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Bayueshan tunnel (BYS) is an important construction crossing over coal mine goaf. The underground mining subsidence has led the tunnel cracked seriously in three years after it was built. In order to evaluate the coal mine influence and future stability of the tunnels, probability integral method (PIM) was used to calculate the tunnel deformation. PIM is an experience function method based on random medium theory which is used widely in China. With the parameters analyzed, the tunnels’ subsidence was calculated. The results show that it can interpret the tunnel damage well, and the maximum normal strain positions fit the damaged tunnel positions well. It proved that PIM can be used to evaluate the tunnel’s radial deformation caused by underground coal excavation. In order to maintain tunnels to keep a long-term stability, the future deformation was calculated in case the coal excavation continues. It shows that the tunnel would be cracked again if the excavation continued. Other reasons such as the old goaf deformation and water and vehicle dynamic load are also important reasons for the tunnels’ deformation. In order to keep traffic safety, it needs to reinforce the cracked foundation under the tunnel. Then, grouting injection was proposed to reduce the old goaf deformation under the tunnels. If the fracture zone under the tunnels disturbed by the dynamic traffic load, the old goaf will face a risk of sudden collapse. So, to ensure the grouting effect, the grouting depth should be deeper than the sum of traffic load influence depth and height of coal mine caved fissure zone. The grouting scope should keep all the crack rock area under the tunnel from being disturbed by the dynamic traffic load. This design can reduce the sudden collapse risk of the goaf and reduces the vehicles’ load disturbance on the cracked rock. The researched technology provides an engineering guidance to tunnel subsidence calculation, stability evaluation, and maintenance in complex geological and engineering situations.

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Line of Sight (LOS ) deformation based on Differential Interferometric Synthetic Aperture Radar (DInSAR) techniques cannot be used in traditional probability integration method (PIM) parameter inversion. To improve the accuracy of parameter inversion, a model based on 3D deformation was proposed. The model simulates 3D deformation using PIM directly. The inverse of the Sum of the Squared Errors (SSE) of the PIM results and the measured deformation results was used as a fitting function within the GA. Reliable PIM parameters can be obtained based on this GA model. To identify the surface movement law of the Jinfeng coal mine, 6 Global Navigation Satellite System ( GNSS ) monitor points were established over the 011207 and 011809 working panels. Due to the limited number of points and the large distance between the points, it is not sufficient to obtain reliable PIM parameters using GNSS only. As a complement, 83 Sentinel-1A images were analyzed with small baseline subset (SBAS) DInSAR, and the LOS direction deformation was obtained. The reliable PIM parameters were calculated with the 3D inversion model based on the combination of LOS direction deformation and GNSS-monitored deformation. Then, those parameters were used to predict the coal mine deformation of panels 011207 and 011809, which demonstrated that the prediction results coincide with the measured results. The model can be used to study the laws of mining subsidence combined with DInSAR and GNSS, which can reduce the requirements of the number of GNSS points and the impact of radar decoherence. This provides a new technical approach for studying the law of surface movement in mining subsidence research.

The Bayueshan (BYS) tunnels are adjacent tunnels which comprise key engineering structures important for Yurong highway from Chongqing to Sichuan, China. The tunnels were established crossing over the old goafs of a coal mine. The tunnels have been damaged three times between 2014 and 2016. To evaluate the reasons for the damage, fast Lagrangian analysis of continua in three dimensions ( FLAC 3 D ) was used to simulate the underground coal-mine excavation yearly from 2012 to 2015. The simulation results show that the subsidence of the ground surface increased annually. The maximum subsidence of the left tunnel was 505 mm and that of the right tunnel was 512 mm. The excavation led to increase in the tunnels’ stress concentration. The simulations further show that uneven horizontal displacement and subsidence were the major factors in inducing tunnel construction defects. Poor geological conditions, water, and vehicle dynamic loads were also important factors that induced damage. Several engineering suggestions for ways to maintain the tunnels are given in this paper, and the research provides a reference for safety evaluation for tunnels crossing over an old goaf.

The subway alleviates the traffic pressure in the city but also brings the potential risk of land subsidence. The land subsidence caused by the subway is a global problem that seriously affects the safety of subway operations and surrounding buildings. Therefore, it is very important to carry out long-term deformation monitoring on the subway system. StaMPS-PS is a time-series Interferometric Synthetic Aperture Radar (InSAR) technique that serves as an effective means for monitoring urban ground subsidence. However, the accuracy of external (Digital Elevation Models) DEM will affect the accuracy of StaMPS-PS monitoring, and previous studies have mostly used SRTM-1 arc DEM (30 m) as the external DEM. In this study, to obtain a more precise measurement of surface deformation caused by the excavation of the Hohhot subway, a total of 85 scenes of Sentinel-1A data from July 2015 to October 2021, as well as two different resolution digital elevation models (DEMs) (ALOS PALSAR DEM and SRTM-1 arc DEM), were used to calculate and analyze the subsidence along the subway line in Hohhot city. The StaMPS-PS monitoring results showed the ALOS PALSAR DEM, as an external DEM, had higher accuracy, and there was regional subsidence in both the construction processes of Line 1 and Line 2 of the Hohhot subway, with a maximum subsidence rate of −21.1 mm/year. The dynamic changes in subway subsidence were fitted using the Peck formula and the long short-term memory (LSTM) model. The Peck formula results showed the width and maximum subsidence of the settlement troughs gradually expanded during the construction of the subway. The predicted values of the Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) of the LSTM model were less than 4 mm and 10%, respectively, consistent with the measured results. Furthermore, we discussed the factors that affect settlement along the subway line and the impact of two external DEMs on StaMPS-PS. The study results provide a scientific method for DEM selection and subsidence analysis calculations in the StaMPS-PS monitoring of urban subway subsidence.

Monitoring ground displacement produced by underground mining is essential to ensure the safety of infrastructure over mining areas. Differential synthetic aperture radar (DInSAR) can only obtain the 1-D [i.e., along the line-of-sight (LOS) direction] displacement component. In this study, we present an improved algorithm for retrieving and predicting 3-D displacement fields induced by underground mining based on the LOS displacement derived from DInSAR and the probability integral method (PIM). Whole parameters included in the standard PIM model are involved in the improved algorithm. In addition, the interaction between multiple working panels is considered and incorporated into the model. Next, a stochastic optimization technique hybridizing the cultural algorithm and random particle swarm optimization has been designed to retrieve model parameters, which can be used to retrieve and predict the 3-D displacement field. Simulated experiments show that the root mean square errors (RMSEs) are 10, 12, and 17 mm in the vertical, east-west, and north-south directions, respectively, by comparing the simulated and retrieved 3-D displacement. Furthermore, the capability of the proposed method is investigated and validated in the Xuehu mining area of China using three ALOS PALSAR acquisitions. Our results agree well with leveling measurements in the vertical direction with an RMSE of 38 mm. Although the retrieved horizontal displacement cannot be validated due to a lack of field surveys, these displacement fields coincide spatially with the evolution of mining excavation. Index Terms-Cultural algorithm and random particle swarm optimization (CA-rPSO), mining displacement, probability integral method (PIM), three-dimensional (3-D) displacement.