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Zhang M.,Hubei University | Yin Y.,China Institute of Geo Environment Monitoring | Huang B.,Hubei University
Landslides | Year: 2015

Red beds are widespread in the eastern Sichuan Basin, SW China, and are often called “landslide prone strata”. The dip angle of these red beds is commonly less than 10°, which is much less than the angle of internal friction between the bedding planes. Thus, in theory, failure will not occur along the bedding planes in such strata. We used field methods, numerical modeling, and ring shear tests to investigate the effects of rainfall on landslides in shallow-dipping red beds, using the Qingning landslide in SW China as an example. Our results suggest that the probable mechanisms leading to failure are (1) permeation of rainfall through the cracks at the back of the landslide site that increases the hydrostatic water pressure, which adds to the sliding stress and reduces the effective stress on the failure surface, gradually destabilizing the mass. In the Qingning landslide, the maximum water pressure was as high as 21.8 m before failure. When the factor of safety decreased markedly to 1.015, the sliding mass started to slowly slide. (2) As sliding takes place, the sliding zone soil is under undrained shear and its shear strength decreases sharply to a critical value, which promotes rapid sliding. In the Qingning landslide, the shear resistance of the sliding zone soil decreased markedly to 25.9 kPa as the pore water pressure increased to 118.3 kPa. This study may provide a theoretical basis for landslide forecasting in gently inclined red beds of the eastern Sichuan Basin as well as in similar geological settings worldwide. © 2015, Springer-Verlag Berlin Heidelberg. Source

Tong B.,China Institute of Geo Environment Monitoring | Tong B.,Iowa State University | Schaefer V.R.,Iowa State University
International Journal of Geomechanics | Year: 2016

Gravity-type caisson walls are a type of popular but easily damaged waterfront construction structure, especially in seismic regions. Various forms of mitigation have been successfully applied to improve their performance when subjected to liquefaction. Establishment of an effective, reliable, and easily implemented liquefaction remedial design procedure based on commonly used ground improvement technology is important. In this study, following the philosophy of performance-based design, a novel optimization process was developed and applied to a well-known case study. The vibrocompaction method was examined within a framework of a well-calibrated case history to hypothetically improve the seismic performance of a damaged caisson quay wall to an acceptable level. This study includes three major steps: first, the constitutive model used in this study for describing liquefaction was calibrated based on the published data; second, a caisson quay wall case history damaged by liquefaction was simulated as the unimproved benchmark; finally, the vibrocompaction method was applied as the mitigation technique to provide improvement to an acceptable level, and the mitigation design was optimized. The remedial program design characteristics, such as improved soil zone lateral extent in backfill soils and improved zone depth in foundation soils, were optimized. Through a parametric study, insights and recommendations on the establishment of liquefaction remediation design and optimization process for gravity-type caisson wall are provided for further study. © 2016 American Society of Civil Engineers. Source

Li T.,Tsinghua University | Xiao X.,Tsinghua University | Xue Q.,China Institute of Geo Environment Monitoring
Proceedings - 2012 IEEE Symposium on Robotics and Applications, ISRA 2012 | Year: 2012

In this paper we propose a new unsupervised and domain independent approach for sentiment classification. It takes a few documents as the training set to build a sentiment vocabulary list which will be used to classify the documents according to their sentiment orientation. The system is self-supervised and domain independent. Experimental results show that the classification accuracy of the approach can reach 85.7% which is better than the previous experiments of unsupervised methods. © 2012 IEEE. Source

Cheng G.M.,China Institute of Geo Environment Monitoring | Liu T.Z.,China University of Geosciences | Zhi B.,China University of Geosciences
Applied Mechanics and Materials | Year: 2014

In China, surface subsidence caused by steep coal seam mining has affected the safe operation of pipelines in recent years. The study site is one coal mine, where the gas pipeline from Shanshan to Urumqi is across. FLAC3D was adopted to study subsidence-induced stress on the pipeline, and the numerical model was calibrated with the measurement data. Visualization of alarm levels on the pipeline was obtained by integrating the usage of Fish function embedded in FLAC3D and Tecplot. The simulations reveal that the stress on the pipeline is closely related to the excavation depth. The stress on the pipeline increases with the excavation depth increasing when mining the 1st, 2nd, and 3rd levels, whereas the stress on the pipeline decreases slightly with the excavation depth increasing when mining the fourth, fifth, and sixth levels. The maximum stress on the pipeline occurs after mining the 3rd level. The possible damage to the pipe is at the upper-right side. Therefore, the results are helpful to prevent and reduce the impact of subsidence on the pipeline. © (2014) Trans Tech Publications, Switzerland. Source

Peng L.,Wuhan University | Peng L.,China Institute of Geo Environment Monitoring | Niu R.,Wuhan University | Huang B.,Chinese University of Hong Kong | And 3 more authors.
Geomorphology | Year: 2014

This paper aims to develop a novel hybrid model for assessing landslide susceptibility at the regional scale using multisource data to produce a landslide susceptibility map of the Zigui-Badong area near the Three Gorges Reservoir, China. This area is subject to anthropogenic influences because the reservoir's water level fluctuates cyclically between 145 and 175. m; in addition, the area suffers from extreme rainfall events due to the local climate. The area has experienced significant and widespread landslide events in recent years. In our study, a novel hybrid model is proposed to produce landslide susceptibility maps using geographical information systems (GIS) and remote sensing. The hybrid model is based on rough set (RS) theory and a support vector machine (SVM). RS theory is employed as an attribute reduction tool to identify the significant environmental parameters of a landslide, and an SVM is used to predict landslide susceptibility. Four data domains were considered in this research: geological, geomorphological, hydrology, and land cover. The original group of 20 environmental parameters and 202 landslides were used as the inputs to produce a landslide susceptibility map. According to the map, 19.7% of the study area was identified as medium- and high-susceptibility zones encompassing 89.5% of the historical landslides. The results indicate high levels of landslide hazard in and around the main inhabited areas, such as Badong County and other towns, as well as in rural residential areas and transportation areas along the Yangtze River and its tributaries. The predicted map indicates a good correlation between the classified high hazard areas and slope failures confirmed in the field. Furthermore, the quality of the proposed model was comprehensively evaluated, including the degree of model fit, the robustness of the model, the uncertainty associated with the probabilistic estimate, and the model prediction skill. The proposed model was also compared with the general SVM, which demonstrated that the hybrid model has superior prediction skill and higher reliability and confirmed the usefulness of the proposed model for landslide susceptibility mapping at a regional scale. © 2013 Elsevier B.V. Source

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