Subsidence prediction method based on equivalent mining height theory for solid backfilling mining

Based on the characteristics of strata movement of solid backfilling mining technology, the surface subsidence prediction method based on the equivalent mining height theory was proposed, and the parameters selection guideline of this method was also described. While comparing the parameters of caving mining with equivalent height, the subsidence efficient can be calculated according to the mining height and bulk factor of sagging zone and fracture zone, the tangent of main influence angle of solid backfilling mining is reduced by 0.2-0.5（while it cannot be less than 1.0）. For sake of safety, offset of the inflection point is set to zero, and other parameters, such as horizontal movement coefficient and main propagation angle are equal to the corresponding parameters of caving mining with equivalent height. In the last part, a case study of solid backfilling mining subsidence prediction was described. The results show the applicability of this method and the difference of the maximum subsidence point between the prediction and the observation is less than 5%.

An influence function method based subsidence prediction program for longwall mining operations in inclined coal seams

The distribution of the final surface subsidence basin induced by longwall operations in inclined coal seam could be significantly different from that in flat coal seam and demands special prediction methods. Though many empirical prediction methods have been developed, these methods are inflexible for varying geological and mining conditions. An influence function method has been developed to take the advantage of its fundamentally sound nature and flexibility. In developing this method, significant modifications have been made to the original Knothe function to produce an asymmetrical influence function. The empirical equations for final subsidence parameters derived from US subsidence data and Chinese empirical values have been incorpo- rated into the mathematical models to improve the prediction accuracy. A corresponding computer program is developed. A number of subsidence cases for longwall mining operations in coal seams with varying inclination angles have been used to demonstrate the applicability of the developed subsidence prediction model.

A semi-infinite beam theoretical model on predicting rock slope subsidence induced by underground mining

When the mining goaf is close to the cliff,rock slope subsidence induced by underground mining is significantly affected by its boundary conditions.In this study,an analytical method is proposed by considering the key strata as a semi-infinite Euler-Bernoulli beam rested on a Winkler foundation with a local subsidence area.The analytical solutions of deflection are derived by analyzing the boundary and continuity conditions of the cliff.Then,the analytical solutions are verified by the results from experimental tests,FEM and InSAR,respectively.After that,the influence of changing parameters on deflections is studied with sensitivity analysis.The results show that the distance between goaf and cliff significantly affects the deflection of semi-infinite beam.The response of semi-infinite beam is obviously determined by the length of goaf and the bending stiffness of beam.The comparisons between semi-infinite beam and infinite beam illustrate the ascendancy of the improved model in such problems.

Residual subsidence time series model in mountain area caused by underground mining based on GNSS online monitoring

The residual subsidence caused by underground mining in mountain area has a long subsidence duration time and great potential harm,which seriously threatens the safety of people's production and life in the mining area.Therefore,it is necessary to use appropriate monitoring methods and mathematical models to effectively monitor and predict the residual subsidence caused by underground mining.Compared with traditional level survey and InSAR(Interferometric Synthetic Aperture Radar)technology,GNSS(Global Navigation Satellite System)online monitoring technology has the advantages of long-term monitoring,high precision and more flexible monitoring methods.The empirical equation method of residual subsidence in mining subsidence is effectively combined with the rock creep equation,which can not only describe the residual subsidence process from the mechanism,but also predict the residual subsidence.Therefore,based on GNSS online monitoring technology,combined with the mining subsidence model of mountain area and adding the correlation coefficient of the compaction degree of caving broken rock and the Kelvin model of rock mechanics,this paper constructs the residual subsidence time series model of arbitrary point on the ground in mountain area.Through the example,the predicted results of the model in the inversion parameter phase and the dynamic prediction phase are compared with the measured data sequence.The results show that the model can carry out effective numerical calculation according to the GNSS monitoring data of any point on the ground,and the model prediction effect is good,which provides a new method for the prediction of residual subsidence in mountain mining.

The new method of prediction on mining subsidence and deformation

A new probability function of mining overlying strata and subsidence is put forward that has a general statistical significance based on the ideal stochastic medium displacement model. It establishes a new system of prediction on horizontal mining subsidence and deformation, which gives a new method for prediction on mining subsidence and deformation.

Time series prediction of mining subsidence based on a SVM

In order to study dynamic laws of surface movements over coal mines due to mining activities,a dynamic prediction model of surface movements was established,based on the theory of support vector machines(SVM) and times-series analysis.An engineering application was used to verify the correctness of the model.Measurements from observation stations were analyzed and processed to obtain equal-time interval surface movement data and subjected to tests of stationary,zero means and normality.Then the data were used to train the SVM model.A time series model was established to predict mining subsidence by rational choices of embedding dimensions and SVM parameters.MAPE and WIA were used as indicators to evaluate the accuracy of the model and for generalization performance.In the end,the model was used to predict future surface movements.Data from observation stations in Huaibei coal mining area were used as an example.The results show that the maximum absolute error of subsidence is 9 mm,the maximum relative error 1.5%,the maximum absolute error of displacement 7 mm and the maximum relative error 1.8%.The accuracy and reliability of the model meet the requirements of on-site engineering.The results of the study provide a new approach to investigate the dynamics of surface movements.

An improved influence function method for predicting subsidence caused by longwall mining operations in inclined coal seams

Prediction of surface subsidence caused by longwall mining operation in inclined coal seams is often very challenging. The existing empirical prediction methods are inflexible for varying geological and mining conditions. An improved influence function method has been developed to take the advantage of its fundamentally sound nature and flexibility. In developing this method, the original Knothe function has been transformed to produce a continuous and asymmetrical subsidence influence function. The empirical equations for final subsidence parameters derived from col- lected longwall subsidence data have been incorporated into the mathematical models to improve the prediction accuracy. A number of demonstration cases for longwall mining operations in coal seams with varying inclination angles, depths and panel widths have been used to verify the applicability of the new subsidence prediction model.

Modeling of time dependent subsidence for coal and ore deposits

Coal and ore underground mining generates subsidence and deformation of the land surface. Those defor- mations may cause damage to buildings and infrastructures. The environmental impact of subsidence will not be accepted in the future by the society in many countries. Especially acceptance of the ground deformations decreases every year there, where the mining regions are densely urbanized, the The only solution is to limit the subsidence or its impact on the infrastructure. The first is not rentable for the mining industry, the second depends on the precise subsidence prediction and good preventing management involved in the mining areas. The precision of the subsidence prediction depends strictly on the mathematical model of the deformation phenomenon and on the uncertainty of the input data. The subsidence prediction in the geological conditions of the raw materials used to be made on the basis of numerical modeling or the stochastic models. A modified solution of the stochastic model by Knothe will be presented in the paper. The author focuses on the precise description of the deposit shape and on the time dependent displacements of the rock mass. A two parameters＇ time function has been introduced in the algorithm.

Subsidence rules of underground layer thickness： Lu＇an Coal Base coal mines for different soil as an example, China

Damage caused by underground coal mining is a serious problem in mining areas in China; therefore, studying and obtaining the rules of ground movement and deformation under different geological conditions is of great importance. The numerical software ANSYS was used in this study to simulate mining processes under two special geological conditions： （1） thick unconsolidated soil layer and thin bedrock; （2） thin soil layer and thick bedrock. The rules for ground movement and deformation for different soil layer to bedrock ratios were obtained. On the basis of these rules, a prediction parameter modified model of the influence function was proposed, which is suitable for different values of unconsolidated soil layer thickness. The prediction results were verified using two sets of typical field data.

Time function of surface subsidence based on Harris model in mined-out area

The surface subsidence is a common environmental hazard in mined-out area. Based on careful analysis of the regularity of surface subsidence in mined-out area, we proposed a new time function based on Harris curve model in consideration of the shortage of current surface subsidence time functions. By analyzing the characteristics of the new time function, we found that it could meet the dynamic process, the velocity change process and the acceleration change process during surface subsidence. Then its rationality had been verified through project cases. The results show that the proposed time function model can give a good reflection of the regularity of surface subsidence in mined-out area and can accurately predict surface subsidence. And the prediction data of the model are a little greater than measured data on condition of proper measured data quantity, which is safety in the engineering. This model provides a new method for the analysis of surface subsidence in mined-out area and reference for future prediction, and it is valuable to engineering application.

Surface subsidence due to underground mining operation under weak geological condition in Indonesia

Subsidence analysis and prediction with measured data have been conducted and applied to local strata and mining conditions worldwide. Underground coal mines chose the most suitable analysis and prediction method for them. However, there was no study based on the measured data of subsidence induced by underground mining operation in Indonesia. This paper describes the condition of underground coal mine in Indonesia and then discusses the subsidence behavior due to longwall mining operation based on measured data in Balikpapan coal-bearing formation in Indonesia.

THE APPLICATION OF ACOUSTIC LOGGING METHOD IN THE MODEL AND PARAMETERS IDENTIFICATION OF ROCK MASS

This paper describes the new method that is introduced into prediction of subsidence using system engineering method with acoustic logging and density logging. According to the result of acoustic logging, the real and complex rock beds are divided into a set of different bed groups and the equivalent mechanical model is to be built. Based on the modern control theory,according to the input data (convergence or settlement of the roof) and the output data (surface movement and deformation) of the system, the static parameters of equivalent rock beds can be derived from back calculation using the optimum method. Then the reqression relationship between the dynamic and static parameters can be built. So the prediction of rock and ground movements for other areas in the same district can be done, when using this relationship with the acoustic logging data and density logging data in situ.