Design method of high-performance grouting material accurately matched with physical property structure of soft coal rock

Abstract

The invention discloses a design method of a high-performance grouting material accurately matched with a soft coal rock physical property structure, and relates to the technical field of geotechnical engineering grouting. According to the method, mineral components, permeability, fracture distribution, strength, wettability and hydrological characteristics of soft coal rock are analyzed through multi-dimensional tests such as X-ray diffraction and a scanning electron microscope, and a quantitative mapping relation between physical property parameters and grouting material performance is established; constructing a grouting reinforcement material database comprising a material sub-library, a performance sub-library and a case sub-library, and introducing a generative adversarial network to dynamically update the fracture model; an orthogonal test and a machine learning algorithm are adopted to carry out multi-objective ratio optimization, and precise matching of grouting material performance and engineering geological conditions is realized in combination with field adaptability index closed-loop verification. According to the method, the grout groutability and the surrounding rock deformation control effect can be remarkably improved, the technical problems that a traditional grouting material depends on experience, and a database is static and low in efficiency are solved, and an intelligent solution is provided for complex soft coal rock engineering reinforcement.

Description

Technical Field

[0001] This invention belongs to the field of grouting technology in geotechnical engineering, and in particular relates to a design method for high-performance grouting materials that accurately match the physical properties of soft coal and rock. Background Technology

[0002] In current grouting engineering practice, the insufficient compatibility between the performance of grouting materials and the physical and structural characteristics of coal and rock masses has become a key bottleneck restricting the reinforcement effect. The properties of coal and rock masses vary significantly under different engineering scenarios. For example, fractured mudstone has a macroscopic fracture network, weak coal bodies develop microfractures, and there are water-rich environments. However, currently, no single grouting material can meet the grouting requirements under all working conditions. How to rationally select the best-matching grouting material and grout ratio parameters for different soft coal and rock mass properties is of great significance for ensuring the grouting reinforcement effect in soft coal and rock engineering. Existing technologies mostly focus on the research and development of grouting materials with specific functions (such as CN202311291869.1, CN202411177090.1, etc.). This "single formula" design mode cannot be applied to the dynamically changing engineering geological conditions in actual engineering projects, and it is difficult to achieve precise synergistic matching between the multi-dimensional technical performance parameters such as grout injectability, permeability, affinity, and adhesion and the physical and structural characteristics of soft coal and rock masses. While a few published patents (such as CN202411627395.8 and CN202411433785.1) attempt to improve grout performance by adding admixtures, they mostly employ experience-driven designs and lack a reverse-engineering method for grouting material design based on refined characteristic parameters of the physical properties and structure of soft coal and rock masses. Therefore, there is an urgent need to construct a collaborative grouting material design method based on the entire chain of "coal and rock physical property structure analysis - grouting material selection and design - grout comprehensive performance optimization," to obtain the mapping relationship between "coal and rock physical property structure - grout comprehensive performance" and a grouting material database, thereby achieving precise integration of grouting materials with the engineering geological conditions of coal and rock. Summary of the Invention

[0003] This invention addresses the shortcomings of existing grouting reinforcement material design methods by providing a high-performance grouting reinforcement material design method that precisely matches the physical and structural characteristics of soft coal and rock. This method enables precise, intelligent, rapid, and efficient design of soft rock grouting materials.

[0004] To solve the above-mentioned technical problems, the present invention is achieved through the following technical solution:

[0005] This invention relates to a design method for high-performance grouting materials that precisely match the physical properties and structure of soft coal and rock, comprising the following steps:

[0006] S1: Analysis of target coal and rock physical properties: Multi-dimensional tests are conducted on the soft coal and rock mass to be reinforced to obtain mineral composition characteristics, permeability characteristics, fracture distribution characteristics, strength characteristics, wetting characteristics and hydrophysical characteristics;

[0007] S2: Performance threshold mapping: Based on the physical property parameters obtained in S1, establish a physical property-performance mapping relationship and determine the threshold of key performance indicators for grouting materials;

[0008] S3: Establishment of a multi-source grouting material database: Establish a grouting reinforcement material database that includes material sub-libraries, performance sub-libraries, and case sub-libraries;

[0009] S4: Intelligent Database Retrieval: Retrieve the case sub-library of the pre-built grouting reinforcement material database. If there is an engineering case with matching physical property characteristics, select the corresponding grouting material mix ratio scheme; otherwise, proceed to S5.

[0010] S5: Multi-constraint optimization design: Using the performance threshold determined in S2 as boundary conditions, the grouting material ratio parameters are optimized through orthogonal experiments and machine learning algorithms to generate candidate solutions;

[0011] S6: Closed-loop verification feedback: Verify the laboratory performance and field application effect of the candidate solution, and store successful cases in the database case sub-library.

[0012] As a preferred technical solution of the present invention, the specific method for conducting multi-dimensional testing on the soft coal rock mass to be reinforced in step S1 is as follows:

[0013] Mineral composition characteristics: The content and distribution of mineral components were analyzed using XRD and SEM-EDS techniques;

[0014] Permeability characteristics: The permeability level is classified into six levels using panoramic digital images of the borehole, micro-CT or SEM images, and borehole water pressure tests;

[0015] Fractured distribution characteristics: Digital images of fracture structures are obtained through borehole panoramic testing, and the statistical distribution patterns of fractures are learned using GAN or CNN.

[0016] Strength characteristics: obtained through laboratory standard uniaxial compression tests;

[0017] Wetting characteristics: characterized by the contact angle of the water-rock interface;

[0018] Hydrophysical characteristics: characterized by the disintegration resistance index.

[0019] As a preferred embodiment of the present invention, S2 specifically includes:

[0020] Based on the permeability characteristics, the threshold value for the critical fracture aperture value that the grout can be injected is determined;

[0021] Based on the characteristics of crack distribution, the threshold values ​​for slurry fluidity indicators are determined.

[0022] Based on the characteristics of fracture distribution and strength, the threshold values ​​of stone body strength, stone body toughness and magma-rock bond strength were determined through numerical simulation.

[0023] Based on mineral composition and hydrophysical characteristics, thresholds for slurry stability and slurry swelling were determined.

[0024] Based on wetting and hydrophysiological characteristics, the threshold for magma-rock affinity was determined.

[0025] As a preferred embodiment of the present invention, the rules for performance threshold mapping in step S2 include the following:

[0026] Permeability matching: The critical fracture aperture into which the grout can be injected is ≤ the equivalent fracture aperture of the coal and rock;

[0027] Crack distribution matching: Simulate the slurry penetration and diffusion range based on the crack network to limit rheological properties and setting time;

[0028] Hydraulic characteristics matching: weakly disintegrated coal and rock have a water outflow rate ≤10%, medium / strongly disintegrated coal and rock have a water outflow rate ≤5%, and the expansion rate offsets the shrinkage and is positively correlated with the bond strength;

[0029] Wetting characteristics matching: contact angle of hydrophilic coal and rock <60°, contact angle of medium / strong disintegration hydrophobic coal and rock >120°.

[0030] As a preferred technical solution of the present invention, step S3 includes: adopting a multi-dimensional quantitative evaluation index system for the comprehensive performance of grouting materials, deconstructing the comprehensive performance of grouting materials into a two-dimensional evaluation system including permeability characteristics and strength characteristics, testing and analyzing the performance of grouting materials based on a grouting material performance parameter characterization test method that integrates multiple modern testing technologies, and establishing a grouting reinforcement material database based on the data obtained from the test analysis.

[0031] As a preferred technical solution of the present invention, the dual-dimensional evaluation system specifically includes the following indicators:

[0032] Permeability characteristics: fineness of grouting material, particle size of grout flocculation particles, critical fracture aperture value for grout injection, rheological properties of grout, time-varying viscosity of grout, static contact angle between grout and rock, and surface tension of grout;

[0033] Strength characteristics: grout water separation rate, grout stone formation rate, grout expansion rate, tensile strength of stone body, compressive strength of stone body, toughness of stone body, tensile strength of grout-rock bonding interface, and shear strength of grout-rock bonding interface.

[0034] As a preferred technical solution of the present invention, the grouting reinforcement material database includes:

[0035] Materials Sub-library: Used to store basic material information for various cementitious materials and admixtures used in grouting reinforcement;

[0036] Performance Sub-library: Stores data on 21 performance indicators, including permeability and strength characteristics, obtained through standardized testing methods under various grouting material ratio schemes;

[0037] Case study sub-library: used to store engineering geological conditions, corresponding physical property parameters, grouting material ratios used, and on-site application effects.

[0038] As a preferred embodiment of the present invention, the method for characterizing and testing the performance parameters of the grouting material is as follows:

[0039] Grouting material fineness: determined using a laser particle size analyzer;

[0040] Particle size of slurry flocculation: measured using a focused beam reflectivity measurement system;

[0041] Critical fracture aperture value for grout injection: In-situ microscopic visualization grouting test was used;

[0042] Slurry rheological properties: Regression analysis was performed using a rotational viscometer combined with Newton, Bingham, or Herschel-Barclay rheological models;

[0043] Slurry viscosity-time degradation: Vicat apparatus was used;

[0044] Static contact angle between magma and rock: measured using a contact angle measuring instrument;

[0045] Slurry surface tension: Surface tension meter was used;

[0046] Slurry water separation rate and stone formation rate: volumetric method was used;

[0047] Slurry expansion rate: determined using a linear dilatometer method;

[0048] Tensile strength of the stone: determined using the Brazilian splitting method;

[0049] Stone compressive strength: tested using a standard uniaxial compression test;

[0050] Stone body elongation: Standard direct tensile test was used;

[0051] Tensile strength of the magma-rock bond interface: tested using the standard direct tensile test;

[0052] Shear strength of the magma-rock bond interface: Standard direct shear test was used.

[0053] As a preferred embodiment of the present invention, in the method for testing the rheological properties of slurry, the specific rheological model is subjected to mathematical regression analysis based on the experimental data using the following formula:

[0054]

[0055] Where: μ is the dynamic viscosity of the Newtonian fluid, τ0 is the initial yield stress of the Bingham fluid and the Herschel-Bulkley fluid, and μ p Let V be the plastic viscosity of Bingham fluid, and n be the consistency coefficient and rheological index of Herschel-Bulkley fluid, respectively. γ is the shear rate. The apparent viscosity of Bingham fluid and Herschel-Bulkley fluid can be calculated according to equation (1):

[0056]

[0057] Where: μ v This refers to the apparent viscosity.

[0058] As a preferred embodiment of the present invention, step S5 specifically includes the following steps:

[0059] Factor analysis and orthogonal experiment: Identify key influencing factors and their level ranges, and design a multidimensional orthogonal experiment matrix;

[0060] Optimization design of grouting reinforcement material performance: nonlinear mapping relationship is established by machine learning algorithm, and multi-objective optimization is performed by GAN and response surface methodology;

[0061] Optimization scheme verification and selection: Verify the performance indicators of candidate schemes through laboratory testing, and select the optimal ratio scheme.

[0062] The present invention has the following beneficial effects:

[0063] Precise matching: Through six-dimensional physical property analysis and two-dimensional performance mapping, quantitative matching between slurry properties and coal and rock conditions is achieved, solving the defects of traditional "one-size-fits-all" design;

[0064] Intelligent and efficient: By introducing AI technologies such as GAN and CNN to process crack data and optimize the ratio, the R&D cycle is shortened by more than 50% compared with the traditional trial and error method;

[0065] Data-driven: The database stores 21 standardized performance parameters and engineering cases, supporting rapid selection for similar working conditions and reducing the cost of repetitive research;

[0066] Full-chain closed loop: The six-step process from physical property analysis to on-site verification forms a complete technical closed loop, improving the reliability and traceability of grouting reinforcement effect.

[0067] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0068] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0069] Figure 1 This is a flowchart illustrating the method in this invention;

[0070] Figure 2 This is a refined test and evaluation diagram of the physical and structural characteristics of soft coal and rock in the grouting reinforcement design method of the present invention.

[0071] Figure 3 This is a diagram of a multi-dimensional quantitative characterization and evaluation index system for the comprehensive performance of grouting materials in the method of this invention.

[0072] Figure 4 This diagram illustrates the method for determining the threshold values ​​of grouting reinforcement materials that accurately match the physical properties and structural characteristics of soft coal and rock, as described in this invention. Detailed Implementation

[0073] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0074] like Figure 1 As shown: This invention is a design method for high-performance grouting materials that accurately match the physical properties and structure of soft coal and rock, comprising the following steps:

[0075] S1: Analysis of target coal and rock physical properties: Multi-dimensional tests are conducted on the soft coal and rock mass to be reinforced to obtain mineral composition characteristics, permeability characteristics, fracture distribution characteristics, strength characteristics, wetting characteristics and hydrophysical characteristics;

[0076] S2: Performance threshold mapping: Based on the physical property parameters obtained in S1, establish a physical property-performance mapping relationship and determine the threshold of key performance indicators for grouting materials;

[0077] S3: Establishment of a multi-source grouting material database: Establish a grouting reinforcement material database that includes material sub-libraries, performance sub-libraries, and case sub-libraries;

[0078] S4: Intelligent Database Retrieval: Retrieve the case sub-library of the pre-built grouting reinforcement material database. If there is an engineering case with matching physical property characteristics, select the corresponding grouting material mix ratio scheme; otherwise, proceed to S5.

[0079] S5: Multi-constraint optimization design: Using the performance threshold determined in S2 as boundary conditions, the grouting material ratio parameters are optimized through orthogonal experiments and machine learning algorithms to generate candidate solutions;

[0080] S6: Closed-loop verification feedback: Verify the laboratory performance and field application effect of the candidate solution, and store successful cases in the database case sub-library.

[0081] A specific example is as follows:

[0082] Target coal and rock physical property analysis: Refined testing and evaluation of the physical and structural characteristics of soft coal and rock for grouting reinforcement design

[0083] Different types of soft coal and rock media require targeted grouting reinforcement designs, but currently there is no refined testing and evaluation scheme for the physical and structural characteristics of coal and rock used in grouting reinforcement design. Therefore, this paper considers establishing an evaluation system for the physical and structural characteristics of soft coal and rock for grouting reinforcement design, including mineral composition characteristics, permeability characteristics, fracture distribution characteristics, strength characteristics, wetting characteristics, and hydrophysiological characteristics. By quantifying the characteristic index parameters, this system will provide basic data for the subsequent rational design and optimization of grouting material performance. See details... Figure 2 .

[0084] Mineral composition characteristics: The intensity of diffraction peaks characteristic of mineral crystal structure was measured by X-ray diffraction (XRD) to analyze the mineral composition content; at the same time, the distribution of minerals in micro-areas was analyzed by scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS) to determine the composition and content of coal and petrological minerals.

[0085] Permeability characteristics: The permeability characteristics of coal and rock directly determine whether grout can be injected. By using panoramic digital images of boreholes (macroscopic fractures) and laboratory micro-CT or electron microscopy scanning SEM images (microscopic fractures), combined with borehole water pressure tests, we can classify the permeability level of coal and rock and identify the equivalent fracture opening of coal and rock.

[0086] The specific categories are as follows:

[0087] Extremely low permeability (I): standard permeability coefficient K < 10-6 cm / s, equivalent fracture aperture of coal and rock b < 25 μm;

[0088] Low permeability (II): Standard permeability coefficient 10⁻⁶ ≤ K < 10⁻⁵ cm / s, equivalent fracture aperture of coal and rock 25 μm ≤ b < 50 μm;

[0089] Weak permeability (III): Standard permeability coefficient 10⁻⁵≤K<10⁻⁴cm / s, equivalent fracture aperture of coal and rock 50μm≤b<100μm;

[0090] Medium to strong permeability (IV): standard permeability coefficient 10⁻⁴ ≤ K < 10⁻² cm / s, equivalent fracture aperture of coal and rock 100 μm ≤ b < 500 μm;

[0091] High permeability (V): standard permeability coefficient 10⁻² ≤ K < 100 cm / s, equivalent fracture aperture of coal and rock 500 μm ≤ b < 2500 μm;

[0092] Extremely high permeability (VI): standard permeability coefficient K>100cm / s, equivalent fracture aperture of coal and rock b>2500μm.

[0093] Fracture Distribution Characteristics: The coal and rock fracture network is the main channel for slurry infiltration and diffusion. Digital images of the coal and rock fracture structure were obtained using a borehole panoramic testing method. In-situ data were collected on characteristic parameters such as fracture spacing, orientation (strike, dip), length, density, aperture, and roughness. Generative Adversarial Networks (GANs) or Convolutional Neural Networks (CNNs) were used to learn the statistical distribution patterns of fractures from the collected field data. A random discrete fracture network model was used to generate a random fracture network that conforms to the actual distribution, verifying whether the statistical characteristics of the model match the actual data. Simultaneously, the fracture structure model was dynamically updated and corrected in real time based on field monitoring data (such as water pressure tests).

[0094] Strength characteristics: The strength of coal and rock reinforced by grouting is closely related to the strength of the coal and rock before grouting, the distribution of coal and rock fissures, and the strength of the grout-formed rock mass. When the coal and rock mass is weak, a high-strength grout should be selected; conversely, when the coal and rock mass is strong, the grout strength can be appropriately reduced to decrease the cost of grouting reinforcement. The strength characteristics of coal and rock are mainly obtained through laboratory standard uniaxial compression tests.

[0095] Wetting characteristics: Characterized by the water-rock interface contact angle, specifically classified as follows: ① Wetting phase, where the water-rock interface contact angle is less than 90°, indicating that the injected coal and rock are hydrophilic; ② Non-wetting phase, where the water-rock interface contact angle is greater than or equal to 90°, indicating that the injected coal and rock are hydrophobic.

[0096] Hydrophysical characteristics: characterized by the disintegration resistance index, and specifically classified as follows:

[0097] Weak disintegration (I): The typical mineral composition is a small amount or no clay minerals, and the disintegration resistance index is 70% < Id,2 ≤ 100%.

[0098] Medium disintegration (II): The typical mineral composition is mainly kaolinite and illite, and the disintegration resistance index is 30% < Id,2 ≤ 70%.

[0099] Strong disintegration (III): Typical mineral composition includes montmorillonite clay minerals, with a disintegration resistance index Id,2 ≤ 30%.

[0100] Multi-dimensional quantitative characterization and evaluation of the comprehensive performance of grouting materials

[0101] There are many types of grouting materials available, and the overall performance of the grout is affected by numerous factors. Currently, there is no good evaluation index system in the design of grouting materials and the optimization of grout proportions that can systematically and comprehensively characterize and describe the overall performance of the grout. To address this, a multi-dimensional quantitative evaluation index system for the overall performance of grouting materials is proposed, and a characterization and testing method for the performance parameters of grouting materials integrating multiple modern testing technologies is determined.

[0102] A multi-dimensional quantitative evaluation index system for the comprehensive performance of grouting materials: The comprehensive performance of grouting materials is deconstructed into two major dimensions: permeability characteristics (including 3 primary indicators and 7 secondary indicators) and strength characteristics (including 5 primary indicators and 8 secondary indicators). Specifically, the permeability characteristics of grouting materials include 3 primary evaluation indicators: grout injectability, grout flowability, and grout-rock affinity; the strength characteristics of grouting materials include 5 primary evaluation indicators: grout stability, grout expansion, stone body strength, stone body toughness, and grout-rock bond strength. See details... Figure 3 .

[0103] Each primary indicator is further broken down into the following 15 secondary evaluation indicators:

[0104] Grout injectability includes the fineness of the grouting material, the particle size of the grout flocculation particles, and the critical fracture aperture value for grout injection.

[0105] Slurry flowability: including slurry rheological properties and slurry viscosity over time;

[0106] Magma-rock affinity: including magma-rock static contact angle and magma surface tension;

[0107] Slurry stability: including slurry water separation rate;

[0108] Grout expansion properties: including grout stone formation rate and grout expansion rate;

[0109] Stone strength: includes tensile strength and compressive strength of the stone;

[0110] Stone toughness: including stone elongation;

[0111] Pulp-rock bond strength: including tensile strength of the pulp-rock bond interface and shear strength of the pulp-rock bond interface.

[0112] Characterization and testing methods for comprehensive performance indicators of grouting materials: The specific testing methods for the 15 secondary performance indicators of grouting materials are as follows.

[0113] Fineness of grouting material: Characterized by D95 particle size, and tested using a laser particle size analyzer.

[0114] Particle size of slurry flocculation particles: The particle size of slurry D95 chord was characterized by the test method using a focused beam reflectivity measurement system.

[0115] Critical fracture aperture for grout injection: Characterized by two physical quantities, bmin and bcrit. bmin represents the minimum fracture aperture at which grout cannot be injected at all, and bcrit represents the minimum fracture aperture at which grout can be injected into the fracture without any seepage. The test method uses an in-situ microscopic visualization grouting test to obtain images of the grout seepage microscopic process to determine the bmin and bcrit values.

[0116] Rheological properties of the slurry: These were characterized by three physical quantities: rheological flow pattern, apparent viscosity, and yield stress. A rotational viscometer was used for the testing. The rheological model was analyzed using mathematical regression based on the experimental data, as shown in the following formula:

[0117]

[0118] Where: μ is the dynamic viscosity of the Newtonian fluid, τ0 is the initial yield stress of the Bingham fluid and the Herschel-Bulkley fluid, and μ p Let V be the plastic viscosity of Bingham fluid, V and n be the consistency coefficient and rheological index of Herschel-Bulkley fluid, and γ be the shear rate. The apparent viscosity of Bingham fluid and Herschel-Bulkley fluid can be calculated according to equation (1):

[0119]

[0120] Where: μ v This refers to the apparent viscosity.

[0121] Slurry viscosity-time variation: Characterized by two physical quantities, initial setting time and final setting time, and tested using a Vicat apparatus.

[0122] Static contact angle between magma and rock: Characterized by the contact angle, and tested using a contact angle measuring instrument. The rock surface is cut or polished until smooth, so that the surface roughness does not exceed 0.5 μm, to reduce the influence of surface roughness on the contact angle.

[0123] Slurry surface tension: Surface tension is used for characterization, and the test method is a surface tension meter.

[0124] Slurry water separation rate: The slurry water separation rate is used to characterize the slurry, and the test method is the volumetric method.

[0125] Grout stone formation rate: The grout stone formation rate is used to characterize the grout stone formation rate, and the test method is the volumetric method.

[0126] Slurry expansion rate: The slurry expansion rate is used to characterize the slurry expansion rate, and the test method is the linear dilatometer method.

[0127] Tensile strength of the stone: The tensile strength was used to characterize the stone, and the Brazilian splitting method was used for testing.

[0128] Stone compressive strength: Characterized by uniaxial compressive strength, and the test method is the standard uniaxial compression test.

[0129] Stone toughness: Characterized by elongation, the test method is the standard direct tensile test.

[0130] Tensile strength of the magma-rock bond interface: The interfacial tensile strength is used for characterization, and the standard direct tensile test is adopted for testing.

[0131] Shear strength of the magma-rock bond interface: Characterized by two physical quantities, cohesion and internal friction angle, and tested using the standard direct shear test.

[0132] Performance threshold mapping: Determination of performance index thresholds for grouting reinforcement materials that accurately match the physical and structural characteristics of soft coal and rock.

[0133] For soft coal and rock media with different characteristics, grouting reinforcement materials are required to have different properties. Therefore, it is necessary to establish a mapping relationship between the physical and structural characteristics of soft coal and rock and the performance indicators of grouting materials. Combining theoretical analysis and numerical simulation, the threshold values ​​for the performance indicators of grouting reinforcement materials under given physical and structural characteristics of the soft coal and rock media can be obtained. (See details...) Figure 4 .

[0134] Determination of grout injectability threshold based on coal and rock permeability characteristics: Based on the equivalent fracture aperture b value of coal and rock obtained from the coal and rock permeability characteristics assessment, the critical fracture aperture value for grout injection should satisfy bcrit≤b; based on this condition, the fineness threshold of grouting material and the particle size threshold of grout flocculation particles are further determined.

[0135] Determination of slurry flowability threshold based on coal and rock fracture distribution characteristics: Based on the distribution characteristics of coal and rock fractures and combined with numerical simulation technology such as COMSOL, the slurry penetration and diffusion range under the influence of different slurry rheological properties (rheological flow pattern, apparent viscosity and yield stress) and slurry viscosity time-varying properties (initial setting time and final setting time) are determined. Finally, the slurry flowability threshold is comprehensively determined in combination with actual engineering construction conditions.

[0136] Determination of the strength and toughness of the grout body and the threshold of grout-rock bond strength based on the distribution and strength characteristics of coal and rock fissures: According to the distribution and strength characteristics of coal and rock fissures, numerical simulation techniques such as FLAC / UDEC / 3DEC are used to analyze the degree of deformation and failure of the surrounding rock and the stability level under the influence of different performance parameters such as the strength and toughness of the grout body and the grout-rock bond strength. Finally, combined with the actual engineering requirements, thresholds for the strength and toughness of the grout body and the grout-rock bond strength that meet the requirements for surrounding rock stability control are proposed.

[0137] Thresholds for slurry stability and slurry expansion based on the characteristics of coal and rock mineral composition and hydrophysical properties are determined as follows: For weakly disintegrating coal and rock, the slurry water separation rate threshold should be controlled to not exceed 10%; for moderately or strongly disintegrating coal and rock, the slurry water separation rate should be controlled to not exceed 5%; the slurry expansion rate should be able to offset the effect of slurry water separation shrinkage and ensure that the slurry stone formation rate is greater than 100%; at the same time, the slurry expansion rate should match the aforementioned slurry-rock bonding strength, and the higher the slurry-rock bonding strength, the greater the expansion rate should be.

[0138] Based on the wetting characteristics and hydrophysiological characteristics of coal and rock, the threshold for magma-rock affinity index is determined as follows: for hydrophilic soft rocks (wetting phase) that are in a state of moderate or strong disintegration, the static contact angle between magma and rock should be controlled to be greater than 120°; in other cases, the static contact angle between magma and rock should be controlled to be less than 60°.

[0139] Establish a database of grouting reinforcement materials for soft coal and rock.

[0140] Utilizing the multi-dimensional quantitative characterization and evaluation method for the comprehensive performance of grouting materials, the performance of various existing grouting materials is tested and analyzed, and a "Grouting Reinforcement Material Database" is established. This database can significantly improve the efficiency of material research and development and the effectiveness of engineering applications. The grouting reinforcement material database mainly includes material sub-libraries, performance sub-libraries, and case study libraries.

[0141] Materials Sub-library: Mainly used to store basic information of various cementitious materials and admixtures used for grouting reinforcement, including material name, material composition, material fineness, production process, toxicity, flammability, pollution, storage conditions, and functional uses.

[0142] The performance sub-library is primarily used for systematically storing comprehensive performance data of grouting materials, including 21 indicators such as grouting material name, material ratio, process parameters, grout flocculation particle size, critical fracture aperture value for grout injection, grout rheological pattern, apparent viscosity, yield stress, initial setting time, final setting time, grout-rock static contact angle, grout surface tension, grout water separation rate, grout stone formation rate, grout expansion rate, tensile strength of the stone body, compressive strength of the stone body, elongation of the stone body, tensile strength of the grout-rock interface, cohesion of the grout-rock interface, and internal friction angle of the grout-rock interface. These indicators have all been standardized and quantified according to the performance parameter characterization and testing methods for grouting materials.

[0143] Case Study Sub-library: Primarily used to correlate engineering geological conditions with the application effects of grouting materials. Stored information includes: case location, coal and rock mineral composition characteristics, permeability characteristics, fracture distribution characteristics, strength characteristics, wetting characteristics, hydrophysical characteristics, grouting material mix proportions, construction process parameters, and on-site application effect evaluation. Before optimizing the performance design of grouting materials for a specific grouting reinforcement project, the case study sub-library should be searched first. If identical or similar cases are found, they can be directly applied to the project, reducing the development time and repetitive research work for grouting materials.

[0144] Optimization Design of Grouting Reinforcement Material Performance under Multi-Objective Threshold Constraints

[0145] Due to the inherent contradictions among different properties of grouting materials, such as the contradiction between strength and fluidity (i.e., high-fluidity grout has low strength, and high-strength grout has poor fluidity), it is necessary to optimize the grouting reinforcement material to its optimal performance while meeting the aforementioned performance threshold constraints. This can be achieved by changing the material mix ratio or process parameters, combined with orthogonal experiments and artificial intelligence prediction models. The specific method is as follows:

[0146] Factor analysis and orthogonal experiment: Determine the key influencing factors and their level ranges that affect the performance of grouting reinforcement materials, including the composition and dosage of gel materials, type and ratio of admixtures, water-cement ratio gradient parameters, grouting process parameters, etc., with no less than 3 gradient levels set for each factor; design a multidimensional orthogonal experimental matrix for laboratory testing and analysis, and systematically record the comprehensive performance data of grout under different ratio schemes.

[0147] Optimization design of grouting reinforcement material performance: Machine learning algorithms were used to train orthogonal experimental data to establish a nonlinear mapping relationship between key influencing factors of grout performance and 15 performance indicators. Based on engineering requirements, optimization objectives for grouting materials were set. Combined with the aforementioned comprehensive performance threshold range of grout (4.1-4.5), multi-objective optimization was performed using generative adversarial networks (GAN) and response surface methodology to generate candidate mix proportions that meet the comprehensive performance threshold range.

[0148] Optimization scheme verification and selection: The performance indicators of candidate schemes are verified through laboratory testing, and the optimal ratio scheme that meets the actual needs of the project is selected.

[0149] On-site application effect feedback verification

[0150] Field tests were conducted using the selected optimal grouting material mix design. A detailed evaluation of the field grouting reinforcement effect was carried out (including grout diffusion range, rock mass strength, surrounding rock deformation, etc.). The compatibility of the grouting reinforcement material performance with the actual coal and rock physical properties and structural characteristics and engineering requirements was verified. Finally, the grouting case was saved to the case sub-library of the grouting reinforcement material database to provide a reference for the design of grouting materials in subsequent projects.

[0151] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A design method for high-performance grouting materials that precisely match the physical properties and structure of soft coal and rock, characterized in that, Includes the following steps: S1: Analysis of target coal and rock physical properties: Multi-dimensional tests are conducted on the soft coal and rock mass to be reinforced to obtain mineral composition characteristics, permeability characteristics, fracture distribution characteristics, strength characteristics, wetting characteristics and hydrophysical characteristics; S2: Performance threshold mapping: Based on the physical property parameters obtained in S1, establish a physical property-performance mapping relationship and determine the threshold of key performance indicators for grouting materials; S3: Establishment of a multi-source grouting material database: Establish a grouting reinforcement material database that includes material sub-libraries, performance sub-libraries, and case sub-libraries; S4: Intelligent Database Retrieval: Retrieve the case sub-library of the pre-built grouting reinforcement material database. If there is an engineering case with matching physical property characteristics, select the corresponding grouting material mix ratio scheme; otherwise, proceed to S5. S5: Multi-constraint optimization design: Using the performance threshold determined in S2 as boundary conditions, the grouting material ratio parameters are optimized through orthogonal experiments and machine learning algorithms to generate candidate solutions; S6: Closed-loop verification feedback: Verify the laboratory performance and field application effect of the candidate solution, and store successful cases in the database case sub-library.

2. The design method for high-performance grouting materials that precisely match the physical properties and structure of soft coal and rock according to claim 1, characterized in that, The specific method for conducting multi-dimensional testing of the soft coal rock mass to be reinforced in step S1 is as follows: Mineral composition characteristics: The content and distribution of mineral components were analyzed using XRD and SEM-EDS techniques; Permeability characteristics: The permeability level is classified into six levels using panoramic digital images of the borehole, micro-CT or SEM images, and borehole water pressure tests; Fractured distribution characteristics: Digital images of fracture structures are obtained through borehole panoramic testing, and the statistical distribution patterns of fractures are learned using GAN or CNN. Strength characteristics: obtained through laboratory standard uniaxial compression tests; Wetting characteristics: characterized by the contact angle of the water-rock interface; Hydrophysical characteristics: characterized by the disintegration resistance index.

3. The design method for high-performance grouting materials that precisely match the physical properties and structure of soft coal and rock according to claim 1, characterized in that, Step S2 specifically includes: Based on the permeability characteristics, the threshold value for the critical fracture aperture value that the grout can be injected is determined; Based on the characteristics of crack distribution, the threshold values ​​for slurry fluidity indicators are determined. Based on the characteristics of fracture distribution and strength, the threshold values ​​of stone body strength, stone body toughness and magma-rock bond strength were determined through numerical simulation. Based on mineral composition and hydrophysical characteristics, thresholds for slurry stability and slurry swelling were determined. Based on wetting and hydrophysiological characteristics, the threshold for magma-rock affinity was determined.

4. The design method for high-performance grouting materials that precisely match the physical properties and structure of soft coal and rock according to claim 3, characterized in that, The rules for performance threshold mapping in step S2 include the following: Permeability matching: The critical fracture aperture into which the grout can be injected is ≤ the equivalent fracture aperture of the coal and rock; Crack distribution matching: Simulate the slurry penetration and diffusion range based on the crack network to limit rheological properties and setting time; Hydraulic characteristics matching: weakly disintegrated coal and rock have a water outflow rate ≤10%, medium / strongly disintegrated coal and rock have a water outflow rate ≤5%, and the expansion rate offsets the shrinkage and is positively correlated with the bond strength; Wetting characteristics matching: contact angle of hydrophilic coal and rock <60°, contact angle of medium / strong disintegration hydrophobic coal and rock >120°.

5. The design method for high-performance grouting materials that precisely match the physical properties and structure of soft coal and rock according to claim 1, characterized in that, Step S3 includes: adopting a multi-dimensional quantitative evaluation index system for the comprehensive performance of grouting materials, deconstructing the comprehensive performance of grouting materials into a two-dimensional evaluation system that includes permeability characteristics and strength characteristics, testing and analyzing the performance of grouting materials based on the performance parameter characterization test method that integrates multiple modern testing technologies, and establishing a grouting reinforcement material database based on the data obtained from the test analysis.

6. The design method for high-performance grouting materials that precisely match the physical properties and structure of soft coal and rock according to claim 5, characterized in that, The dual-dimensional evaluation system specifically includes the following indicators: Permeability characteristics: fineness of grouting material, particle size of grout flocculation particles, critical fracture aperture value for grout injection, rheological properties of grout, time-varying viscosity of grout, static contact angle between grout and rock, and surface tension of grout; Strength characteristics: grout water separation rate, grout stone formation rate, grout expansion rate, tensile strength of stone body, compressive strength of stone body, toughness of stone body, tensile strength of grout-rock bonding interface, and shear strength of grout-rock bonding interface.

7. The design method for high-performance grouting materials that precisely match the physical properties and structure of soft coal and rock according to claim 6, characterized in that, The grouting reinforcement material database: Materials Sub-library: Used to store basic material information for various cementitious materials and admixtures used in grouting reinforcement; Performance Sub-library: Stores data on 21 performance indicators, including permeability and strength characteristics, obtained through standardized testing methods under various grouting material ratio schemes; Case study sub-library: used to store engineering geological conditions, corresponding physical property parameters, grouting material ratios used, and on-site application effects.

8. The design method for high-performance grouting materials that precisely match the physical properties and structure of soft coal and rock according to claim 6, characterized in that, The performance parameter characterization and testing methods for the grouting material are as follows: Grouting material fineness: determined using a laser particle size analyzer; Particle size of slurry flocculation: measured using a focused beam reflectivity measurement system; Critical fracture aperture value for grout injection: In-situ microscopic visualization grouting test was used; Slurry rheological properties: Regression analysis was performed using a rotational viscometer combined with Newton, Bingham, or Herschel-Barclay rheological models; Slurry viscosity-time degradation: Vicat apparatus was used; Static contact angle between magma and rock: measured using a contact angle measuring instrument; Slurry surface tension: Surface tension meter was used; Slurry water separation rate and stone formation rate: volumetric method was used; Slurry expansion rate: determined using a linear dilatometer method; Tensile strength of the stone: determined using the Brazilian splitting method; Stone compressive strength: tested using a standard uniaxial compression test; Stone body elongation: Standard direct tensile test was used; Tensile strength of the magma-rock bond interface: tested using the standard direct tensile test; Shear strength of the magma-rock bond interface: Standard direct shear test was used.

9. The design method for high-performance grouting materials that precisely match the physical properties and structure of soft coal and rock according to claim 8, characterized in that, In the aforementioned method for testing the rheological properties of slurry, the specific rheological model is analyzed using mathematical regression based on the experimental data using the following formula: Where: μ is the dynamic viscosity of the Newtonian fluid, τ0 is the initial yield stress of the Bingham fluid and the Herschel-Bulkley fluid, and μ p Let V be the plastic viscosity of Bingham fluid, and n be the consistency coefficient and rheological index of Herschel-Bulkley fluid, respectively. γ is the shear rate. The apparent viscosity of Bingham fluid and Herschel-Bulkley fluid can be calculated using the above formula: Where: μ v This refers to the apparent viscosity.

10. The design method for high-performance grouting materials that precisely match the physical properties and structure of soft coal and rock according to claim 1, characterized in that, Step S5 specifically includes the following steps: Factor analysis and orthogonal experiment: Identify key influencing factors and their level ranges, and design a multidimensional orthogonal experiment matrix; Optimization design of grouting reinforcement material performance: nonlinear mapping relationship is established by machine learning algorithm, and multi-objective optimization is performed by GAN and response surface methodology; Optimization scheme verification and selection: Verify the performance indicators of candidate schemes through laboratory testing, and select the optimal ratio scheme.

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