Model Updating of Slope Stability Analysis Using 3D Conditional Random Fields

Ouyang, Jiayi; Liu, Yong; Yao, Kai; Yang, Chenjun; Niu, Hui-Feng

doi:10.1061/ajrua6.0001150

Cited by 8 publications

(2 citation statements)

References 36 publications

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“…In geotechnical engineering, predictions of slope models often differ significantly from the measured results. Thus, the model updating approach can assist engineers in calibrating geotechnical material parameters or numerical models by incorporating test data, monitoring data, and field observation data 26–28 . Bayesian methods stand out as a frequently employed strategy in model updating, providing a probabilistic perspective to address the challenges of refining models 29–31 .…”

Section: Introductionmentioning

confidence: 99%

“…Thus, the model updating approach can assist engineers in calibrating geotechnical material parameters or numerical models by incorporating test data, monitoring data, and field observation data. [26][27][28] Bayesian methods stand out as a frequently employed strategy in model updating, providing a probabilistic perspective to address the challenges of refining models. [29][30][31] The most common method of Bayesian updating is carried out through sampling techniques, such as Markov chain Monte Carlo (MCMC) methods.…”

Section: Introductionmentioning

confidence: 99%

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Experimental model updating of slope considering spatially varying soil properties and dynamic loading

Wang,

Ouyang,

Fragkoulis

et al. 2024

Earthquake Engineering and Resilience

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The widespread threat posed by slope structure failures to human lives and property safety is widely acknowledged. Additionally, natural soil often displays spatial variability due to geological deposition and other factors. Therefore, predicting the seismic response of slopes subjected to ground motions and inversely analyzing the spatial distribution of soils remains an unresolved issue. In the present work, a shaking table experimental test is first designed and carried out, in which a soft‐soil slope dynamic system is established. To capture the seismic response of the soft‐soil slope, specifically the experimental characteristic of acceleration and soil pressure response in both spatial domain and time domain, a series of sensors were pre‐embedded in the slope. Subsequently, a model updating approach is proposed for slope seismic analysis that incorporates spatial variability of soil. In addition, to enhance computational efficiency, the dimensionality reduction of Karhunen–Loève expansion method is introduced to reduce inverse analysis parameters. On the basis of 34 samples collected from experimental data, it is shown that near‐fault pulse‐like ground motions deliver greater concentrated energy, causing more severe damage to slope structures, especially the topsoil layer. Furthermore, using data obtained from a shaking table test subjected to ground motion Recorded Sequence Number 158H1 from the Pacific Earthquake Engineering Research Center NGA‐West2 database as an example, it is also shown that the proposed approach demonstrates high accuracy in predicting the spatial distribution of the maximum shear modulus in soil slope dynamic systems. The present work not only addresses the challenges posed by mainshock–aftershock effects but also highlights the potential of model updating approaches to enhance the understanding of slope behavior under seismic loading conditions.

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Section: Introductionmentioning

confidence: 99%