Gob-side entry driving coal pillar optimal width identification method

Abstract

The invention provides a gob-side entry driving coal pillar optimal width identification method. The method comprises the following steps: establishing a calculation model of an internal stress field width of solid coal according to geological conditions and mine pressure data of a target working face; establishing an expression of the minimum width of the coal pillar and an expression of the maximum width of the coal pillar on the basis of the calculation model of the internal stress field width of the solid coal so as to determine an optimization search domain of the width of the coal pillar; constructing a fitness function taking the coal pillar width as an optimization variable; and carrying out iterative optimization on the fitness function in the optimization search domain by adopting a PLO algorithm, and outputting the optimal width of the coal pillar. According to the method, the gob-side entry driving coal pillar width design efficiency can be remarkably improved, the problems of experience dependence and low efficiency are solved, the operation process is simple, the evaluation result is reliable, evaluation parameters can be quantitatively described, and the surrounding rock control effect is stable and controllable after the optimization result is applied to field engineering.

Description

Method for Identifying the Optimal Width of Coal Pillars in Goaf Excavation Technical Field

[0001] This invention relates to the field of tunnel engineering technology, and in particular to a method for identifying the optimal width of coal pillars in roadway excavation. Background Technology

[0002] Goaf-side excavation is an important pillarless or small-pillar roadway protection technique in coal mining. It refers to excavating a roadway for the current working face along the edge of the goaf of an adjacent mined face, leaving a narrow coal pillar of a certain width. This technique has significant advantages such as increasing coal recovery rate, reducing roadway excavation work, and placing the roadway in a zone of reduced lateral support pressure, making it easier to maintain. It is widely used in coal mining in my country.

[0003] One of the core challenges and difficulties of goaf-side excavation technology lies in determining the appropriate width of the coal pillars for protection. However, if the coal pillar width is too narrow, under the influence of mining stress, severe roof subsidence, plastic failure of the coal pillar, and even loss of load-bearing capacity can easily occur, leading to safety accidents such as roof collapse. Conversely, if the coal pillar width is too large, it will result in wasted coal pillars in the section, causing low economic efficiency in the mine. Therefore, scientifically determining an optimal coal pillar width that balances safety, stability, and economy is crucial for the successful application of goaf-side excavation technology and for promoting safe, efficient, and green mining.

[0004] In recent years, scholars both domestically and internationally have conducted extensive research on the width of coal pillars for roadway protection during goaf excavation. However, most experts and scholars primarily employ physical model experiments, theoretical derivations, and numerical simulations, or a combination of these methods, to study the width of coal pillars for roadway protection during goaf excavation. Theoretical derivations, based on elastoplastic mechanics, limit equilibrium theory, and internal and external stress field theory, typically require significant simplification of complex rock strata structures, constitutive relationships, and boundary conditions. This results in limited model accuracy and a complex calculation process, making it difficult to comprehensively consider the coupled effects of multiple factors. Numerical simulations and physical model experiments typically utilize numerical software such as finite element and discrete element methods, or involve conducting simulation experiments with similar materials. However, model building and parameter selection are time-consuming and laborious, and each simulation or experiment can only perform trial calculations for a specific scheme, lacking automatic optimization and resulting in low efficiency, making it unsuitable for rapid design and scheme optimization. Summary of the Invention

[0005] The purpose of this invention is to provide a method for identifying the optimal width of coal pillars in goaf tunneling, which can significantly improve the efficiency of coal pillar width design in goaf tunneling, solve the problems of reliance on experience and low efficiency, and has a simple operation process, reliable evaluation results, and quantitatively describable evaluation parameters. After applying the optimization results to field engineering, the surrounding rock control effect is stable and controllable.

[0006] To achieve the above objectives, the present invention provides a method for identifying the optimal width of a coal pillar in a goaf-running roadway, comprising:

[0007] A calculation model for the width of the internal stress field of solid coal is established based on the geological conditions and mine pressure data of the target working face.

[0008] Based on the calculation model of the internal stress field width of the solid coal, expressions for the minimum width and maximum width of the coal pillar are established to determine the optimization search domain for the width of the coal pillar.

[0009] A fitness function is constructed with the coal pillar width as the optimization variable, and the fitness function is based on the cross-sectional shrinkage rate f of the goaf roadway. h Coal pillar stress level f y and coal pillar loss resources f j The fitness function is established as follows:

[0010] ,

[0011] Where F is the fitness value;

[0012] The PLO algorithm is used to iteratively optimize the fitness function within the optimization search domain, and the optimal width of the coal pillar is output.

[0013] Optionally, the calculation model for the width l of the internal stress field of the solid coal is as follows:

[0014] ,

[0015] Where L is the length of the working face; C0 is the initial pressure step distance of the basic top of the working face; h m The basic top thickness is given by E; the elastic modulus of the coal seam is given by ξ; and the stiffness coefficient is given by h. c h represents the coal seam thickness. z L is the direct roof thickness; n is the direct roof expansion coefficient; L B γ is the length of the arc-shaped triangular block B; γ is the unit weight of the rock layer.

[0016] Optional, minimum width P of coal pillar min The expression is:

[0017] ,

[0018] Where K is the stress concentration factor of the working surface, H is the burial depth, C is the cohesion, and φ is the internal friction angle.

[0019] Optional, maximum width P of the coal pillar max The expression is: P max =lb, where b is the tunnel width; the optimization search domain is [minimum width of coal pillar, maximum width of coal pillar].

[0020] Optionally, the geological conditions of the target working face include at least the coal seam thickness h.c Uniaxial compressive strength σ of coal pillar t Real-time stress σ of coal pillar m Cohesion C, internal friction angle φ, elastic modulus of coal seam E, and immediate roof thickness h z Direct roof expansion coefficient n, basic roof thickness h m Burial depth H, rock stratum unit weight γ, stiffness coefficient ξ.

[0021] Optionally, the mine pressure data of the target working face includes at least the initial pressure step distance C0 of the basic top of the working face and the length L of the arc-shaped triangular block B. B Working face length L, tunnel width b, working face stress concentration factor K, and roof subsidence h at the point of contact with the goaf. a .

[0022] Optionally, the cross-sectional shrinkage rate f of the goaf roadway. h The calculation method is as follows:

[0023] ,

[0024] Among them, h a h represents the roof subsidence at the point where the goaf touches the rock mass. c Where φ is the coal seam thickness, γ is the internal friction angle, γ is the rock stratum unit weight, K is the stress concentration factor of the working face, H is the burial depth, C is the cohesion, b is the tunnel width, and L is the depth. B Let B be the length of the arc-shaped triangular block, and P be the width of the coal pillar.

[0025] Optional, coal pillar stress level f y The calculation method is as follows:

[0026] ,

[0027] Where, σ m σ represents the real-time stress of the coal pillar. t It represents the uniaxial compressive strength of the coal pillar.

[0028] Optional, coal pillar loss resource situation f j The calculation method is as follows:

[0029] ,

[0030] Where l is the width of the internal stress field of the solid coal, and P is the width of the coal pillar.

[0031] Optionally, the method of using the PLO algorithm to iteratively optimize the fitness function within the optimization search domain includes: when the iteration reaches the convergence state, that is, when the change in the fitness value of the fitness function is less than a preset value, outputting the optimal width of the coal pillar corresponding to the minimum fitness value.

[0032] As configured above, this invention establishes a calculation model for the width of the internal stress field of solid coal, and based on this model, establishes expressions for the minimum and maximum width of the coal pillar, thereby determining the optimization search domain for the coal pillar width. Furthermore, a fitness function with the coal pillar width as the optimization variable is constructed, and the PLO algorithm is used to iteratively optimize the fitness function within the optimization search domain to output the optimal coal pillar width. The optimal coal pillar width identification method provided by this invention is simple to operate, provides reliable evaluation results, and allows for quantitative description of evaluation parameters. It significantly improves the efficiency of coal pillar width design in gob-side excavation, solving the problems of experience dependence and low efficiency. It frees engineers from tedious trial calculations, achieving scientific and streamlined efficient design. After applying the optimization results to on-site engineering, the surrounding rock control effect is stable and controllable. Attached Figure Description

[0033] Those skilled in the art will understand that the accompanying drawings are provided to better understand the invention and do not constitute any limitation on the scope of the invention. Wherein:

[0034] Figure 1 is a schematic diagram of a method for identifying the optimal width of coal pillars in a goaf tunnel according to an embodiment of the present invention. Detailed Implementation

[0035] In this document, unless otherwise stated, the terms “upper,” “lower,” “left,” “right,” “inner,” “outer,” “front,” “back,” “top,” “bottom,” etc., are used to indicate orientation or positional relationship based on the accompanying drawings, and are only for the convenience of describing the invention and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a characteristic orientation and operation, and therefore should not be construed as a limitation of the invention.

[0036] The specific embodiments of the present invention will now be described in more detail with reference to the accompanying drawings. The advantages and features of the present invention will become clearer from the following description. It should be noted that the drawings are all in a very simplified form and use non-precise proportions, and are only used to facilitate and clarify the illustration of the embodiments of the present invention.

[0037] The rise and development of artificial intelligence has provided new insights into the study of coal pillar width. The PLO algorithm, inspired by the rotational motion of high-energy particles traveling towards Earth, primarily simulates the motion of charged particles in the Earth's magnetic field, including rotational motion, auroral elliptical walking, and particle collisions. This invention aims to introduce an intelligent optimization algorithm to automatically optimize the width of coal pillars in goaf excavation, thereby improving the automation and intelligence of coal pillar width design.

[0038] Figure 1 is a schematic diagram of a method for identifying the optimal width of a coal pillar in a goaf tunnel according to an embodiment of the present invention. Referring to Figure 1, the present invention provides a method for identifying the optimal width of a coal pillar in a goaf tunnel, which includes steps S1, S2, S3 and S4. Steps S1, S2, S3 and S4 will be described in detail below.

[0039] Step S1: Based on the theory of internal and external stress fields, establish a calculation model for the width of the internal stress field of the solid coal according to the geological conditions and mine pressure data of the target working face.

[0040] Furthermore, the geological conditions of the target working face include at least the coal seam thickness h. c Uniaxial compressive strength σ of coal pillar t Real-time stress σ of coal pillar m Cohesion C, internal friction angle φ, elastic modulus of coal seam E, and immediate roof thickness h z Direct roof expansion coefficient n, basic roof thickness h m The burial depth H, rock stratum unit weight γ, and stiffness coefficient ξ are all factors to be considered. The target working face's mining pressure data should at least include the initial pressure step distance C0 of the basic roof of the working face and the length L of the arc-shaped triangular block B. B Working face length L, tunnel width b, working face stress concentration factor K, and roof subsidence h at the point of contact with the goaf. a .

[0041] Specifically, the calculation model for the width l of the internal stress field of the solid coal is as follows:

[0042] .

[0043] Among them, l, L, h m h c h z L B The unit of C0 is m, and the unit of γ is kN / m. 3 The unit of E is GPa, which can be understood as L B The value can be considered equal to the period used to press the step distance.

[0044] Step S2: Based on the calculation model of the internal stress field width of the solid coal, establish the expression for the minimum width of the coal pillar and the expression for the maximum width of the coal pillar, so as to determine the optimization search domain for the width of the coal pillar.

[0045] Specifically, the minimum width P of the coal pillar min The expression is:

[0046] ,

[0047] Among them, H and h c The unit is m, the unit of the internal friction angle φ is °, and the unit of C is MPa.

[0048] Maximum width P of coal pillar max The expression is: P max =lb, where b is in meters; the optimization search domain is [minimum width of coal pillar, maximum width of coal pillar], that is, the optimization search domain is [P]. min P max ].

[0049] Step S3: Construct a fitness function with the coal pillar width as the optimization variable.

[0050] The fitness function is based on the cross-sectional shrinkage rate f of the roadway. h Coal pillar stress level f y and coal pillar loss resources f j Establishment. The fitness function is:

[0051] ,

[0052] Where F is the fitness value.

[0053] Cross-sectional shrinkage rate f of the tunnel h The calculation method is as follows:

[0054] ,

[0055] Where P is the width of the coal pillar, h a The unit of P is m.

[0056] Coal pillar stress level f y The calculation method is as follows:

[0057] ,

[0058] Where, σ m σ t The unit is MPa.

[0059] Coal pillar loss resource situation f j The calculation method is as follows:

[0060] .

[0061] Step S4: Use the PLO algorithm to iteratively optimize the fitness function within the optimization search domain and output the optimal width of the coal pillar. For example, the PLO algorithm can be called in the Matlab software environment to iteratively optimize the fitness function.

[0062] Furthermore, prepare the input parameters required for the PLO algorithm, complete the population initialization, and based on the current optimization parameters (i.e., a set of candidate coal pillar width values), call the fitness function to calculate the fitness value F corresponding to each coal pillar width value P.

[0063] The method of using the PLO algorithm to iteratively optimize the fitness function within the optimization search domain includes: when the iteration reaches the convergence state, that is, when the change in the fitness value of the fitness function is less than a preset value (that is, when the fitness value tends to be stable), the optimal width of the coal pillar corresponding to the minimum fitness value is output.

[0064] Furthermore, the current optimization parameters are sorted based on the calculated fitness value F, identifying the current minimum fitness value and its corresponding coal pillar width. It is then determined whether the change in fitness value has reached the preset convergence accuracy or whether the number of iterations has reached the preset upper limit. If either iteration termination condition is met, the calculation stops, and the coal pillar width corresponding to the minimum fitness value is output as the optimal coal pillar width. The iteration process curve can also be output. If the iteration termination condition is not met (i.e., convergence has not been reached), the preset rotational motion, aurora elliptical walking, and particle collision strategies in the PLO algorithm are executed. Based on the current population information, a set of updated optimization parameters (i.e., new candidate coal pillar width values) is generated, and the next round of iteration calculation is performed.

[0065] As configured above, this invention establishes a calculation model for the width of the internal stress field of solid coal, and based on this model, establishes expressions for the minimum and maximum width of the coal pillar, thereby determining the optimization search domain for the coal pillar width. Furthermore, a fitness function with the coal pillar width as the optimization variable is constructed, and the PLO algorithm is used to iteratively optimize the fitness function within the optimization search domain to output the optimal coal pillar width. The optimal coal pillar width identification method provided by this invention is simple to operate, provides reliable evaluation results, and allows for quantitative description of evaluation parameters. It significantly improves the efficiency of coal pillar width design in gob-side excavation, solving the problems of experience dependence and low efficiency. It frees engineers from tedious trial calculations, achieving scientific and streamlined efficient design. After applying the optimization results to on-site engineering, the surrounding rock control effect is stable and controllable.

[0066] It should be noted that references to "an embodiment," "an embodiment," "a specific embodiment," "some embodiments," etc., in the specification only indicate that the described embodiment may include a specific feature, structure, or characteristic. Furthermore, such phrases do not necessarily refer to the same embodiment. Additionally, when a specific feature, structure, or characteristic is described in conjunction with an embodiment, whether explicitly described or not, implementing such a feature, structure, or characteristic in conjunction with other embodiments is within the knowledge of those skilled in the art.

[0067] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple, and relevant parts can be referred to the method section.

[0068] It should also be noted that although the present invention has been disclosed above with reference to preferred embodiments, these embodiments are not intended to limit the present invention. For any person skilled in the art, many possible variations and modifications can be made to the technical solutions of the present invention based on the disclosed technical content, or equivalent embodiments can be modified accordingly, without departing from the scope of the present invention. Therefore, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the present invention shall still fall within the scope of protection of the present invention.

[0069] It should also be understood that, unless otherwise specified or indicated, the terms “first,” “second,” “third,” etc., in the specification are used only to distinguish the various components, elements, and steps in the specification, and not to indicate the logical or sequential relationships between the various components, elements, and steps.

[0070] Furthermore, it should be recognized that the terminology described herein is used only to describe particular embodiments and not to limit the scope of the invention. It must be noted that the singular forms “a” and “an” used herein and in the appended claims include plural bases unless the context clearly indicates otherwise. For example, a reference to “a step” or “an apparatus” means a reference to one or more steps or apparatuses, and may include secondary steps and secondary apparatuses. All conjunctions used should be understood in the broadest sense. Also, the word “or” should be understood to have the definition of logical “or” rather than logical “exclusive OR”, unless the context clearly indicates otherwise. Furthermore, implementation of the methods and / or devices in embodiments of the invention may include performing selected tasks manually, automatically, or in combination.

Claims

1. A method for identifying the optimal width of a coal pillar in a goaf-running roadway, characterized in that, include: A calculation model for the width of the internal stress field of solid coal is established based on the geological conditions and mine pressure data of the target working face. Based on this model, expressions for the minimum and maximum width of the coal pillar are established to determine the optimization search domain for the coal pillar width. A fitness function with the coal pillar width as the optimization variable is constructed, based on the cross-sectional shrinkage rate f of the goaf roadway. h Coal pillar stress level f y and coal pillar loss resources f j The fitness function is established as follows: Where F is the fitness value; the PLO algorithm is used to iteratively optimize the fitness function within the optimization search domain to output the optimal width of the coal pillar.

2. The method for identifying the optimal width of a coal pillar in roadway excavation as described in claim 1, characterized in that, The calculation model for the width l of the internal stress field of the solid coal is as follows: Where L is the length of the working face; C0 is the initial pressure step distance of the basic top of the working face; h m The basic top thickness is given by E; the elastic modulus of the coal seam is given by ξ; and the stiffness coefficient is given by h. c h represents the coal seam thickness. z L is the direct roof thickness; n is the direct roof expansion coefficient; L B γ is the length of the arc-shaped triangular block B; γ is the unit weight of the rock layer.

3. The method for identifying the optimal width of a coal pillar in roadway excavation as described in claim 2, characterized in that, Minimum width P of coal pillar min The expression is: Where K is the stress concentration factor of the working surface, H is the burial depth, C is the cohesion, and φ is the internal friction angle.

4. The method for identifying the optimal width of a coal pillar in roadway excavation as described in claim 2, characterized in that, Maximum width P of coal pillar max The expression is: P max =lb, where b is the tunnel width; the optimization search domain is [minimum width of coal pillar, maximum width of coal pillar].

5. The method for identifying the optimal width of a coal pillar in roadway excavation as described in claim 1, characterized in that, The geological conditions of the target working face include at least the coal seam thickness h. c Uniaxial compressive strength σ of coal pillar t Real-time stress σ of coal pillar m Cohesion C, internal friction angle φ, elastic modulus of coal seam E, and immediate roof thickness h z Direct roof expansion coefficient n, basic roof thickness h m Burial depth H, rock stratum unit weight γ, stiffness coefficient ξ.

6. The method for identifying the optimal width of a coal pillar in roadway excavation as described in claim 1, characterized in that, The target working face's mining pressure data includes at least the initial pressure step distance C0 at the basic top of the working face and the length L of the arc-shaped triangular block B. B Working face length L, tunnel width b, working face stress concentration factor K, and roof subsidence h at the point of contact with the goaf. a .

7. The method for identifying the optimal width of a coal pillar in roadway excavation as described in claim 1, characterized in that, Cross-sectional shrinkage rate f of the tunnel h The calculation method is as follows: , where h a h represents the roof subsidence at the point where the goaf touches the rock mass. c Where φ is the coal seam thickness, γ is the internal friction angle, γ is the rock stratum unit weight, K is the stress concentration factor of the working face, H is the burial depth, C is the cohesion, b is the tunnel width, and L is the depth. B Let B be the length of the arc-shaped triangular block, and P be the width of the coal pillar.

8. The method for identifying the optimal width of a coal pillar in roadway excavation as described in claim 1, characterized in that, Coal pillar stress level f y The calculation method is as follows: , where σ m σ represents the real-time stress of the coal pillar. t It represents the uniaxial compressive strength of the coal pillar.

9. The method for identifying the optimal width of a coal pillar in roadway excavation as described in claim 1, characterized in that, Coal pillar loss resource situation f j The calculation method is as follows: , where l is the width of the internal stress field of the solid coal, and P is the width of the coal pillar.

10. The method for identifying the optimal width of a coal pillar in roadway excavation as described in claim 1, characterized in that, The method of using the PLO algorithm to iteratively optimize the fitness function within the optimization search domain includes: when the iteration reaches the convergence state, if the change in the fitness value of the fitness function is less than a preset value, the optimal width of the coal pillar corresponding to the minimum fitness value is output.

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