Prediction of the Heights of the Water-Conducting Fracture Zone in the Overlying Strata of Shortwall Block Mining Beneath Aquifers in Western China

Yun, Zhang; Cao, Shenggen; Gao, Rui; Guo, Shuai; Lan, Lixin

doi:10.3390/su10051636

Cited by 11 publications

(6 citation statements)

References 18 publications

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“…In this case, the estimated height (H p ) of the WCFZ is 20 times of the coal thickness (d), and the cumulative thickness ( h) of the hard rock above the coal roof is 73.72 m. The hard rock proportional coefficient (c) is 0.9215 according to the Equation (8).…”

Section: The Test Of the Mpga-svr Modelmentioning

confidence: 99%

“…With the increase of mining depths, mining intensity and mining speed, the problem of mine water is becoming more prominent [5]. Therefore, accurately predicting the height of the water-conducting fracture zone (WCFZ) in the mining overburden strata is of great significance for the safe production of coal mining [6][7][8]. In the process of coal mining, the development of a WCFZ in mining overburden strata is an extremely complicated mechanical problem, which is characterized by the fuzzy randomness of the rock stratum structure, the complexity of the mining influence stress change and the nonlinear deformation and failure of the mining overburden.…”

Section: Introductionmentioning

confidence: 99%

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Predicting the Water-Conducting Fracture Zone (WCFZ) Height Using an MPGA-SVR Approach

et al. 2020

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Mine water that inrushes from coal-roof strata has always posed a substantial threat to mining activities every year. Therefore, an accurate prediction of the water-conducting fracture zone (WCFZ) height in the mining overburden strata is of great significance for the prevention and control of mine water accidents. The support vector regression (SVR) is proposed to predict the height of the WCFZ based on the mining depth, hard rock proportional coefficient, mining thickness and length of the working face. Simultaneously, the multi-population genetic algorithm (MPGA) is employed to search for the optimal SVR parameters. The MPGA-SVR model is trained and tested with a total of 69 collected data samples, and it is also applied to a field test. The accuracy and stability of the model were measured by the mean squared error and correlation coefficients. The obtained results show that the MPGA-SVR model achieves a higher accuracy and stability than the traditional empirical formula and genetic algorithm (GA)-SVR model. In terms of the process for optimizing the SVR parameters, the MPGA can find the optimal parameters more quickly and accurately, and it can effectively overcome the problem of premature and slow convergence of the genetic algorithm (GA). The proposed model improves the prediction accuracy and stability, which will help to avoid accidents caused by the inrush of water inrush in mining overburden strata and protect the ecological environment of the mining area.

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Section: The Test Of the Mpga-svr Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Predicting the Water-Conducting Fracture Zone (WCFZ) Height Using an MPGA-SVR Approach

et al. 2020

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“…According to incomplete statistics, gangue accumulation in China has exceeded six billion tons and has increased steadily at a speed of 0.68 billion tons per year, occupying approximately 13,000 hm 3 of land. This can cause serious waste of land resources and water pollution (Zhang, 2019;Wang, 2022). Meanwhile, because of the high carbon content in gangue, large amounts of harmful gases such as CO, CO 2 , and SO 2 can be emitted after spontaneous combustion or slow oxidation of gangue, which then act as new carbon emission sources (Wang, et al, 2016;An, 2017;Liu, et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Control mechanism of the migration of heavy metal ions from gangue backfill bodies in mined-out areas

Zhang

Liu

et al. 2023

Front. Earth Sci.

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In the process of solid backfill mining, the leaching of heavy metal ions from the gangue backfill body in the mined-out area can pose potential risk of polluting water resources in the mine. Accordingly, based on the environment of the gangue backfill body, the migration model of heavy metal ions from the gangue backfill body was established to reveal the pollution mechanism of water resources by the gangue backfill body in the mined-out area. The main factors that affect the migration of heavy metal ions were analyzed, and prevention and control techniques for the leaching and migration of heavy metal ions from gangue backfill bodies were proposed. Research showed that the heavy metal ions in gangue backfill bodies were subjected to the coupled action of seepage, concentration, and stress and then driven by water head pressure and gravitational potential energy to migrate downward along the pore channels in the floor, during which mine water served as the carrier. The migration distance of heavy metal ions increased with time. According to the migration rate, the migration process can be subdivided into three phases: the rapid migration phase (0–50 years), the slow migration phase (50–125 years), and the stable phase (125–200 years). It was concluded that the leaching concentration of heavy metal ions, the particle size of gangue, the permeability of floor strata, and the burial depth of coal seams were the main influencing factors of the migration of heavy metal ions. From the two perspectives of heavy metal ion leaching and migration, prevention and control techniques for the leaching and migration of heavy metal ions from gangue backfill bodies were proposed to protect water resources in mining area. The present study is of great significance to realizing utilization of solid waste in mines and protecting the ecological environment.

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“…ere are many environmental issues associated with mining including air pollution due to dust and gas emission, water contamination, loss of groundwater resources, destruction to the surface structures, and degradation of ecosystems [1,2]. Underground mining, in particular, has a significant influence on ground movement or is known as subsidence, which induces serious environmental disturbances on land [3]. Many studies have been conducted on land degradation above underground coal mine workings such as water content change within the soil, evolution of physical and chemical properties of soil, and vegetation deterioration as shown in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

Field Measurement and Numerical Modelling Study on Mining‐Induced Subsidence in a Typical Underground Mining Area of Northwestern China

Zhang

Bai

Wang

et al. 2021

Advances in Civil Engineering

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Mining-induced subsidence is a great concern for environmental protection in underground mining areas in China and all over the world. In view of the fact that the research on land degradation above underground coal mines are completely or partially independent of coal mining activity and the fact that the mechanism behind mining-induced subsidence has not been well understood, this study presents a field measurement and numerical study of mining-induced subsidence with respect to mining activity of three adjacent longwall panels in a coal mine in Northwest China. This study shows that surface subsidence lags far behind panel extraction or mining activity. The profiles of ground surface are dominated and manifested by the subsurface strata structures. The subsidence influence throughout the whole length of a longwall panel varies. Stability of strata structures within overburden before the final subsidence controls the stability of ground surface land. Chain pillars of 20 m between panels of 240 m wide with cover depth of 600 m have been crushed in the gob and do not have any function in supporting the overburden strata. The final subsidence of the three adjacent panels is far to come in the future and the land reuse above underground coal mines should be carefully planned by making sure that the gob is completely compacted or no potential secondary subsidence occurs in the future.

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Prediction of the Heights of the Water-Conducting Fracture Zone in the Overlying Strata of Shortwall Block Mining Beneath Aquifers in Western China

Cited by 11 publications

References 18 publications

Predicting the Water-Conducting Fracture Zone (WCFZ) Height Using an MPGA-SVR Approach

Predicting the Water-Conducting Fracture Zone (WCFZ) Height Using an MPGA-SVR Approach

Control mechanism of the migration of heavy metal ions from gangue backfill bodies in mined-out areas

Field Measurement and Numerical Modelling Study on Mining‐Induced Subsidence in a Typical Underground Mining Area of Northwestern China

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