The 2009 Jiweishan rock avalanche, Wulong, China: deposit characteristics and implications for its fragmentation

Ming, Zhang; Wu, L. Z.; Zhang, Juncai; Li, Liangping

doi:10.1007/s10346-019-01142-6

Cited by 47 publications

(25 citation statements)

References 79 publications

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“…[ 16 ] In general, these parameters are determined through a trial‐and‐error analysis with prior knowledge generated from past studies. [ 18,30,36,37,38 ] The particle‐boundary contact parameters (i.e., basal friction coefficients) and damping coefficients, shown in Figure 2a and Table 1, are consistent with the values adopted in Zou et al., [ 18 ] while the contact micro‐parameters among the particles are calibrated through a series of 2‐D uniaxial compression simulation, as illustrated in Figure 2b.…”

Section: Deterministic Simulation Of the Jiweishan Landslide With Pfcsupporting

confidence: 77%

“…Also shown in Table 1 are the macro‐parameters of the sliding mass obtained from the laboratory tests. [ 56,57 ]…”

Section: Deterministic Simulation Of the Jiweishan Landslide With Pfcmentioning

confidence: 99%

“…In the conventional PFC simulation, a trial‐and‐error process is often adopted to single‐out the most appropriate set of micro‐parameters. [ 30 ] As a result, the true behavior of the concerned landslide may not be fully captured by the simulated behavior, as shown in Figure 3. To overcome this concern, all possible combinations of the micro‐parameters that yield the true macro‐parameters of the sliding mass should be systematically examined in the PFC simulation of the landslide runout behaviors.…”

Section: Characterization Of the Uncertainty In The Input Micro‐parameters Within Pfcmentioning

confidence: 99%

“…According to Li et al., [ 29 ] a set of macro‐parameters (i.e., uniaxial compressive strength, Young's modulus, and Poisson's ratio) of the sliding mass could be associated with various combinations of micro‐parameters. In the conventional PFC simulations of landslides; however, only a single set of micro‐parameters is adopted, [ 30 ] where the influence of each micro‐parameter is studied through parametric analyses. [ 31 ] In other words, the conventional PFC simulations of landslide runout behaviors are a deterministic process, and uncertainty in the selection of the input micro‐parameters is not explicitly considered.…”

Section: Introductionmentioning

confidence: 99%

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Probabilistic analysis of a discrete element modelling of the runout behavior of the Jiweishan landslide

Bing

Gong

Tang

et al. 2021

Num Anal Meth Geomechanics

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Landslide is one of the most destructive geohazards around the world. The destruction of a landslide can be estimated from its deformation and runout behaviors, which might be simulated with numerical software such as particle flow code (PFC). In the PFC simulation of the runout behavior of a landslide, the results are dependent upon the particle‐particle contact micro‐parameters (e.g., contact modulus and friction coefficient). The calibration of the micro‐parameters of the PFC models is a challenge and various uncertainties are involved. The uncertainty in the selection of the modelling parameters leads to uncertainty in the simulated runout behavior of the landslide. As a result, the damage potential of the landslide cannot be accurately evaluated. To this end, this paper presents a probabilistic analysis of the runout behavior of the Jiweishan landslide, in which the uncertainty in the selection of the particle‐particle contact micro‐parameters is explicitly considered. Here, the input micro‐parameters are modeled as discrete random variables, the possible realizations of which are obtained through an orthogonal analysis of the PFC simulation‐based uniaxial compression tests. The derived possible realizations of the micro‐parameters are then adopted as the inputs to the built model of the landslide. With the results obtained from these PFC simulations, the runout behaviors of the Jiweishan landslide, such as the runout distance and the deposit thickness, are studied probabilistically. The results provide an improved estimate of the landslide runout behavior and further aid in making an informed risk assessment of the landslide.

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Section: Deterministic Simulation Of the Jiweishan Landslide With Pfcsupporting

confidence: 77%

“…Also shown in Table 1 are the macro‐parameters of the sliding mass obtained from the laboratory tests. [ 56,57 ]…”

Section: Deterministic Simulation Of the Jiweishan Landslide With Pfcmentioning

confidence: 99%

Section: Characterization Of the Uncertainty In The Input Micro‐parameters Within Pfcmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Probabilistic analysis of a discrete element modelling of the runout behavior of the Jiweishan landslide

Bing

Gong

Tang

et al. 2021

Num Anal Meth Geomechanics

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show abstract

“…The colluvium in the front of the deposit simulated here also supports the plowing process ( Figure 10F), but it is difficult to distinguish the new deposits from the path materials in this study because they are the products of the same kind of rock fragmentation. This phenomenon was observed in a similar landslide, the 2009 Jiweishan rock avalanche in Chongqing, China, wherein loose soil on the transport path was bulldozed to the very front and pushed passively by the rock debris, rather than remaining at the bottom and reducing frictional resistance between the debris and the ground through the deposit investigation and numerical simulation by Zhang et al (2019).…”

Section: Discussionmentioning

confidence: 64%

Numerical Simulation of the 2017 Xinmo Catastrophic Landslide Considering Entrainment Effect

2020

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The mass movement process of the 2017 Xinmo catastrophic landslide was simulated using the discreet element method (DEM). Field investigation indicates that the basal entrainment is a typical feature of this landslide. Hence, the entrained colluvium on the sliding path is considered in the DEM model. According to the terrain elevation data before and after sliding, the slope geometry is divided into three parts: sliding bed, sliding body, and colluvium on the path. The blocks are generated in MATLAB and a fill-remove method has been used to produce the loose colluvium. The key parameter, contact friction angel, which controls the mobility of mass movement, has been obtained through displacement back analysis. The simulated deposit area and main sliding time coincide with actual landslide characteristics. Simulation results indicate that the colluvium is pushed to the bottom of the Songpinggou Valley by the sliding body. The local topography has a significant influence on the sliding direction. Some typical phenomena of substrate entrainment, including frontal plowing, mass spray, shear zones in substrate, thickened substrate, and basal abrasion, are observed in the DEM simulation. During the entrainment process, the frontal plowing, or the thrust, plays an important role in creating the substrate failure compared with basal abrasion. After the failure of the whole colluvium, the magnitude of thrust descends quickly but is still slightly larger than that of shear thrust. Entrainment of dry material on the slope leads to more friction energy consumption and reduces the mobility of mass movement. This work shows a good capability of simulating entrainment of dry materials using a discreet element method and highlights the significance of plowing relative to the basal abrasion under conditions of limited path material supply.

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Micro-seismic source location determined by a modified objective function

Huang

et al. 2019

Engineering with Computers

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The 2009 Jiweishan rock avalanche, Wulong, China: deposit characteristics and implications for its fragmentation

Cited by 47 publications

References 79 publications

Probabilistic analysis of a discrete element modelling of the runout behavior of the Jiweishan landslide

Probabilistic analysis of a discrete element modelling of the runout behavior of the Jiweishan landslide

Numerical Simulation of the 2017 Xinmo Catastrophic Landslide Considering Entrainment Effect

Micro-seismic source location determined by a modified objective function

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