Redirigiendo al acceso original de articulo en 19 segundos...
Inicio  /  Applied Sciences  /  Vol: 10 Par: 17 (2020)  /  Artículo
ARTÍCULO
TITULO

Study on the Early Warning Methods of Dynamic Landslides of Large Abandoned Rockfill Slopes

Nan Qiao    
Yun-Ling Duan    
Xiao-Meng Shi    
Xue-Fei Wei and Jin-Ming Feng    

Resumen

The excavation of large-scale underground projects produces a large amount of rubble waste material that is temporarily deposited near the project site, which forms a large-scale waste rockfill artificial slope. The slope has a granular structure, thus, during excavation and trans-shipment, surface shallow landslides may frequently occur. Existing contact monitoring methods such as buried sensors and GPS (Global Position System) are difficult to apply to the monitoring of rockfill landslides. Therefore, there are no appropriate early warning methods for waste rockfill slope landslides during dynamic transfer. Here, we used ground-based interferometric synthetic aperture radar to monitor the deformation of a rockfill slope during the excavation and transfer processes as a proposed method for the early warning against landslides on rockfill slopes during dynamic construction based on the radar interference measurement results. Through data cleaning and data interpolation, the line of equal displacement was generated, and the cross-sectional area of the equal displacement bodies of landslides was calculated. In addition, we established a four-level early warning grading standard, with the rate of change of the cross-sectional area of the equal displacement body as the early warning index, and realized real-time dynamic early warning of waste rockfill landslides during excavation and transportation. Finally, five landslide examples were used to verify the proposed warning method. The results show that the warning method can make an early warning 8?14 min before the occurrence of landslide, which can effectively avoid the appearance of catastrophic events.

 Artículos similares

       
 
Rachid Belaroussi, Elie Issa, Leonardo Cameli, Claudio Lantieri and Sonia Adelé    
Human impression plays a crucial role in effectively designing infrastructures that support active mobility such as walking and cycling. By involving users early in the design process, valuable insights can be gathered before physical environments are co... ver más
Revista: Algorithms

 
Fabi Prezja, Leevi Annala, Sampsa Kiiskinen and Timo Ojala    
Diagnosing knee joint osteoarthritis (KOA), a major cause of disability worldwide, is challenging due to subtle radiographic indicators and the varied progression of the disease. Using deep learning for KOA diagnosis requires broad, comprehensive dataset... ver más
Revista: Algorithms

 
Aquib Raza, Thien-Luan Phan, Hung-Chung Li, Nguyen Van Hieu, Tran Trung Nghia and Congo Tak Shing Ching    
Knee osteoarthritis (KOA) is a leading cause of disability, particularly affecting older adults due to the deterioration of articular cartilage within the knee joint. This condition is characterized by pain, stiffness, and impaired movement, posing a sig... ver más
Revista: Information

 
Yiannis Michailidis, Thodoris Kyzerakos and Thomas I. Metaxas    
Integrative neuromuscular training (INT) is commonly employed for preventing injuries, yet there is a scarcity of studies examining its impact on the physical capabilities of young athletes. This study sought to explore the influence of a brief, in-seaso... ver más
Revista: Applied Sciences

 
Dongye Lv, Hanbing Liu, Qiang Miao, Wensheng Wang, Guojin Tan, Chengwei Shi and Hanjun Li    
The passivation behavior of steel reinforcements in concrete is significantly influenced by the environment, concrete pore solution, and the passive film formed on the steel surface. The present study used electrochemical methods to successfully characte... ver más
Revista: Applied Sciences