Effects of spatial auto-correlation structure for friction angle on runout distance in heterogeneous sand collapse

2021 ◽  
pp. 100705
Author(s):  
Guotao Ma ◽  
Mohammad Rezania ◽  
Mohaddeseh Mousavi Nezhad
Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-25
Author(s):  
Thanh Son Nguyen ◽  
Kuo-Hsin Yang ◽  
Chia-Chun Ho ◽  
Feng-Chi Huang

Although the mechanisms of slope failure caused by rising groundwater have been widely investigated, the kinematic behavior of landslides in the postfailure stage, which contains essential information for hazard mitigation and risk assessment, has not yet been fully studied. Thus, in this study, a series of numerical simulations using the material point method (MPM) were conducted to analyze the kinematic behavior and soil movement of shallow landslides (infinite slope problems). First, the proposed MPM formulation was validated in a full-scale landslide flume test. The simulated results of final slope profile, runout distance, deposit height, shear band development, slope displacement, and velocity accorded with the experimental results, suggesting that the MPM can quantitatively simulate large deformations. A parametric study of shallow slopes with various hydrological conditions and soil hydraulic and soil mechanical parameters was then performed to assess the influence of the aforementioned factors on landslide kinematics. The simulation results indicated that mechanical behavior at the slope toe is complex; the multiple plastic shear bands generated at the slope toe were due to a combination of shearing and compression. The deposition profile of the slopes was significantly influenced by all input parameters. Among the aforementioned parameters, soil cohesion, location of the groundwater table, and saturated soil permeability most greatly affected runout distance in the sensitivity assessment. Soil friction angle had a minor influence on the kinematic behavior of the slope.


2020 ◽  
Vol 8 (5) ◽  
pp. 3489-3492

The Electroencephalogram is frequently debased by muscle artifacts. Electroencephalogramis a generally utilized record method for the investigation of more mind associated infections, for example, epilepsy. The identification and elimination of muscle-artifacts from the Electroencephalogram signal represents a genuine test and is significant for the solid translation of Electroencephalogram-based computableactions. In this paper, an automatic strategy for identification and removal of muscle artifacts from Electroencephalogram signals, in light of free part investigation is presented. To this end, we exploid the way that the Electroencephalogram signal may display adjuussionsted auto-correlation structure and unearthly attributes for the period of when it is stained by muscle action. Thusly, we design classifiers so as to naturally separate among sullied and non-debased EEG ages utilizing highlights dependent on the previously mentioned amounts and look at their presentation on simulated data and in Electroencephalogram recordings got from patients with epilepsy.


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