Identification of Primary Failure Modes of Tunnel System and Influence of Supporting Structures on Tunnel System Reliability using Multiple Response Surfaces

Liu, Zhiliang; Li, Liang; Yu, Gaoming; Hu, Jun; Lin, Houlai; Li, Chunli; Lu, Shibao; Meng, Kaiqi; Liu, Jun

doi:10.1007/s12205-022-1924-1

Cited by 5 publications

(10 citation statements)

References 45 publications

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“…The key to the response surface function is to determine the 2mþ1constants. Following the research studies (Zhang et al, 2011;Liu et al, 2023b), 2mþ1sampling points are carefully designed to cover the potential random variable spaces. The yield acceleration of sampling points is calculated using the pseudo-static limit equilibrium method and is equated with k yi (X) obtained by Eq.…”

Section: The Identification Of Rssmentioning

confidence: 99%

“…The verification of response surface function. Before the calibrated RSF can be adopted to predict k y at unsampled points, it should be verified by comparing the predictions with those from pseudo-static limit equilibrium methods (Liu et al, 2023b;Ma and Liu, 2022). The verification steps are as follows:…”

Section: 32mentioning

confidence: 99%

“…The key to the response surface function is to determine the 2 m +1constants. Following the research studies (Zhang et al ., 2011; Liu et al. , 2023b), 2 m +1sampling points are carefully designed to cover the potential random variable spaces.…”

Section: Newmark Sliding Block Model With Representative Slip Surface...mentioning

confidence: 99%

“…An alternative method is the use of surrogate models in MCS, such as Response Surface Method (RSM) (Li et al. , 2023; Liu et al. , 2023b), Support Vector Machine (SVM) (Tan et al.…”

Section: Introductionmentioning

confidence: 99%

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Seismic reliability analysis of slope in spatially variable soils using multiple response surfaces

Li,

Cheng

et al. 2023

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PurposeThis paper aims to develop an efficient algorithm combining straightforward response surface functions with Monte Carlo simulation to conduct seismic reliability analysis in a systematical way.Design/methodology/approachThe representative slip surfaces are identified and based on to calibrate multiple response surface functions with acceptable accuracy. The calibrated response surfaces are used to determine the yield acceleration in Newmark sliding displacement analysis. Then, the displacement-based limit state function is adopted to conduct seismic reliability analysis.FindingsThe calibrated response surface functions have fairly good accuracy in predicting the yield acceleration in Newmark sliding displacement analysis. The seismic reliability is influenced by such factors as PGA, spatial variability and threshold value. The proposed methodology serves as an effective tool for geotechnical practitioners.Originality/valueThe multiple sources of a seismic slope response can be effectively determined using the multiple response surface functions, which are easily implemented within geotechnical engineering.

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Section: The Identification Of Rssmentioning

confidence: 99%

Section: 32mentioning

confidence: 99%

Section: Newmark Sliding Block Model With Representative Slip Surface...mentioning

confidence: 99%

“…An alternative method is the use of surrogate models in MCS, such as Response Surface Method (RSM) (Li et al. , 2023; Liu et al. , 2023b), Support Vector Machine (SVM) (Tan et al.…”

Section: Introductionmentioning

confidence: 99%

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Seismic reliability analysis of slope in spatially variable soils using multiple response surfaces

Li,

Cheng

et al. 2023

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“…In order to improve the computational efficiency of MCS simulation, surrogate models have been developed to establish the relationship between the random variables and the response of geotechnical structures (e.g., the relationship between soil strength parameters and slope sliding displacement). The developed surrogate models within the literature include but not limited to response surface method (RSM), [31][32][33][34][35] artificial neural network (ANN), 36,37 support vector machine (SVM), 38,39 multivariate adaptive regression splines (MARS), 40 random forest (RF), [41][42][43] convolutional neural network (CNN). Response surface method is widely used in slope reliability analysis due to its simplicity.…”

Section: Introductionmentioning

confidence: 99%

Seismic reliability analysis of soil slope based on Newmark sliding block model with representative slip surfaces and response surfaces

et al. 2023

Engineering Reports

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This paper presents a framework combining Monte Carlo Simulation (MCS) and the Newmark sliding block model with representative slip surfaces (RSS) (model II) and multiple response surfaces method (MRSM) to conduct seismic reliability analysis and risk assessment of soil slopes. An empirical threshold is introduced to define the limit state function to identify the failure samples in MCS and the sliding area and Newmark sliding displacement are multiplied to quantify the failure consequence. The proposed methodology is illustrated through a soil slope with multiple layers. The calculation results demonstrate that traditional Newmark sliding block model (model I) tend to underestimate the variations of yield acceleration. Both the failure probability and landslide risk exhibit decreasing trends with the increase of threshold. Significant discrepancy in failure probability and landslide risk between two models is found even for a small threshold. Therefore, the proposed methodology is highly recommended in seismic reliability analysis and risk assessment. The contributions of RSSs to the failure probability and landslide risk are insensitive to the variation of displacement thresholds.

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Reliability analysis of deep tunnels in spatially varying brittle rocks using interval and random field modelling

Kumar,

Maurya,

Tiwari

2024

International Journal of Rock Mechanics and Mining Sciences

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Identification of Primary Failure Modes of Tunnel System and Influence of Supporting Structures on Tunnel System Reliability using Multiple Response Surfaces

Cited by 5 publications

References 45 publications

Seismic reliability analysis of slope in spatially variable soils using multiple response surfaces

Seismic reliability analysis of slope in spatially variable soils using multiple response surfaces

Seismic reliability analysis of soil slope based on Newmark sliding block model with representative slip surfaces and response surfaces

Reliability analysis of deep tunnels in spatially varying brittle rocks using interval and random field modelling

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