Combined ANN prediction model for failure depth of coal seam floors

Failure depth of coal seam floors is one of the important considerations that must be kept in mind when mining is carried out above a confined aquifer. In order to study the factors that affect the failure depth of coal seam floors such as mining depth, coal seam pitch, mining thickness, workface length and faults, we propose a combined artificial neural networks (ANN) prediction model for failure depth of coal seam floors on the basis of existing engineering data by using genetic algorithms to train the ANN. A practical engineering application at the Taoyuan Coal Mine indicates that this method can effectively determine the network struc- ture and training parameters, with the predicted results agreeing with practical measurements. Therefore, this method can be applied to relevant engineering projects with satisfactory results.

Analysis of floor failure depth by using electric profiling method in longwall gangue backfill mining

In underground mining, floor failure depth accompanying mining phases usually results from changes in the advance abutment pressure in the coal mass, and changes in stress redistribution in the areas that have already been mined. Although a variety of techniques have been applied to determine the failure depth, and a number of studies have provided the evidence for the decreasing of failure depth under backfilling, these methods and interactions have not been unequivocally identified. Based on the premise of one possible relation between the failure depth and filling body, which is that the filling materials （gangue） in the gob area can not only restrain the movement of the overlying strata effectively, but also can help to decrease failure depth of the floor in the coal mine. The failure depth in a specific longwall gangue backfilling mine was measured using the mine electricity profiling method. These electrode cables are arranged in a crossheading order to measure the depth and position of the destroyed floor using the DC method. After this, several different methods were used to interpret the recorded data from the field study for gaining failure depth, and the results were compared to the theoretical calculation values. And finally, the authors analyzed the reasons for failure depth form values recorded not indicating a large decrease trend when compared to the theoretical calculation. In this area, it is found that： ① The results using the mine electricity profiling method turns out to be robust and can be used in predicting floor failure depth, and the horizontal position of the maximum destroyed in working face of longwall backfilling. The maximum destroyed position and failure space of the floor can be identified by using this method. ②There is a time-delay processing between the advance of the working face and the failure of floor strata in the mining processing. ③Additionally, based on the data collected from field measurements, which includes three different test electrode spacing approaches （single, double and triple electrode spacing）, and the theoretical value from theoretical calculations. The premise mentioned above cannot be supported during the specific field test, and the role of the filling body in the mined area cannot decrease the floor failure depth effectively in comparison to the theory predictions. Basically, the failure depths in the two different methods have similar results and it is possible that there will not be a direct correlation between the filling body and failure depth. ④Although the failure depth cannot decrease effectiveness when using gangue backfilling in the field testing, due to gob gangue, filling materials being able to deliver the abutment pressure from the overburden in most cases, once they were compacted and rammed by the overburden pressure, it still can make the fracture of the gob area clog and be further consolidated. In this way, it is assumed that water-bursting accidents can be prevented effectively under backfill mining. For this reason, gangue backfilling may make a significant contribution to safety mining.

Analytical solution for stress and deformation of the mining floor based on integral transform

Following exploitation of a coal seam, the final stress field is the sum of in situ stress field and an excavation stress field. Based on this feature, we firstly established a mechanics analytical model of the mining floor strata. Then the study applied Fourier integral transform to solve a biharmonic equation,obtaining the analytical solution of the stress and displacement of the mining floor. Additionally, this investigation used the Mohr–Coulomb yield criterion to determine the plastic failure depth of the floor strata. The calculation process showed that the plastic failure depth of the floor and floor heave are related to the mining width, burial depth and physical–mechanical properties. The results from an example show that the curve of the plastic failure depth of the mining floor is characterized by a funnel shape and the maximum failure depth generates in the middle of mining floor; and that the maximum and minimum principal stresses change distinctly in the shallow layer and tend to a fixed value with an increase in depth. Based on the displacement results, the maximum floor heave appears in the middle of the stope and its value is 0.107 m. This will provide a basis for floor control. Lastly, we have verified the analytical results using FLAC3 Dto simulate floor excavation and find that there is some deviation between the two results, but their overall tendency is consistent which illustrates that the analysis method can well solve the stress and displacement of the floor.