Microseismic Monitoring and Numerical Simulation of Rock Slope Failure

A numerical code with an elastic-brittle failure model has been developed to simulate the seismic activities in rock failure problems. The feasibility in principle of monitoring and prediction of rock failure was numerically simulated. The heterogeneity was considered to be the main reason for the existence of slope failure precursors. Seismic events could be observed in heterogeneous rock, whereas the homogeneous rocks showed an abrupt fracture mode without any early seismic precursors. The failure process of a slope was numerically investigated by using a gravity increase method (centrifugal loading method), and the application of the microseismic monitoring system in the slope was introduced. The numerical results showed that the fracture of the main faults caused the slope slide, and the microcracking caused by the heterogeneity in the faults prior to the landslide could be considered as the precursors of the slope failure, which were captured by the microseismic monitoring system. The microseismic monitoring technique was proved to be successful in predicting the failure in the slope, and the numerical results will be helpful in interpreting the microseismic monitoring results.

[1]  Hong-Nan Li,et al.  Multisensors On-Site Monitoring and Characteristic Analysis of UHV Transmission Tower , 2012, Int. J. Distributed Sens. Networks.

[2]  Ting-Hua Yi,et al.  Recent research and applications of GPS‐based monitoring technology for high‐rise structures , 2013 .

[3]  Joris C. Verster,et al.  Caffeinated drinks, alcohol consumption and hangover severity , 2011 .

[4]  Ting-Hua Yi,et al.  Optimal sensor placement for structural health monitoring based on multiple optimization strategies , 2011 .

[5]  Tao Xu,et al.  Numerical simulation of 3-d failure process in heterogeneous rocks , 2004 .

[6]  Monica Papini,et al.  Towards rockfall forecasting through observing deformations and listening to microseismic emissions , 2009 .

[7]  Huilin Xing,et al.  A three-dimensional numerical investigation of the fracture of rock specimens containing a pre-existing surface flaw , 2012 .

[8]  A. Jones.  10 – Rock Mechanics and Rock Engineering , 1989 .

[9]  Neil Dixon,et al.  Quantification of slope displacement rates using acoustic emission monitoring , 2007 .

[10]  Ming Cai,et al.  Assessment of excavation damaged zone using a micromechanics model , 2005 .

[11]  P. K. Kaiser,et al.  Quantification of rock mass damage in underground excavations from microseismic event monitoring , 2001 .

[12]  Nuwen Xu,et al.  Optimal Design of Micro-Seismic Monitoring Array and Seismic Source Location Estimation for Rock Slope , 2011 .

[13]  Gloria Senfaute,et al.  Mining-induced seismicity: Seismic measurement using multiplet approach and numerical modeling , 2006 .

[14]  Peng Lin,et al.  A Flexible Network Structure for Temperature Monitoring of a Super High Arch Dam , 2012, Int. J. Distributed Sens. Networks.

[15]  Jimin Wang,et al.  Preliminary engineering application of microseismic monitoring technique to rockburst prediction in tunneling of Jinping II project , 2010 .

[16]  Chun An Tang,et al.  Microseismic monitoring and stability analysis of the left bank slope in Jinping first stage hydropower station in southwestern China , 2011 .

[17]  A. Hirata,et al.  Safety Management Based on Detection of Possible Rock Bursts by AE Monitoring during Tunnel Excavation , 2007 .