on Walther's law and the maximum likelihood estimation method. According to Walther's law, the HTPM can be calculated by the following two equations:…”

Section: Enhanced Cmc Model For Stratigraphic Uncertainty Simulationmentioning

confidence: 99%

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Stability of unsaturated soil slope considering stratigraphic uncertainty and rotated anisotropy of soil properties

Cao,

Zhou,

Shen

2023

Num Anal Meth Geomechanics

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The stratigraphic uncertainty and rotated anisotropy of soil properties exist widely in nature. Recent studies have shown that the slope stability was significantly influenced by these two uncertainties. However, there is no proper method for simulating these two uncertainties at the same time, and the influence of the two uncertainties has not been considered in previous unsaturated soil slope stability analysis. This paper aims to propose a coupled method for characterizing the stratigraphic uncertainty and rotated anisotropy of soil properties, and investigate the unsaturated soil slope stability considering the two uncertainties. Through a slope case, the proposed method for characterizing the two uncertainties is examined. The effect of rotational angle on the slope stability and groundwater table is studied. In addition, four different uncertainty considerations are chosen to compare their influence on the slope stability and groundwater table. The results show that the proposed method can well characterize the two uncertainties at the same time. The rotational anisotropy of soil properties has a substantial impact on the slope stability and groundwater table. The rotational angles corresponding to the maximum and minimum reliability index of slope depend on the uncertainty considerations in the slope stability analysis. The slope reliability index only considering stratigraphic uncertainty is the highest, and the slope reliability index considering stratigraphic uncertainty and rotated anisotropy of soil properties is the lowest.

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Section: Methodsmentioning

confidence: 99%

Section: Enhanced Cmc Model For Stratigraphic Uncertainty Simulationmentioning

confidence: 99%

Stability of unsaturated soil slope considering stratigraphic uncertainty and rotated anisotropy of soil properties

Cao,

Zhou,

Shen

2023

Num Anal Meth Geomechanics

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“…Recently, to estimate the subsurface uncertainty effectively, machine learning-based models, such as the Markov random field model (MRF) [4], coupled Markov chain model [5], and iterative convolutional XGBoost [6], with their advances in artificial intelligence and uncertainty quantification, have been widely applied to geotechnical engineering. Most existing approaches have been implemented in two-dimensional settings.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional stochastic model for stratigraphic uncertainty quantification using Bayesian machine learning

Wang,

Wei

2024

IOP Conf. Ser.: Earth Environ. Sci.

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Data-driven geotechnics is an emerging research field that contributes to the digitalization of geotechnical engineering. Among the numerous applications of digital techniques in geotechnical engineering, interpreting and simulating stratigraphic conditions with quantified uncertainty is an essential task and an open question in geotechnical practice. However, developing an uncertainty-aware integration of subjective engineering judgments (i.e., geological knowledge) and sparse objective site exploration results (i.e., borehole observations) is challenging. This investigation develops an effective three-dimensional stochastic geological modeling framework based on Markov random field (MRF) theory and Bayesian machine learning to characterize stratigraphic uncertainty. The proposed model considers both stratigraphic uncertainty (inherent) and model uncertainty (imperfect knowledge). A stratigraphic modeling example was studied to demonstrate the effectiveness of the proposed approach. We envision that this approach could be further generalized to industrial practices to improve risk control in geotechnical engineering.

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“…Among these models, the CMC model is widely used in stratigraphic modeling for its simplicity in theory and other advantages [22]. Based on the CMC model, some improvements have been made by researchers to enhance the abilities of stratigraphic uncertainty simulation [23][24][25]. For example, to apply the CMC model to small-scale geological engineering problems, Qi et al [22,26] proposed a method to estimate the horizontal transition probability matrix (HTPM) by using borehole data.…”

Section: Introductionmentioning

confidence: 99%

Stability of Unsaturated Soil Slope Considering Stratigraphic Uncertainty

Cao

Wan

Li³

2023

Sustainability

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Stratigraphic uncertainty is widely present in nature, but it has not been well considered in the stability analysis of unsaturated soil slopes in the past. In this study, the stability of the unsaturated soil slope is evaluated based on borehole data considering stratigraphic uncertainty. Firstly, an enhanced coupled Markov chain model is used to simulate stratigraphic uncertainty. Then, a finite element algorithm for automatically calculating the safety factor (FS) and the average groundwater table (AGT) of the unsaturated soil slope is developed. At last, a hypothetical slope located in the stratum from Perth, West Australia is analyzed using the proposed algorithm under different borehole schemes. The results show that with the increase in the borehole number, the statistics of FS and AGT will not monotonically increase or decrease. But the trend is that the mean values of FS and AGT gradually approach and eventually converge to the real values, and the standard deviations of FS and AGT decrease. There is a linear relationship between the standard deviation of FS (or AGT) and the average information entropy. The FS and AGT are negatively correlated considering stratigraphic uncertainty.

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Improved coupled Markov chain method for simulating geological uncertainty

Cited by 46 publications

References 58 publications

Stability of unsaturated soil slope considering stratigraphic uncertainty and rotated anisotropy of soil properties

Stability of unsaturated soil slope considering stratigraphic uncertainty and rotated anisotropy of soil properties

Three-dimensional stochastic model for stratigraphic uncertainty quantification using Bayesian machine learning

Stability of Unsaturated Soil Slope Considering Stratigraphic Uncertainty

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