Font Size: a A A

Study On Damage Process And Early Warning Model Of Bedding Rock Landslide

Posted on:2021-05-28Degree:MasterType:Thesis
Country:ChinaCandidate:J BaiFull Text:PDF
GTID:2370330647463475Subject:Architecture and civil engineering
Abstract/Summary:PDF Full Text Request
Bedding rock landslides are widely distributed in our country,and cause huge casualties and economic property losses every year,which is a kind of geological disaster with great harm.Although scholars at home and abroad have a relatively systematic and in-depth understanding of the formation mechanism of such landslides,bedding rock landslides have the characteristics of sudden and destructive.How to establish effective landslide early warning criteria and models,improve the reliability of bedding rock landslides monitoring and early warning,so as to reduce disaster losses,remains to be further studied.In this paper,we take Xingyi 2.17 landslide in Guizhou Province as the research object.Through field investigation and related data research,we analyze the structural characteristics and influencing factors of the landslide.Through the comprehensive application of satellite remote sensing,UAV aerial photography,surface displacement monitoring and other technical means,we preliminarily revealed the deformation and failure process of the landslide,and analyzed its genetic mechanism.The results show that Xingyi landslide is a typical bedding rock landslide,which has unfavorable structural characteristics such as weak interlayer,high and steep free surface.After the excavation of slope toe,under the action of long-term gravity and groundwater,it eventually evolved into landslide geological disaster.Then,taking Xingyi landslide as the prototype,we set up a geological model of bedding rock landslide,carried out physical simulation test,and reproduced the process of landslide deformation and instability.At the same time,we use acoustic emission detection technology to reveal the law of rock mass damage changes in the process of Landslide Evolution,and based on this,we propose a landslide early warning model based on rock mass damage and fracture,which provides a new idea and method for landslide early warning.Through the research of this paper,the main achievements are as follows:(1)We have found out the geological conditions and failure modes of the typical bedding rock landslide Xingyi landslide in Guizhou Province.Xingyi landslide in Guizhou Province is developed from a typical bedding rock slope with weak intercalation.The slope rock mass is mainly composed of hard dolomite with occurrence of 52 °? 22 °.There is a weak layer with thickness of about 1 m in it.The original stable structure is long-term free because of the excavation of the slope toe.In addition,many factors such as the geological structure and the development of joints and fissures form the slope structure which is not conducive to the stability of the slope.After the excavation of the slope toe,it deforms and forms progressive backward failure.(2)We have found out the control mechanism of weak intercalation in bedding rock slope to the formation of landslide.Combined with the slope structure and deformation characteristics,we conclude that the rock mass in the sliding source area of the landslide is an unstable slope formed after the first sliding in 2014.The weak interlayer is affected by long-term gravity and groundwater,resulting in compression and extrusion deformation towards the free direction,which leads to the cracking of overlying thick dolomite,thus forming the trailing edge controlled sliding structural plane.Along the interface between soft and hard rock,the sliding body produces shear slip deformation,which eventually evolves into landslide geological disaster.Finally,we use the discrete element numerical simulation software to verify the process of compression and shear deformation instability of landslide.(3)Based on the physical model test,we obtained that the damage evolution mechanism of bedding rock landslide.According to the analysis of landslide mechanism and model test results,we conclude that the formation of bedding rock landslide is the result of long-term creep leading to rock mass damage and continuous accumulation.From the microscopic point,the stress intensity factor at the crack tip of rock body exceeds the fracture toughness,leading to the generation and development of cracks,forming the initial damage of rock mass.After the continuous development and penetration of cracks,large cracks are formed,and the damage of rock mass is intensified ? According to the change rule of each parameter in the process of Landslide Evolution,the damage and failure process of bedding rock landslide is divided into four stages: initial damage,crack development,crack penetration and nearly sliding to failure.(4)We clarified that the corresponding relationship between AE signals generated in the process of deformation evolution of bedding rock landslide and its deformation evolution stage.When there are micro cracks in the slope,the acoustic emission signal is weak.When there are large cracks in the landslide,the acoustic emission signal is strong.The accumulated characteristic parameters of acoustic emission have obvious inflection point characteristics,which can be used as the basis for the division of the damage and deformation stages of the landslide.(5)We set up an early-warning model based on the damage process of rock mass,and put forward a comprehensive early-warning criterion based on the cumulative energy curve of acoustic emission and the damage degree of rock mass,which improves the reliability of landslide early-warning.Compared with the early-warning model based on deformation process,the early-warning model proposed in this paper is more advanced in each early-warning level,and the duration of each stage is longer,which can strive for more emergency response time,and the technical method is also effective and feasible.
Keywords/Search Tags:Bedding rock landslide, Weak intercalation, Genetic mechanism, physical simulation, acoustic emission, Early warning model
PDF Full Text Request
Related items