1. Introduction

Mine dynamic hazards mainly include the rockburst, high-speed landslide, coal and gas outburst, underground debris flow, gob area catastrophic collapse, tailings dam collapse, and water inrush, etc. Rockburst is usually referred to as dynamic catastrophe, which results in causalities and roadway destruction, caused by elastic strain energy emitting in a sudden, rapid and violent way from coal or rockmass. It is often accompanied by an airblast and violent failures which can disrupt mine ventilation, pose a danger to miners, and may also cause a large release of strata gas and explosive dust into the air (Brauner 1994; Dou et al. 2012; Jiang et al. 2014; Cook 1976; Salamon 1983; Ortlepp 1994).

With the depletion of shallow mineral resources, there is an inevitable trend for mineral extraction to go deeper. Duo to the mining depth and the mined out area increases, the frequency and intensity of induced explosion will be increased simultaneously. Mining face and deep tunnels near the rockburst area will endanger the production safety. Strong rockbursts also cause engineering loss, damage people’s living environment and pose a threat to public safety. Therefore, it is of great significance to carry out the research and management of rockburst in deep mining and tunnel engineering (He et al. 2005; Zhou et al. 2005).

Rockburst is one of the most important mine dynamic hazards in China. According to the State Administration of Work Safety of China, the total casualty in mine accidents was 54,744 from 2002 to 2016, especially the accidents caused by the rockburst, water inrush, coal gas outburst and other dynamic hazards account for more than 60%. In 2016, there were 538 deaths in coal mines in China, compared with 9 in the United States. The death totally in China is 59.78 times than that of the United States, and about 80–90% of world’s major mining hazards (more than 10 people) occur in China every year.

The study of type and induced condition of rockburst is the precondition for the prevention of rockburst. It was stated that any rockburst results from a mining tremor but not all the tremors cause rockburst. In fact, two kinds of hazards (seismic hazard and rockburst hazard) were proposed and defined, which one tremor cannot be predicted (Kornowski et al. 2012). The tremors in corresponding to the rupture events were observed at scales ranging from laboratory samples to the earth’s crust, which included rock failures in laboratory tests and field experiments, landslides, mining-induced seismicity, and crustal earthquakes (Amitrano 2012). It was verified that rocks under stress emit acoustic waves in the laboratory and microseismic events in mines. Then, AEs of rocks observed in the laboratory were considered as a small-scale model of seismicity of earth’s crust (Filimonov et al. 2005; Hardy 2003; Scholz 1968).

In the past few years, although the mining industry has carried out a large number of mine rockburst induced conditions and control technology research, the mine safety production situation is still grim. If the mine rockburst induced conditions, monitoring and predicting model can not be solved in short term, it will become a bottleneck restricting for the development of mining (especially deep mining).

In order to solve the key technical problems related to rockbursts, it is necessary to analyze their inducing conditions. Studies have already been done to determine these inducing conditions and to lay foundations for rockburst prediction. However, these studies are incomplete. To date, there is still no unified explanation for the rock dynamic hazards, especially the triggered conditions of rockbursts. So, it is very important to study the rockburst induced conditions and analyze the rock failure behavior by various theories, which can provide reasonable suggestions for mining design, mining method and rockburst prevention measures. It also is very important meaning to mining safety and efficient recovery.

Rockburst is a nonlinear dynamic process, in which the energy is converted into kinetic energy by the broken rockmass and ejected. Thus, from the energy point of view, rockburst is an essentially process, in which the elastic strain energy accumulated in the rockmass is released abruptly. Hence, the main factors that affect the occurrence of a rockburst are the impact which can make rock into a high-energy storage. High-energy storage of rock is more likely to cause rockburst. In other words, rock has sufficient capacity to store large elastic strain energy and there is a high concentration of stress within the rock. Based on this, rockburst was induced by both a high concentration of stress and a large quantity of recoverable strain energy (Qian 2004).

At present, relatively few studies focus on the conditions of rockburst and each of them has different emphases. In this area of study work is as follows:

It was established an analytical model for the nonlinear instability mechanism of coal and rockmass which based on non-equilibrium thermos dynamics and dissipative structure theory, the three-dimensional model of coal and rockmass instability, coal and rock damage model by considering the dynamic instability model according to the Hoek-Brown strength theory (Jiang et al. 2005). It was found that the migration of microseismic events was mainly caused by stress redistribution, which was related to the collapse of the main caves, while the secondary microseismic clusters were related to the small-scale damage (Trifu et al. 2008). It was found that main non-uniformity stress would appear after injecting large-volume fluid into the granite body and along the fault surface shear stress would be released. The occurrence of microseismic events and fault surface shape indicating the fault sliding was quasi-static (Scotti et al. 1994). It was also found that a microseismic event with a magnitude of less than 0 can be used to assess a 2.9 level destructive rockburst event. The stress inversion and the main quantification component analysis were of good correlation. What’s more, it could be used to derive microseismic failure surfaces and structural maps (Ttifu et al. 1996). It was found that AE can be used to monitor the material destruction process and quantify the waveform analysis of microseismic event magnitude (Arastehl et al. 1997). AE event was occured in the direction of rupture tip during loading. At the same time, the macro-rupture was occurred at the unloading event. A typical loading event was an essentially component in the tensile stress zone, while the unloading usually was a shear stress.

From a research perspective, the deep mining rockburst were mainly concentrated on the induced conditions. The research work so far mainly analyzed the lab experiment under the uniaxial condition and deduced the model which mainly included the time-consuming, energy storage and energy consumption, the distribution of precursor information before rock failure. However, multiple factors of rockmass, which leaded to rockburst in the deep mining, were in complex stress environment conditions. Actually, lab experiment is only a special case of scene and it has a certain difference compared the actual rockburst, experimental investigation is a similar understanding for the real situation of rockburst hazard. At present, rock mechanics is still not enough explaining to the induced factors of rockburst, the monitoring criterion and the predicting model. Especially, the excavation leads to the stress redistribution and the fault activity induced by the microseismic event is still insufficient. It is necessary to do some further study in the lab experiments and practical production applications. Therefore, it is very important to analyze the characteristics, influencing factors, formation mechanism; emissive events induced condition, rockburst key predicting point and predicting model.

The macroscopic fracture and failure of rockmass are due to the nucleation, expansion and penetration of microfracture. The secondary stress redistribution of rockmass by excavation is affected by the stress field disturbance and resulting in dislocation, disintegration and migration of mesome. With the development of rock mechanics, it has become an important method of dynamic hazards monitoring that includes the monitoring of stress wave and the maturation of AE positioning technology, microseismic monitoring technology and AE technology. By analyzing the strength, the frequency and the location of microseismic activity, we can get access to some hazards precursor information to achieve risk assessment and predicting. However, the implementation of rock test on the site is more difficult and can’t easily get the results. At the same time, lab experiment is an effective way to study the destruction and regularity of rockmass. So, it is an effective means to conduct AE test and combine with the field monitoring results. Therefore, it is the primary task to carry out the research on the prediction of dynamic hazards by summing up the characteristics and evolution patterns of AE in the process of rock rupture.

To date, less methods aim at studying the distribution of precursory information of rockburst and they have different emphases. The main work in this area as follows:

In a uniaxial loading test, it is known that the number of AE events is small during the initial loading stage. In the later stage of rock elastic and plastic deformation, the number of cumulative AE events increased rapidly before the damage and maintain a low release rate during the rock fracture process (Liu et al. 2011). From the experimental data, it was found that the precursory characteristics of rock samples were inferred and the heterogeneous fault was caused by the failure of specimens (Lei et al. 2004). It was found that the fault, stress and boundary deformation had a close interaction for the shear strain generation area evolved (Mekinnon 2006). It was also found the presence of AE relatively quiet period by rock uniaxial compression AE test (Schiavi et al. 2011). It was found that the AE energy of material was accelerated after destruction through the AE monitoring tests on concrete, rock and other materials under uniaxial loading conditions (Carpinteri et al. 2008).

This book focus on the rockburst induced conditions and predicting, three-dimensional reconstruction model of rock fracture cracks under loading, dynamic evolution of rock fractures, experimental investigation of rockburst precursor information. The author’s work in investigation of key points of synergetic predicting of rockbursts and their predicting models based on the nondeterministic theory is also introduced.

Rockburst is a sudden, unexpected and abrupt failure. It is a bottle neck for any geotechnical engineering being carried out at great depth. The study of rock failure process and evolution patterns has become the important issues in underground engineering. In the past, it was difficult to observe the true geometric distribution within the materials due to the limitations of test technique and equipment. With the rapid development of science and technology, Computed Tomography (CT) scanning technology has gradually become the most advanced non-destructive testing means. The application of CT scanning technology can achieve the continuous scan, dynamic observation test under load in the geotechnical engineering. In the same time, we also can get the parameters change in the process of computed tomography, the internal structure of sample, the microscopic structure of sample, the moving microscopic particulate matter, the developmental crack, the local change density, etc. CT image is a kind of grayscale image which can reflect the change of density inside the rockmass. Through the change of gray degree, the distribution of material in different areas of rockmass can be reflected in the image. What’s more, the process of structural failure can be well reflected by CT images.

In fact, many researchers analyzed CT images and three-dimensional cracks reconstruction (Kawakata et al. 1999, 2000), and it was come true that to simulate the outdoor rockmass distribution by X-ray rock CT scanning (Ueta et al. 2000). Chinese scholars focus on the analysis of changes of CT number in the CT image and the quantitative analysis was only in theory. The advantages of digital image processing technology did not totally display in the field of geotechnical engineering. It is necessary to use numerical simulation to describe the geotechnical material and reflect the real force of rockmass. Therefore, the CT image of rock, based on the digital image technology, provides a new way to analyze the process of meso-cracks reconstruction.

The process of rock failure is a significant accumulation of process, which is determined by the brittle characteristics of rock. In the process of cyclic load/unload, the higher concentrated stress will appear at the tip of rock crack, which will lead to the initiation and expansion of cracks inside the rock and gradually generate new macroscopic cracks leading to the overall destruction of specimen. With the continuous development of society and the process of human production, engineering construction is gradually increased in the influence of fractured rockmass.

Most scholars studied the cracks evolution by similar model test which could be observed intuitively and clearly about the process of cracks initiation, expansion and penetration failure. It was conducted the prefabricated oblique fissures of marble compression test which showed the process of expansion and it was asymmetric (Nolen-Hoeksema et al. 1987). What’s more, rock failure and the surface of crack distribution were observed in the test. As the existing technical level, internal cracks in the rock sample were achieved, but rock similar materials were used to study the crack propagation and transparent characteristics. All of these results in accurate observation and record was not achieved. In this book, CT scanning technology and digital image technology were used to obtain these cracks images of rock under different load levels. The nonlinear dynamics of cracks propagation process was revealed.

The study of propagation evolution patterns still rests in the whole process of crack initiation-extension-failure of microscopic level so far, and it does not explain the macroscopic failure criterion of rock in the process of crack propagation. This book intends to establish a three-dimensional visualization model of cracks which can provide a new way to study the transition from microscopic scale to macroscopic scale.