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Rockburst is one of the mine dynamic hazards. 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). It was very important to establish a multi-means to monitor and predict model for rockburst. This chapter was introduced the current research status on 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 indicated that it was very important to analyze the characteristics, influencing factors, formation mechanism; emissive events induced condition, rockburst key predicting point and predicting model. The author's work in investigation of key points of synergetic predicting of rockbursts and their predicting models based on the nondeterministic theory was also introduced. In this book, we did some studys on dynamic hazard evolution, predicting model using traditional monitoring, AE monitoring, microseismic monitoring and infrared monitoring.

Experimental materials and equipments were introduced in laboratory and field tests. Experimental materials, which were coal, Sulfide ores, Oxidized and limestone, etc, were got from Da’anshan coal mine, Xiezhuang coal mine, Huize Lead-zinc mine. The laboratory equipments were used in laboratory, such as servo stiffness compressor, AE monitoring system, infrared thermal imager, CT test scanning equipment were introduced respectively, as well as the MS monitoring system in the field equipment. Scanning electron microscopy (SEM) and energy dispersive Spectrometer (EDS) were used to obtain a variety of physical information about the samples, and analyze their component elements, species and contents. These experimental materials and equipments provided the basic condition for obtaining data of predicting rockburst.

Mechanism and predicting of rockburst is complicated, and there is no mechanism and prediction model to explain the occurrence of rockburst satisfactorily. In this chapter, the mechanism of rockburst stress-energy evolution is obtained by analyzing the pre-peak stage of rock compressive deformation. Rockburst is mainly caused by the accumulation of stress and the accumulation and release of elastic strain. The change of stress for rockburst occurred plays a leading role, It not only leads to the accumulation and release of elastic strain energy, but also the damage cracking unit of rock structure. Thereby, reducing the energy storage capacity of rock elastic strain energy. In addition, the elastic strain energy released by rockburst is the result of accumulation and dissipation of elastic strain energy. Based on the analyse, the stress-energy evolution of rockburst was proposed. The nonlinear dynamic theories of predicting rockburst were introduced, such as mutation, damage, load/unload response ratio, entropy, fuzzy matter element and Bayesian theory. New predicting models and methods were established based on these theories.

The problem of sudden destruction of rockmass is closely related to the existence and evolution of fissures. The development and evolution of rock fissures under loading pass three stages: the stage of secondary crack initiation, the stage of formation of macro-fracture zone and the stage of localized deformation. In this chapter, using a CT scan of the specimen under uniaxial cyclic loading/unloading, the CT images were calculated and processed in MATLAB to get the lengths and areas of cracks before reconstructed its three-dimensional fracture model. The microscopic characteristics of sandstone was reproduced by the reconstructed numerical model, and the model was simulated by FLAC software under uniaxial cyclic load/unload. In order to further reveal the damage mechanism of rockmass instability, predicting rockburst during the process of damage evolution and rockmass instability was organically combinated.

The evolution patterns of cracks propagation still stays in the whole process of cracks initiation-extension-failure of microscopic level, and does not explain the macroscopic failure pattern of rock through the process of cracks propagation. A three-dimensional visualization model of cracks was established, which provided a new way to study the transition from microscopic scale to macroscopic scale. Verifying the relationship between the areas and lengths of cracks and stress, based on CT scanning results of sandstone, CT images was analyzed using the MATLAB software and the evolution pattern of mesoscopic cracks were explored under uniaxial cyclic load/unload. Crack growth factor model was proposed to quantitatively describe the propagation and evolution of cracks in the process of sandstone fracture, which provided a theoretical basis for studying the effect of meso-structure change on the macroscopic damage of sandstone,and extended to all hard rock. It revealed the nonlinear dynamic evolution patterns of cracks propagation in the process of sandstone failure using CT parameters. This model provided a new method for predicitng rock dynamic hazard. Compared with the actual test results using the three-dimensional reconstruction and numerical simulation of roof and bottom sandstone’s mesostructure of initial stage, the correctness of numerical simulation was verified.

This chapter investigated the AE precursor information of rockburst. Firstly, the characteristics of rock cracks initiating, propagating and linking was analyzed with the spatial-temporal distribution characteristics of AE, AE evolution pattern and the precursor feature of limestone failure were found. Secondly, the characteristic point of the relatively quiet period was defined as a characteristic precursor point of rock failure. The corresponding time was suggested. When AE energy release rate reached at the maximum, as the critical point for predicting rock failure. Thirdly, the ideal precursor parameters to predict rock failure were suggested after studying the variation regulation of AE energy parameters for rock failure. The spatial-temporal-energy evolution model of AE events on the fracture surface was established during rock failure, as well as the characteristics of fracture surface and the energy evolution.

Based on the daily precursor monitoring techniques, such as infrared and AE / MS monitoring, methods of IRR, LURR, TDF, information entropy, TM, parameter , MS event were used to analyze the precursory information for the predicting key point respectively. The results showed that all of the mentioned methods and information have high potential to be used for seeking a predicting key point. Therefore, a model of multi-means and synergistic prediction for rockburst was designed based on these above methods for making up for and verify each other, making it more reasonable, scientific and effective.

Predicting is the basis of prevention and controlling of rockburst hazards. Duo to the characteristic of sudden, disruptive, and complex, the accurate prediction of rockbursts is difficult and an urgent problem need to be solved. Rockburst tendency is an important metric to quantify the risk and potential intensity of occurrences and grade the hazard of an affected mine. However, there are still no accurate prediction methods or effective control measures. By considering multiple factors, the new model can overcome the limitations of single-factor methods. These attempts have not yet formed a complete theoretical system. Based on the Bayesian theory and Fuzzy element-matter theory, two multi-index evaluation models were proposed the predicting model for rockburst tendency.

Many predicting models and methods of rockburst were established, such as crack growth factor model,tangent damage factor identification, tangent modulus identification, information entropy and value, load/unload response ratio, infrared radiation, cumulative apparent volume and MS rate, spatial-temporal-energy evolution model of rock failure, Bayesian model, Fuzzy matter-element model, etc. These field cases verified that these proposed models, methods and theories were highly accurate and meaning for the predicting rockburst.