Effects of Discontinuities on Rock Slope

2018 ◽  
pp. 57-65
Author(s):  
Aniruddha Bhaduri ◽  
B. K. Maheshwari
Keyword(s):  
Rock Slope

scholarly journals Correction to: GAMAH‑R: a new mining rock slope classification system

2021 ◽  
Author(s):  
Flávio Affonso Ferreira Filho ◽  
Romero César Gomes ◽  
Teófilo Aquino Vieira da Costa
Keyword(s):  
Classification System ◽  
Rock Slope

scholarly journals Study on rapid ecological protection of rock slope

2020 ◽  
Vol 525 ◽  
pp. 012051
Author(s):  
Yunming Aocun ◽  
Yapin Lv ◽  
Qingan Wang ◽  
Tianwei Xia
Keyword(s):  
Rock Slope ◽  
Ecological Protection

scholarly journals Deformation response and anchorage control of excavation unloading of high and steep rock slope

2020 ◽  
Vol 570 ◽  
pp. 042010
Author(s):  
Zhihong Dong ◽  
Xiuli Ding ◽  
Shuling Huang ◽  
Yongjin Wu ◽  
Aiqing Wu
Keyword(s):  
Rock Slope ◽  
Deformation Response

scholarly journals Semi-automated regional classification of the style of activity of slow rock-slope deformations using PS InSAR and SqueeSAR velocity data

Landslides ◽  
2021 ◽  
Author(s):  
Chiara Crippa ◽  
Elena Valbuzzi ◽  
Paolo Frattini ◽  
Giovanni B. Crosta ◽  
Margherita C. Spreafico ◽  
...  
Keyword(s):  
Rock Slope ◽  
Progressive Failure ◽  
Principal Component ◽  
Cost Effective ◽  
Displacement Rate ◽  
Machine Learning Classification ◽  
Management Perspective ◽  
Alpine Environments

AbstractLarge slow rock-slope deformations, including deep-seated gravitational slope deformations and large landslides, are widespread in alpine environments. They develop over thousands of years by progressive failure, resulting in slow movements that impact infrastructures and can eventually evolve into catastrophic rockslides. A robust characterization of their style of activity is thus required in a risk management perspective. We combine an original inventory of slow rock-slope deformations with different PS-InSAR and SqueeSAR datasets to develop a novel, semi-automated approach to characterize and classify 208 slow rock-slope deformations in Lombardia (Italian Central Alps) based on their displacement rate, kinematics, heterogeneity and morphometric expression. Through a peak analysis of displacement rate distributions, we characterize the segmentation of mapped landslides and highlight the occurrence of nested sectors with differential activity and displacement rates. Combining 2D decomposition of InSAR velocity vectors and machine learning classification, we develop an automatic approach to characterize the kinematics of each landslide. Then, we sequentially combine principal component and K-medoids cluster analyses to identify groups of slow rock-slope deformations with consistent styles of activity. Our methodology is readily applicable to different landslide datasets and provides an objective and cost-effective support to land planning and the prioritization of local-scale studies aimed at granting safety and infrastructure integrity.

Characterization of artificially reconstructed clayey soil treated by polyol prepolymer for rock-slope topsoil erosion control

2021 ◽  
Vol 287 ◽  
pp. 106114
Author(s):  
Zezhuo Song ◽  
Jin Liu ◽  
Yongxiang Yu ◽  
Shefeng Hao ◽  
Bo Jiang ◽  
...  
Keyword(s):  
Rock Slope ◽  
Clayey Soil ◽  
Erosion Control

Reliability parameter back analysis of bedding rock slope with multi-layer slide surfaces

2021 ◽  
Author(s):  
Shi Zuo ◽  
Lianheng Zhao ◽  
Hanhua Tan ◽  
Liang Li ◽  
Dongping Deng ◽  
...  
Keyword(s):  
Rock Slope ◽  
Back Analysis ◽  
Reliability Parameter ◽  
Bedding Rock Slope
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