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In order to analyze the stability of the bridge above the goaf, the disturbance influence of goaf residual deformation on the bridge is studied. Firstly, an equivalent numerical simulation method of goaf residual deformation evolution process is studied by quantitative analysis the sensitivity of residual subsidence to the rock parameters using the OAT (one-variable-at-a-time). Then, the collaborative deformation of ground, pile, and bridge floor is studied under the condition of a simply-supported beam bridge above the goaf center. Finally, the mechanism of collaborative deformation of ground, pile, and bridge floor is revealed. The results show that the goaf residual deformation process can be obtained by weakening the elastic modulus of fractured rock in the caving zone. At the final residual deformation stage, the subsidence ratio of ground to pile is about 10, and the subsidence ratio of pile to bridge floor is about 2, while the ground horizontal movement ratio of ground to pile is about 7, and the bridge floor horizontal movement can be ignored. The bridge floor is always in the positive curvature influence zone, and the pile has an inhibitory effect on the curvature deformation of the bridge floor. The compression deformation occurs between the piles locations, while the tensile deformation occurs at the pile location. The evolution of negative frictional resistance derived from goaf residual deformation is the main reason for the change in the collaborative deformation law among the ground, pile and bridge floor. This research can provide scientific support and theoretical basis for the design, construction, and protection of the bridge above the goaf center, and can also provide reference for the stability evaluation of bridge above goaf under other conditions. [ABSTRACT FROM AUTHOR]

Coal mining under slopes often leads to slope instability, resulting in substantial economic losses and human casualties. Therefore, constructing a scientific and practical slope stability evaluation model for slope disaster prevention and control is of great significance. In this study, seven evaluation indexes were selected, and their influence mechanisms were analyzed to establish a system of evaluation indexes for the stability of mining slopes in Xing County, Shanxi Province, China. A new evaluation model for the stability of mining slopes was established based on the interval analytic hierarchy process (IAHP) to determine the subjective weights of the indexes and the improved CRITIC method to determine the objective weights of the indexes, which circumvented the limitations of subjective or objective weights by combining the minimum discriminating information. The model was applied to the mining slopes in Xing County, Shanxi Province, and the results showed that slopes A, C, D and E were in an unstable state, slope B was in an understable state after mining. Finally, the accuracy of the evaluation results was verified through field surveys. The model has engineering application value in predicting the stability of mining slopes and can provide theoretical suggestions for later slope management to ensure the safe production of coal mines. [ABSTRACT FROM AUTHOR]

After underground coal resources are mined out in mining areas, large-gradient deformation is prone to occur on the ground surface during a short period of time. When the deformation gradient exceeds the threshold value of the gradient monitored by the D-InSAR (Differential Interferometry Synthetic Aperture Radar) technology, the conventional D-InSAR technology is likely to cause the failure of InSAR (Interferometry Synthetic Aperture Radar) phase unwrapping algorithms. In this case, neither the conventional D-InSAR technology nor the method of prior model + InSAR can obtain the 3D (three-dimensional) deformation field of mining-induced subsidence. Aiming at these problems, a method of monitoring 3D deformation of mining subsidence with large gradient was developed in this paper, which combines the improved dynamic prediction model and a single pair of D-InSAR. The probability integral method was firstly improved, and its problem of fast convergence at the edge of the subsidence basin was solved. Secondly, according to the geometric projection relationship between the LOS (Light Of Sight) deformation of D-InSAR in the mining area and the 3D surface deformation, the observation condition equation of the mining subsidence monitored by D-InSAR based on the improved dynamic model of PIM (Probability Integral Method) was established. Then, the solving model of prediction parameters of the improved dynamic model of PIM was constructed according to the GA (Genetic Algorithm) theory. Finally, based on the LOS deformation obtained by D-InSAR technology, the 3D deformation of mining subsidence is obtained by the 3D deformation predicting method proposed in this paper. The feasibility of the method was verified by the simulation experiment results. The LOS deformation at the edge of the subsidence basin was obtained by the differential interference processing of data from two images of Sentinel-1A on 16 November 2017 and 10 December 2017 of 1613 working face of Guqiao South Mine. The 3D deformation of the surface in the mining area during this period were obtained by using the method proposed in this paper. The predicted subsidence value was compared with the measured surface subsidence value. The result is as follow: the maximum error value of subsidence was 60 mm, about 9.1% of the maximum value of subsidence, and the fitting error of mean square of subsidence was ± 26.21 mm. The results show that the predicting 3D deformation method of D-InSAR for large gradient of mining subsidence based on constraints of improved dynamic prediction model proposed in this paper has certain engineering application values. [ABSTRACT FROM AUTHOR]

In resource-exhausted cities, the development and reuse of land resources above abandoned goafs will invigorate economy and form new regional economic development centers. However, the infrastructures to be built will be affected by the land above an abandoned goaf subjected to long-term residual subsidence. Under such background, accurate prediction of residual subsidence can provide quantitative criteria for land resources development. In this paper, a surface residual subsidence prediction model (SRSPM) was developed. The research results showed that the residual subsidence was caused by compaction of voids including gaps among fractured rocks, the boundary at coal wall and the overburden-separation between soft stratum and hard stratum, respectively. By analyzing the spatial distribution and shape characteristics of these voids, the SRSPM was developed using the theory of probability integral method. Its reliability was verified by comparing with an existed prediction model in a numerical simulated experiment. The SRSPM can provide scientific decision support for the choice of the suitable development model of the land resource above the abandoned goaf. [ABSTRACT FROM AUTHOR]