A surface mining intensity index calculation model based on mining parameters

Abstract

This invention discloses a surface mining intensity index calculation model based on mining parameters. It uses mining width, mining depth, loose layer thickness, mining face thickness, and mining speed as factors to evaluate surface mining intensity. A 3x3 Boltzmann calculation model is constructed to obtain a surface mining intensity coefficient, which is then used as an index to measure surface mining intensity. This invention, by considering four mining parameters—mining thickness, mining depth, working face width, and working face advance speed—to obtain the surface mining intensity coefficient, provides a more comprehensive evaluation compared to previous methods that used mining sufficiency and whether the surface had reached the critical maximum subsidence value.

Description

Technical Field

[0001] This invention relates to the field of surface mining intensity index calculation technology. Specifically, it is a surface mining intensity index calculation model based on mining parameters. Background Technology

[0002] As coal resources in the eastern and central regions gradually deplete, the Northwest region will become my country's main energy supply base. The Northwest region is rich in coal resources, with simple geological conditions, stable occurrence, thin bedrock, relatively shallow burial, excellent coal quality, and most coal seams are quite thick with numerous mineable layers, making it suitable for large-scale surface mining. On the other hand, the Northwest region is arid and water-scarce, with low vegetation cover and poor resistance to disturbance, resulting in an extremely fragile ecological environment. Large-scale coal mining will inevitably cause surface damage, soil erosion, vegetation degradation, desertification, and environmental pollution.

[0003] In current research on the disturbance caused by coal mining to the Earth's surface, some researchers have proposed the concept of "mining sufficiency" to describe the impact of mining size on the maximum surface subsidence. Guo Wenbing et al. evaluated the degree of surface disturbance based on 14 geological mining factors, but this method is difficult to apply in practice due to the large number of factors considered.

[0004] In existing technologies, the degree of mining sufficiency is used to describe the degree of surface subsidence, and it is divided into insufficient mining, sufficient mining, and over-sufficient mining. It is mainly used to calculate the maximum surface subsidence value. For example, the maximum surface subsidence value of insufficient mining is calculated by introducing the mining degree coefficient ρ.

[0005] W fm =ρW cm =ρqMcosα

[0006] In the formula, therefore,

[0007] like Figure 1 As shown, here: W fm —Maximum surface subsidence under insufficient mining conditions; W cm —Maximum surface subsidence value after full mining; D—Working face width; L—Working face advance length; ρ—Mining degree coefficient; H0—Average mining depth, m; M—Working face thickness; k D —Mining width to mining depth ratio; A3, A4 —Boltzmann coefficients; n1 and n2 are taken as 1 when they are greater than 1, α —coal seam dip angle, q —subsidence coefficient when fully mined.

[0008] The description of mining sufficiency essentially considers the size of the goaf in the working face area, thus determining the degree of surface mining (sufficiency). The aforementioned mining sufficiency coefficient is mainly based on the width-to-depth ratio (D / H) to represent mining sufficiency, but it does not consider mining thickness, cannot evaluate the magnitude of surface deformation, and its impact on the surface is incomplete. It can be said that currently, there is no clear definition of "surface mining intensity" both domestically and internationally. Therefore, it is necessary to clarify the definition and indicator system of surface mining intensity to provide guidance for the rational development of resources, subsidence control, environmental protection, soil and water conservation, and sustainable social development in western mining areas. Summary of the Invention

[0009] Therefore, the technical problem to be solved by this invention is to provide a surface mining intensity index calculation model based on mining parameters that can comprehensively evaluate the surface mining intensity. The aim is to calculate the surface mining intensity coefficient using this model, given relevant mining parameters, and to more comprehensively evaluate the degree of surface mining. This invention is suitable for evaluating the surface mining intensity of general mining operations and guiding the mining situation at the working face.

[0010] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0011] A surface mining intensity index calculation model based on mining parameters is proposed. The model uses mining width, mining depth, loose layer thickness, mining thickness and mining speed as factors to evaluate surface mining intensity. A three-square Boltzmann calculation model is constructed to obtain the surface mining intensity coefficient, which is then used as an index to measure surface mining intensity.

[0012] The above-mentioned model for calculating the surface mining intensity index based on mining parameters involves the following modeling and calculation steps:

[0013] Step (1): Determine the values ​​of each mining parameter based on the geological mining conditions and mining technology of the working face: mining width D, mining depth H, loose layer thickness hs, mining thickness M, and mining speed V;

[0014] Step (2): Calculate the Boltzmann function based on the mining width D, mining depth H, and loose layer thickness hs to obtain the comprehensive width-to-depth ratio influence model:

[0015] Step (3): Calculate the value of the Boltzmann function based on the mining thickness M to obtain the mining thickness influence model: BZM2(M);

[0016] Step (4): Calculate the value of the Boltzmann function based on the mining speed V to obtain the mining speed influence model: BZM3(V);

[0017] Step (5): Calculation The product of BZM2(M) and BZM3(V) yields the surface mining intensity coefficient ks.

[0018] In the above calculation model of surface mining intensity index based on mining parameters, step (2) is as follows:

[0019]

[0020] In Formula I: D is the mining width in meters, H is the mining depth in meters, and hs is the loose layer thickness in meters; The value range is [0, 1].

[0021] In the above calculation model for surface mining intensity index based on mining parameters, step (3) is as follows:

[0022]

[0023] In Formula II, M is the mining thickness in meters; the value range of BZM2(M) is [1.0, 1.5].

[0024] In the above calculation model of surface mining intensity index based on mining parameters, step (4) is as follows:

[0025]

[0026] In Formula III, V is the mining speed in m / s; the value range of BZM3(V) is [0.367, 0.667].

[0027] In the above calculation model of surface mining intensity index based on mining parameters, step (2) is as follows:

[0028] In step (3):

[0029] In step (4):

[0030] In step (5):

[0031] In Formula I: D is the mining width in meters, H is the mining depth in meters, and hs is the loose layer thickness in meters;

[0032] In Formula II, M represents the mining thickness in meters;

[0033] In Formula III, V represents the mining speed, measured in meters per second.

[0034] The above-mentioned surface mining intensity index calculation model based on mining parameters has a surface mining intensity coefficient ks ranging from 0 to 1.0: when the surface mining intensity coefficient ks is in the range of 0.3 to 0.6, the working face of the mining area is in the medium to high intensity mining; when the surface mining intensity coefficient ks is in the range of 0.6 to 1.0, the working face of the mining area is in the high intensity mining; and when the surface mining intensity coefficient ks is in the range of 0 to 0.3, the working face of the mining area is in the low intensity mining.

[0035] The technical solution of the present invention achieves the following beneficial technical effects:

[0036] This invention designs a calculation model for the surface mining intensity index, simplifying the calculation process and clearly expressing the scientific connotation of surface mining intensity without complex calculations. This calculation model uses mining thickness M, mining depth H, working face width D, and working face advance speed V as mining parameters to establish a three-square Boltzmann (LEBoltzmann) calculation model for the surface mining intensity index. The surface mining intensity index calculation model proposed in this invention, based on mining parameters, can obtain the surface mining intensity coefficient by considering four mining parameters: mining thickness, mining depth, working face width, and working face advance speed. Compared with previous methods that used mining sufficiency and whether the surface reached the critical maximum subsidence value to evaluate the degree of surface mining, this model provides a more comprehensive evaluation. Attached Figure Description

[0037] Figure 1 Schematic diagram of the relationship between the surface of the mining area and the working face;

[0038] Figure 2 A schematic diagram of mining parameters for a mining face in this invention;

[0039] Figure 3 A model diagram of the comprehensive aspect ratio influence model BZM1 in this invention;

[0040] Figure 4 The model diagram of the thickness influence model BZM2 in this invention;

[0041] Figure 5 Model diagram of BZM3, the model for the influence of mining speed in this invention;

[0042] Figure 6 Surface mining intensity coefficient model diagram in this invention;

[0043] Figure 7 In this embodiment of the invention, a group of coal seam-strata columnar diagrams from some observation stations' working faces is provided.

[0044] Figure 8 Another set of coal seam-strata columnar diagrams from the working faces of the observation stations in this embodiment of the invention;

[0045] Figure 9Schematic diagram of the impact components and intensity coefficients of mining in the western Shendong mining area (including 9 mining areas) and the North China Fengfeng mining area in this embodiment of the invention;

[0046] Figure 10 A schematic diagram of the mining intensity coefficient of typical working faces in various mining areas in this embodiment of the invention. Detailed Implementation

[0047] like Figure 2 The diagram shows the mining parameters of a working face in a mining area where a near-horizontal coal seam (α = 1° to 5°) is being mined. The average mining depth H is 240 meters, the mining thickness M is 6.5 to 8.8 meters, the working face size is 300 meters × 5255 meters, the advance speed V is 12 meters per second, and the loose layer thickness hs is 0 to 27 meters. Sections A and B in the diagram represent surface subsidence areas.

[0048] This embodiment uses mining width, mining depth, loose layer thickness, mining thickness, and mining speed as factors to evaluate surface mining intensity. A 3x3 Boltzmann calculation model is constructed to obtain the surface mining intensity coefficient, which is then used as an indicator to measure surface mining intensity. The specific modeling and calculation steps are as follows:

[0049] Step (1): Surface mining intensity refers to a mining subsidence state characterized by thick coal seams, shallow burial depth, wide working faces, rapid advancement, large movement of rock strata and the surface, and severe deformation. Therefore, mining parameters can be determined based on the geological and mining conditions of the working face and the mining technology. In this embodiment, the mining parameters are determined based on the geological and mining conditions of the working face and the mining technology as follows: mining width D = 300m, mining depth H = 240m, and loose layer thickness... Mining thickness Mining speed V = 12 m / s.

[0050] Step (2): Calculate the Boltzmann function value based on the mining width D, mining depth H, and loose layer thickness hs:

[0051] Step (3): Calculate the value of the Boltzmann function based on the mining thickness M:

[0052]

[0053] Step (4): Calculate the value of the Boltzmann function based on the mining speed V:

[0054]

[0055] Step (5): Calculation The product of BZM2(M) and BZM3(V) yields the surface mining intensity coefficient ks;

[0056]

[0057] The surface mining intensity coefficients of other mining areas in the western Shendong mining area and the Xin'an mine in the Fengfeng mining area of ​​North China were calculated using the calculation steps of this embodiment. The calculation results for each mining area are shown in the table below:

[0058]

[0059] During the calculation process, such as Figures 3 to 5 As shown, The values ​​of are [0, 1], BZM2(M) is [1.0, 1.5], and BZM3(V) is [0.367, 0.667]. As can be seen from the table above, the surface mining intensity coefficient ks of the 14 working faces in the western Shendong mining area ranges from 0.442 to 0.992. In contrast, the surface mining intensity coefficient ks of the Xin'an mine in the Fengfeng mining area of ​​North China is only 0.048, less than 1 / 10 of that of the western Shendong mining area. When the surface mining intensity coefficient ks is in the range of 0.3 to 0.6, the working face in the mining area is under medium-to-high intensity mining; when the surface mining intensity coefficient ks is in the range of 0.6 to 1.0, the working face in the mining area is under high intensity mining; when the surface mining intensity coefficient ks is in the range of 0 to 0.3, the working face in the mining area is under low intensity mining. Therefore, it can be concluded that the Xin'an mine in the Fengfeng mining area of ​​North China mainly uses low-intensity mining.

[0060] In addition, the researchers of this invention also used the above method to calculate the surface mining intensity of the working faces of the following mining areas in the Huaihe River Basin: Huaibei Yuandian 7222, Huaibei Yuandian 1025, Pan'er Mine 11123, Pan'sidong 11111, Pan'san Mine 1622(3), Pan'sidong 11113, Guqiao Mine 1117(1), Guqiao Mine 1117(3), Gubei Mine 1232(3), Xieqiao Mine 1242(3), Zhangji Mine 11418(W); the central mining area: Zhaojiazai 11206, Xinyi Mine 11010, Xinyi Mine 11020; and the North China mining area: Sihe Mine 4307 and Sihe Mine 1308. The results are as follows. Figure 10 As shown.

[0061] Based on the surface mining intensity coefficient calculated above, when carrying out backfilling mining, the backfill thickness should be reasonably calculated before backfilling, taking into account factors such as the protection requirements of the protected objects in the mining area, coal seam occurrence parameters, and backfilling methods. This provides guidance for the overall planning and cost calculation before backfilling mining, maximizing economic benefits while controlling surface deformation. If the surface mining intensity is not used for calculation, the traditional method to obtain the backfill thickness is to select a test area for backfilling experiments before full backfilling, obtain the compression rate of the backfill body through experiments, observe the surface subsidence, calculate various indicators, and then adjust the material backfill thickness. This method is time-consuming and labor-intensive and cannot maximize economic benefits. The evaluation model in this embodiment evaluates surface mining intensity based on four main factors, taking into account the mining area and mining thickness, and calculates the surface mining intensity coefficient. It is more comprehensive and reasonable than the previous mining sufficiency evaluation model based on two factors: working face width and mining depth; and simpler and clearer than the evaluation model using more than 10 factors, providing a basis for optimizing mining process parameters in the mining area.

[0062] Obviously, the above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of the claims of this patent application.

Claims

1. A method for calculating surface mining intensity index based on mining parameters, characterized in that, The factors used to evaluate the intensity of surface mining are mining width, mining depth, loose layer thickness, mining thickness, and mining speed. ， A three-square Boltzmann calculation model was constructed to obtain the surface mining intensity coefficient, which was then used as an indicator to measure the intensity of surface mining. The modeling and calculation steps are as follows: Step (1): Determine the mining parameters based on the geological and mining conditions of the working face and the mining technology: mining width D Mining depth H Loose layer thickness hs Mining thickness M and mining speed V ; Step (2): Based on the mining width D Mining depth H and loose layer thickness hs Calculate the value of the Boltzmann function to obtain the comprehensive aspect ratio influence model: ; , (Formula I); In Formula I: D This refers to the width of the quarry, in meters. H The depth of the mine is expressed in meters. hs The thickness of the loose layer is expressed in meters. Step (3): Based on the mining thickness M Calculate the value of the Boltzmann function to obtain the thickness influence model: BZM2 (M) ; , (Formula II); In formula II, M The thickness of the material being mined is measured in meters. Step (4): Based on the mining speed V Calculate the value of the Boltzmann function to obtain the model of the impact of mining speed: BZM3(V) ; , (Formula III); In Formula III, V Mining speed, in m / s; Step (5): Calculation , BZM2 (M) and BZM3(V) The product of these two factors yields the surface mining intensity coefficient. ks ; , (Formula IV).

2. The method for calculating the surface mining intensity index based on mining parameters according to claim 1, characterized in that, Surface mining intensity coefficient ks The value range is 0 to 1.0: when the surface mining intensity coefficient is... ks When the coefficient is in the range of 0.3 to 0.6, the working face of the mining area is characterized by medium to high intensity mining; when the surface mining intensity coefficient is within the range of 0.3 to 0.6, the mining area is characterized by medium to high intensity mining. ks When the surface mining intensity coefficient is in the range of 0.6 to 1.0, the working face of the mining area is subjected to high-intensity mining; ks When the value is in the range of 0 to 0.3, the working face of the mining area is subjected to low-intensity mining.

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