مقاله انگلیسی رایگان در مورد پیش بینی انفجار سنگ و تحلیل پایداری تونل دسترسی – الزویر 2020

1- Introduction

2- Project overview

3- Establishment of microseismic monitoring system

4- Analysis of microseismic activity characteristics

5- Conclusions

References

Abstract

The access tunnel in the main powerhouse of the Shuangjiangkou hydropower station in China has complex geological conditions and is subject to high in situ stress in deep buried sections. Microseismic activity in the surrounding rock mass of the tunnel was monitored by a microseismic monitoring system, and rockburst was effectively predicted. Based on abundant data obtained from the microseismic monitoring, statistical parameters, which include cumulative apparent volume, the energy index, cumulative released energy and the Es/Ep value, were used to analyze the microseismic activity before and after rockburst to determine a more accurate early warning period and construction safety period. A sharp decrease in the energy index and a rapid increase in the cumulative apparent volume indicated a deterioration of the surrounding rock mass stability. The change characteristics of Es/Ep values revealed that the rockburst process underwent a transformation of compression-shear damage, tension-shear mixed damage and tension damage. Finally, based on the number of daily events N and the b value of the microseismic events, lgN/b was first established to evaluate the rockburst risk of tunnels. When the value of lgN/b was greater than 1, rockburst was more likely to occur; the larger the lgN/b value, the more severe the rockburst was. The research results provide an important reference value for the prediction of rockbursts in deep tunnels and the regulation of site construction progress.

Introduction

Rockburst is a special failure pattern that occurs during excavation in a high-stress environment, accompanied by the sudden release of strain energy, and it can pose a considerable threat to on-site workers and engineering equipment. Therefore, research on rockburst mechanisms and predictions has become a key scientific and technical pursuit in rock mechanics to reduce and control rockbursts.1 Detailed analysis of the occurrence process of rockburst and revealing rockburst mechanisms are the keys to accurately predicting rockbursts. Extensive theoretical and experimental studies have been conducted on failure mechanisms, forecasting methods, and prevention technologies. Ortlepp and Stacey2 distinguished several different rockburst mechanisms in tunnels and shafts, drew a distinction between source and damage mechanisms, and suggested five rockburst types in tunnels and shafts, namely, strain burst, buckling, face crush burst, shear rupture, and fault slip burst. Their research results form a good foundation for further analysis of rockburst mechanisms and rockburst prediction in underground engineering in the future. Based on research findings from other researchers, Kaiser et al.3 proposed three rockburst types (strain burst, pillar burst, and fault slip burst). Frid4 established the electromagnetic radiation criterion for rockburst prediction in coal mines. The antenna that captured signals was normally located 1 m from the mine working face. Therefore, this method of predicting rockbursts cannot be applied to general tunnel excavation. Romashov5 first proposed a generalized model of rockbursts that was in accordance with the general character of deformations in rock masses and physical representations of many phenomena. Their research results form a good foundation for creating a rockburst model of specific rock masses and developing new more reliable methods of estimating their rockburst hazard. Liu et al.6 used cloud models and the attribution weight method to predict rockburst classifications. The data collection is an enormous challenge for their applicability. Gong and Li7 established a distance discriminant analysis method for rockburst prediction. In the research, the parameters used to build the model are difficult to be obtained on site, so it is an enormous challenge for applications in the tunnel with complex geological environments.