Field Measurement and Study on Overburden Fracture and Surface Subsidence Law of Solid Filling Mining under Buildings

In order to predict the surface subsidence scientifically in solid filling mining, it is necessary to establish a complete subsidence prediction model and parameter system according to the evolution law of overburden structure and strata movement characteristics. Mine pressure monitoring and borehole peeping show that the overburden in solid filling mining is mainly a bending zone with relatively complete layered structure, and the overburden only develops a certain height of fault zone near the roof, without collapse. The results show that the surface subsidence pattern of solid filling mining can still be described by probability integral model, and the parameter system of the surface subsidence prediction model based on “equivalent mining height” is further discussed. Finally, the prediction model of surface subsidence established in this paper is applied to an engineering example, and good results are achieved.

A Method of Backfill Mining Crossing the Interchange Bridge and Application of a Ground Subsidence Prediction Model

The traditional backfill mining method is a technology developed by the general trend of green coal mining, but with a high cost and an impact on production efficiency. This paper proposes a structured backfill mining method with high-water materials and pillars. The evolution of roof pressure appearance is assessed through the sensor and monitoring system in the hydraulic support. The main roof fracture step distance is determined based on the roof structure characteristics of backfill mining, and the backfill step distance of underground structural backfill is 22.7 m considering the safety factor. Through the simulation results of Abaqus commercial simulation software, the roof subsidence evolution of different backfill schemes under temporary load and permanent load is compared, and the rationality of the backfill step distance is verified. Based on the probability integral method, the surface subsidence prediction model is proposed, then the final value and the maximum dynamic change value of the surface subsidence at the north and south ends of the interchange bridge by traditional mining and backfill mining are analyzed, which verifies the rationality of the structural backfill mining method.

The Prediction Model of Super Large Subsidence in High Water Table Coal Mining Areas Covered with Thick Unconsolidated Layer

In mining engineering, after the extraction of underground resources, the maximum surface subsidence is usually less than the mining thickness of coal seam. However, under the condition of thick loose layer, some special phenomena appear in surface subsidence, for example, the maximum surface subsidence value is greater than the mining thickness of coal seam. This special phenomenon cannot be predicted by traditional subsidence prediction methods. To solve this problem, by using the numerical simulation software Fast Lagrangian analysis of continua (Flac), we study the changing rules of subsidence with different strata lithology and unconsolidated layer thickness and reveal the formation mechanism of this law. The results show that the effect of the thick unconsolidated layer on the hard rock is greater than that of the soft rock. When the rock is soft, the unconsolidated layer moves as a whole following the bedrock during the whole mining process. The surface subsidence decreases approximately linearly with the thickness ratio increase of the unconsolidated layer to bedrock. However, when the rock is hard or medium hard, there are supporting structures formed inside the rock stratum, which has supporting effect on the overlying strata. The surface subsidence undergoes three proportional sections, first increases, then decreases, and finally increases with the thickness ratio increase of the unconsolidated layer to bedrock. Combined with these laws, based on the theory that the rock strata space can be completely compressed gradually, we derive the calculation method of surface subsidence under the condition of thick unconsolidated layer and apply it to practice. The results show that the prediction results are consistent with the actual situation and meet the engineering requirements. The research results can provide a reference for the subsidence prediction of similar conditions.

Visualizing uncertainty of one-dimensional land subsidence prediction by preparing various local optimal solutions with a genetic algorithm

<p>This study tried to visualize the predictive uncertainty while predicting future land subsidence caused by the groundwater pumping. Because land subsidence modeling is highly uncertain, it is impossible to determine the distribution of subsurface physical property values uniquely. Therefore, we prepared various local optimal solutions through the inversion analysis with a genetic algorithm in order to visualize land subsidence prediction uncertainty. The inversion analysis was conducted using the long-term land subsidence monitoring data at Kawajima in the Kanto Plain, Japan. In this study site, the seasonal groundwater level fluctuations have caused plastic compaction in summer and elastic expansion in winter every year. Obtained multiple sets of subsurface properties were within the range of typical values in the existing literature and satisfactorily reproduced the observed subsidence, showing that the inversion analysis worked well. In addition, the groundwater level scenario analysis was conducted using obtained property sets. This revealed that the subsidences predicted for a sudden groundwater level drop and rapid recovery scenario are more volatile than the subsidences predicted for the stable scenario. This means that it is important to have multiple sets of subsurface properties to predict future land subsidence caused by unprecedented groundwater level fluctuations.</p>