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Effects of spatial autocorrelation structure for friction angle on the runout distance in heterogeneous sand collapse

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Ma, Guotao, Rezania, Mohammad and Mousavi Nezhad, Mohaddeseh (2022) Effects of spatial autocorrelation structure for friction angle on the runout distance in heterogeneous sand collapse. Transportation Geotechnics, 33 . 100705. doi:10.1016/j.trgeo.2021.100705

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Official URL: https://doi.org/10.1016/j.trgeo.2021.100705

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Abstract

This paper proposes a stochastic method for analyzing the runout distance of sand collapse considering the spatial variability of shear strength, in which random field theory and generalized interpolation material point method are integrated into a Monte-Carlo simulation basis. The random field is generated by Cholesky matrix decomposition method and implemented into the material point level, hence heterogeneity and large deformations are simultaneously considered in the modeling process. A sand collapse case is simulated with both homogeneous and heterogeneous condition assumptions by the proposed method. The effect of five theoretical autocorrelation functions (ACFs) on the runout distance of the collapse is highlighted since the ACFs are commonly adopted to characterize the spatial variability of soil properties due to sparse site observation data. It is shown that the deterministic analysis may underestimate the runout distance, while the heterogeneous model provides realistic results. Moreover, five ACFs and different coefficients of variation of friction angle (COV_φ) are compared to investigate their influences on the runout distance modeling. The results show that the uncertainty of runout distance increases with the increase in COV_φ. Meanwhile, the variances of the runout distance also become larger with COV_φ increasing. Based on the proportion of the runout distance which exceeds the deterministic value, the results indicate that the deterministic analysis notably underestimates the risk induced by large runout distances in real heterogeneous granular flows (e.g., landslide, debris-avalanches).

Item Type: Journal Article
Subjects: Q Science > QA Mathematics
T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TE Highway engineering. Roads and pavements
Divisions: Faculty of Science > Engineering
Library of Congress Subject Headings (LCSH): Sand, Landslides -- Forecasting, Landslides -- Mathematical models, Stochastic models, Random fields
Journal or Publication Title: Transportation Geotechnics
Publisher: Elsevier Inc.
ISSN: 2214-3912
Official Date: March 2022
Dates:
DateEvent
March 2022Published
22 December 2021Available
9 December 2021Accepted
Volume: 33
Article Number: 100705
DOI: 10.1016/j.trgeo.2021.100705
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Funder: European Commission Research Fund for Coal and Steel
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
RFCS-RPJ-899518European Commissionhttp://dx.doi.org/10.13039/501100000780
52150610492[NSFC] National Natural Science Foundation of Chinahttp://dx.doi.org/10.13039/501100001809
UNSPECIFIEDChinese Scholarship Councilhttps://www.chinesescholarshipcouncil.com/
UNSPECIFIEDUniversity of Warwickhttp://dx.doi.org/10.13039/501100000741

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