Cao S.,University of Science and Technology Beijing |
Cao S.,State Key Laboratory of High Efficient Mining and Safety of Metal Mines of Ministry of Education |
Song W.,University of Science and Technology Beijing |
Song W.,State Key Laboratory of High Efficient Mining and Safety of Metal Mines of Ministry of Education |
And 3 more authors.
International Journal of Mining Science and Technology | Year: 2016
Combined with a digital bored photography system and in-situ statistics concerning the joints and fissures of both ore-body and surrounding rock, a 2D discrete model was constructed using UDEC. The stress field and displacement field changes of different sublevel stoping systems were also studied. Changes in the overlying rock strata settlement pattern has been analyzed and validated by in-situ monitoring data. The results show that: in the caving process, there exists an obvious delay and jump for the overlying rock strata displacement over time, and a stable arch can be formed in the process of caving, which leads to hidden goafs. Disturbed by the mining activity, a stress increase occurred in both the hanging wall and the foot wall, demonstrating a hump-shaped distribution pattern. From the comparison between simulation results and in-situ monitoring results, land subsidence shows a slow-development, sudden-failure, slow-development cycle pattern, which leads eventually to a stable state. This pattern validates the existence of balanced arch and hidden goafs. © 2016 Published by Elsevier B.V. on behalf of China University of Mining & Technology.
Du F.,University of Science and Technology Beijing |
Du F.,State Key Laboratory of High Efficient Mining and Safety of Metal Mines of Ministry of Education |
Hu N.,University of Science and Technology Beijing |
Hu N.,State Key Laboratory of High Efficient Mining and Safety of Metal Mines of Ministry of Education |
And 4 more authors.
Mathematical Problems in Engineering | Year: 2014
The traditional mine microseism locating methods are mainly based on the assumption that the wave velocity is uniform through the space, which leads to some errors for the assumption goes against the laws of nature. In this paper, the wave velocity is regarded as a random variable, and the probability distribution information of the wave velocity is fused into the traditional locating method. This paper puts forwards the microseism source location method for the undersea mining on condition of the probability distribution of the wave velocity and comes up with the solving process of Monte Carlo. In addition, based on the simulated results of the Monte Carlo method, the space is divided into three areas: the most possible area (area I), the possible area (area II), and the small probability area (area III). Attached to corresponding mathematical formulations, spherical models and cylindrical models in different areas are, respectively, built according to whether the source is in the sensor arrays. Both the examples and the actual applications show that (1) the method of microseism source location in this paper can highly improve the accuracy of the microseism monitoring, especially for the source beyond the sensor arrays, and (2) the space-dividing method based on occurrence possibilities of the source can recognize and sweep the hidden dangers for it predicts the probable location range of the source efficiently, while the traditional method cannot. © 2014 Furui Du et al.