Time function model of dynamic surface subsidence assessment of grout-injected overburden of a coal mine

Wang, Binglong; Xu, Jialin; Xuan, Dayang

doi:10.1016/j.ijrmms.2018.01.044

Cited by 58 publications

(40 citation statements)

References 14 publications

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“…e results of the UDEC numerical model and the theoretical estimation of the abutment pressure for working face 207 are shown in Figure 13. To compare the numerical model results to the theoretical results, we obtained the root mean square errors [46] (0.85 MPa) and relative standard errors [46] (2%) of the theoretical results relative to the numerical results. e root mean square error (0.85 MPa) is much smaller than peak abutment pressure (40.63 MPa) derived from the numerical model, and the relative standard error was less than 5%, which indicates the forms of the stress development curves obtained from the numerical…”

Section: Numerical Simulations Based On Geological Miningmentioning

confidence: 99%

Method to Calculate Working Surface Abutment Pressure Based on Key Strata Theory

Han

Wang

et al. 2019

Advances in Civil Engineering

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Overburden key strata (KS) have a significant influence on abutment pressure distribution. However, current calculation methods for working surface abutment pressure do not consider the influence of the overburden KS. This study uses KS theory to analyze the overburden load transferred to coal-rock masses on both sides of the stope through fractured blocks in different layers of the KS in the fissure zone and KS in different layers of the curve subsidence zone. Using Winkler’s elastic foundation beam theory, we consider the fissure zone KS on the coal mass side and the curve subsidence zone KS as many elastic foundation beams interact with each other. A method to calculate the abutment pressure of the coal mass and the goaf was then established, considering the influence of the overburden KS. The abutment pressure distribution of working surface 207 after mining was then calculated using our method, based on mining conditions present in the Tingnan coal mine. The calculated results were verified using measurements from borehole stress meters and microseismic monitoring systems, as well as numerical simulations. In addition, the calculation results were used to determine a reasonable position for the stopping line and remaining width of the roadway’s protection coal pillar in working surface 207. The results of this study can be used to calculate the abutment pressure distribution of the working surface under a variety of overburden KS conditions. The results can also provide guidance for forecasting and preventing mine dynamic hazards, controlling the surrounding rock in mining roadways, determining reasonable widths for protection coal pillars, and designing the layout of mining roadways.

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Section: Numerical Simulations Based On Geological Miningmentioning

confidence: 99%

Method to Calculate Working Surface Abutment Pressure Based on Key Strata Theory

Han

Wang

et al. 2019

Advances in Civil Engineering

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“…Empirical methods are based on the actual field measurements. These approaches predict subsidence based on parameter relationships developed from field monitoring and experience [1][2][3][4][12][13][14]. The most widely used methods for predicting longwall mining-induced subsidence in Australia are described in detail.…”

Section: Liturature Surveymentioning

confidence: 99%

Mine subsidence prediction using gene expression programming based on multivariable symbolic regression

Rasouli

Shahriar

Madani

2021

ITEGAM- Journal of Engineering and Technology for Industrial Applications (ITEGAM-JETIA)

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Accurate prediction of surface subsidence becomes a significant challenge for active industrial companies in coal mining fields due to the importance of the economic impacts of longwall mining-induced subsidence. This article explores a new variant of genetic programming, namely gene expression programming (GEP). The GEP-based method is utilized to present a new mathematical formula for subsidence prediction in longwall coal mining. The derived model includes both geometrical and geological variables. The data set consists of field measurements obtained through 37 longwall panels of Ulan coal mine, NSW, Australia. The GEP-based model concluded satisfactory subsidence prediction outcomes compared to other empirical methods such as NCB, DMR, ACARP, and IPM. The predictive ability of the GEP-based models, which captures the complex nonlinear effects of the critical factors on the magnitude of subsidence, resulted in a statistically significant improvement in predictive capacity compared to the aforementioned empirical methods. The sensitivity analysis results indicated that Panel width and cover thickness with 31% and 23% were the most influential parameters in the proposed model. Also, the extracted seam thickness, thick layer location, and thick layer thickness had 19%, 16%, and 11% impact on the GEP proposed model, respectively.

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“…Rock caving advances from the seam to the surface at a certain velocity that depends in particular on the physicalmechanical properties of the rocks in the overlying strata (the strength of rocks, stratification, occurrence of water, etc.). For predictive calculation of the dynamic surface subsidence value, the time functions were determined as described (Hu et al, 2015;Wang et al, 2018). The time coefficient expressed using Knothe time function (Knothe, 1953) is represented by:…”

Section: Time Coefficientmentioning

confidence: 99%

Assessment of models to predict surface subsidence in the Czech part of the Upper Silesian Coal Basin - Case study

Jiránková¹

2020

Acta Geodynamica Et Geomaterialia

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This case study presents the verification of two surface subsidence prediction models for longwall mining at depths greater than 400 m. The surface subsidence points were surveyed and compared for both models. The first model uses empirical calculations to predict the surface subsidence. This method is reliable for predicting surface subsidence at shallower depths. At present, however, coal mining has progressed to great depths. The second model is the 2-dimensional finite element method to predict surface subsidence. In contrast to the first method, this method is based on the regional parameters and uses the rock mass properties to evaluate surface subsidence for multiseams at any depth. Results show that the finite element method gives a better approximation of the measured surface subsidence than the Knothe method. The maximum surface subsidence, which was determined by the FEM method, was used to adjust the extraction coefficient in the Knothe's method. The predicted value differs from the measured value by 8 %. The slope of the predicted subsidence trough was within the range of 2-8 % from the surveyed subsidence. This case study proposes a procedure for using both models to successfully predict the surface subsidence.

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Time function model of dynamic surface subsidence assessment of grout-injected overburden of a coal mine

Cited by 58 publications

References 14 publications

Method to Calculate Working Surface Abutment Pressure Based on Key Strata Theory

Method to Calculate Working Surface Abutment Pressure Based on Key Strata Theory

Mine subsidence prediction using gene expression programming based on multivariable symbolic regression

Assessment of models to predict surface subsidence in the Czech part of the Upper Silesian Coal Basin - Case study

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