Sensitivity analysis method and system for factors affecting water redistribution in the vadose zone of subsidence areas

Abstract

The present invention discloses a sensitivity analysis method and system for factors affecting the redistribution of moisture in the vadose zone of a subsidence area, and relates to the technical field of water resource protection and utilization in ecologically fragile mining areas in Northwest China. The method comprises the steps of: conducting a soil-water characteristic curve test under a disturbance stress path in a coal mining subsidence subsidence area; obtaining a VG soil-water characteristic curve model suitable for the coal mining subsidence subsidence area; determining the redistribution of moisture in the vadose zone of the subsidence area under various working conditions characterized by saturation; performing a sensitivity analysis on the main influencing factors affecting the redistribution of moisture in the vadose zone of the subsidence area under coal mining subsidence disturbance based on the range analysis method and the multivariate linear regression analysis method, and ranking the sensitivity of the main influencing factors. The present invention can calculate the accurate law of moisture redistribution in the vadose zone of a coal mining subsidence subsidence area, and rationally analyze the sensitivity of factors affecting moisture redistribution in the vadose zone, thus providing an important theoretical basis for achieving rapid repair of coal mining subsidence subsidence areas.

Description

Technical Field

[0001] The present invention relates to the technical field of water resource protection and utilization in ecologically fragile mining areas in northwest China, and in particular to a sensitivity analysis method and system for factors affecting water redistribution in aeration zones of subsidence areas. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] The ecological and geological environment of the arid and semi-arid regions of Northwest China is fragile, and water resources are scarce. The vadose zone, the sole water transport medium between surface water, groundwater, and vegetation in these regions, directly controls its water dynamics. Large-scale coal mining causes surface subsidence, creating fractured and subsided areas. This redistributes water from the vadose zone, potentially leading to ecological and geological environmental problems such as vegetation dieback, desertification, and a drop in water levels. Subsided areas account for approximately 65%-85% of the total area of the mining-induced subsidence zone (fractured and subsided areas combined). Accurately determining the primary factors influencing water redistribution in the vadose zone under coal mining disturbance is a key issue in the subsequent ecological restoration of mining-induced subsidence areas. This research has important scientific and practical implications for revealing the competitive mechanisms between dominant flow and matrix flow in the vadose zone fractures and the degradation thresholds of soil physical properties. This research can guide the optimization of ecological restoration technologies in mining areas, provide early warning of secondary disaster risks in mining areas, and improve the comprehensive utilization efficiency of water resources.

[0004] The redistribution of moisture in the vadose zone of the subsidence area disturbed by coal mining collapse is affected by multiple factors. It is difficult to take into account the influence of all factors in the subsequent simulation of moisture recovery in the vadose zone. Therefore, it is necessary to screen out the main factors affecting the redistribution of moisture in the vadose zone of the subsidence area disturbed by coal mining collapse. The main factors affecting the redistribution of moisture in the vadose zone of the subsidence area disturbed by coal mining collapse are different in different mining areas, and there is no unified consensus on them. Based on this, it is difficult to study the redistribution of moisture in the vadose zone of the subsidence area disturbed by coal mining collapse. It is often found that the moisture redistribution in the vadose zone of the subsidence area disturbed by coal mining collapse in theoretical research is inconsistent with the actual situation, which cannot guide the ecological geological environment protection and green mine construction in mining areas. At present, the hierarchical analysis method is often used to analyze the moisture redistribution in the vadose zone of the subsidence area disturbed by coal mining collapse based on field monitoring data. Although the above research has achieved relatively rich research results and to a certain extent obtained the main factors affecting the moisture redistribution in the vadose zone of the subsidence area disturbed by coal mining collapse. However, there are still the following shortcomings:

[0005] (1) Field monitoring of moisture in the vadose zone of coal mining subsidence areas takes a long time, is labor-intensive, and is costly, but the amount of data is small, making it impossible to simultaneously study the redistribution of moisture in the vadose zone of coal mining subsidence areas under the influence of multiple factors.

[0006] (2) Existing sensitivity analyses of factors affecting the redistribution of moisture in the vadose zone of the subsidence area caused by coal mining subsidence often fail to consider the randomness of cracks and fail to adopt the VG model applicable to specific mining areas. In addition, the current analytic hierarchy process has shortcomings such as strong subjectivity and poor rationality of weight analysis. Therefore, the sensitivity and weights of the main factors affecting the redistribution of moisture in the vadose zone of the subsidence area caused by coal mining subsidence are often not accurate enough.

[0007] In summary, how to achieve an objective and reasonable sensitivity analysis of various influencing factors of water redistribution in the vadose zone of the subsidence area under coal mining subsidence disturbance, make it applicable to the VG model, and provide a theoretical basis for guiding the ecological and geological environment protection of the mining area and the construction of green mines has become a technical problem that needs to be solved urgently in the existing technology. Summary of the Invention

[0008] In view of the shortcomings of the existing technology, the purpose of the present invention is to provide a sensitivity analysis method and system for factors affecting the redistribution of moisture in the vadose zone of the subsidence area, which can calculate the accurate law of moisture redistribution in the vadose zone of the coal mining subsidence subsidence area, and reasonably analyze the sensitivity of factors affecting the moisture redistribution in the vadose zone of the subsidence area under the disturbance of coal mining subsidence, providing an important theoretical basis for the rapid repair of the coal mining subsidence subsidence area.

[0009] In order to achieve the above object, the present invention is implemented through the following technical solutions:

[0010] A first aspect of the present invention provides a sensitivity analysis method for factors affecting water redistribution in aeration zones of a settlement area, comprising the following steps:

[0011] Conduct soil-water characteristic curve tests under disturbance stress paths in coal mining subsidence areas;

[0012] Obtain the VG soil-water characteristic curve model applicable to the coal mining subsidence area;

[0013] Determine the redistribution of water in the vadose zone of the subsidence area under various mining subsidence disturbances characterized by saturation;

[0014] Based on the range analysis method and multiple linear regression analysis method, a sensitivity analysis of the main influencing factors affecting the redistribution of moisture in the vadose zone of the subsidence area caused by coal mining subsidence was carried out, and the sensitivity of each main influencing factor was ranked.

[0015] Furthermore, the specific steps for conducting soil-water characteristic curve tests under the disturbance stress path in coal mining subsidence areas are as follows:

[0016] Determine the boundary range of coal mining subsidence area based on probability integral method;

[0017] Carry out in-situ random sampling of the coal mining subsidence area according to the determined boundary range;

[0018] Determine the disturbance stress path in coal mining subsidence areas;

[0019] Based on random sampling, soil-water characteristic curve tests were carried out under disturbance stress paths in coal mining subsidence areas.

[0020] Furthermore, the specific steps for determining the disturbance stress path in the coal mining subsidence area are as follows:

[0021] Based on the measured values of soil collapse and movement deformation caused by mining, the principal stress distribution in the coal mining subsidence zone was analyzed in combination with the elastic-plastic theory, and the disturbance stress path in the coal mining subsidence zone was determined. Among them, the stress states in the process of obtaining the disturbance stress path in the coal mining subsidence zone were as follows: triaxial isostatic compression to the original horizontal stress state, continuing to increase the axial compression to the original rock stress state, increasing the confining pressure until the sample is about to fail, and unloading the confining pressure in stages until creep reaches the original stress state.

[0022] Furthermore, the specific steps to determine the redistribution of water in the vadose zone of the subsidence area under coal mining subsidence disturbance characterized by saturation are as follows:

[0023] Based on the VG soil-water characteristic curve model, the main influencing factors and value ranges affecting the redistribution of water in the vadose zone of the subsidence area under coal mining subsidence disturbance were determined, and an orthogonal experimental design was carried out.

[0024] Write random crack code based on orthogonal test conditions;

[0025] The random crack code and VG model were imported into COMSOL, and the values of the main influencing factors under each working condition were input into COMSOL for numerical simulation;

[0026] By arranging multiple monitoring lines in the numerical simulation to obtain the saturation of their monitoring lines, the average saturation of each monitoring line is taken as the saturation at the current depth, so as to determine the moisture redistribution of the vadose zone in the subsidence area under coal mining subsidence disturbance under various working conditions.

[0027] Furthermore, due to the interaction between the stratigraphic structure, hydrogeological conditions and mining conditions in the mining area, the soil type, porosity, number of cracks, permeability coefficient of the vadose zone, permeability coefficient of the cracks and coal seam mining thickness were selected as the main influencing factors of water redistribution in the vadose zone in the subsidence area under coal mining subsidence disturbance.

[0028] Furthermore, based on the range analysis method and the multiple linear regression analysis method, the specific steps of the sensitivity analysis of the main influencing factors affecting the redistribution of water in the vadose zone of the subsidence area under coal mining subsidence disturbance are as follows:

[0029] Multivariate linear analysis was conducted on the average saturation of representative monitoring lines and the values of the main influencing factors under various working conditions;

[0030] The average saturation of representative monitoring lines and the values of main influencing factors under various working conditions are analyzed for range;

[0031] The results of range analysis and multivariate linear regression analysis were comprehensively considered to conduct sensitivity analysis of the main influencing factors affecting the redistribution of moisture in the vadose zone under coal mining subsidence disturbance, and finally the sensitivity ranking of the main influencing factors was obtained.

[0032] Furthermore, based on the sensitivity analysis results of each major factor, the AHP method based on multiple linear regression and range analysis was used to determine the weight of each major influencing factor, and the sensitivity analysis ranking of each major influencing factor was verified.

[0033] A second aspect of the present invention provides a sensitivity analysis system for factors affecting water redistribution in aeration zones of a settlement area, comprising:

[0034] The test module is configured to carry out soil-water characteristic curve tests under the disturbance stress path in coal mining subsidence areas;

[0035] A model building module is configured to obtain a VG soil-water characteristic curve model applicable to the coal mining subsidence area;

[0036] A distribution determination module is configured to determine the redistribution of moisture in the vadose zone of the subsidence area under the disturbance of coal mining subsidence under various working conditions characterized by saturation;

[0037] The influencing factor sensitivity analysis module is configured to conduct sensitivity analysis on the main influencing factors affecting the redistribution of moisture in the aeration zone of the subsidence area caused by coal mining based on the range analysis method and the multivariate linear regression analysis method, and to rank the sensitivity of each main influencing factor.

[0038] A third aspect of the present invention provides a medium having a program stored thereon, which, when executed by a processor, implements the steps of the sensitivity analysis method for factors affecting moisture redistribution in the aeration zone of a settlement area as described in the first aspect of the present invention.

[0039] The fourth aspect of the present invention provides a device comprising a memory, a processor, and a program stored in the memory and runnable on the processor. When the processor executes the program, the steps in the sensitivity analysis method for factors affecting moisture redistribution in the aeration zone of the sedimentation area as described in the first aspect of the present invention are implemented.

[0040] One or more of the above technical solutions have the following beneficial effects:

[0041] The present invention discloses a sensitivity analysis method and system for factors affecting moisture redistribution in the vadose zone of a subsidence area. This method overcomes the shortcomings of field monitoring of moisture in the vadose zone of a subsidence area caused by coal mining, such as long time, heavy workload, high cost, small data volume, and inability to simultaneously study the redistribution of moisture in the vadose zone under the influence of multiple factors. By considering the randomness of cracks in numerical simulations and adopting a VG model suitable for specific mining areas, and using an AHP hierarchical analysis method based on multivariate linear analysis and range analysis, the method overcomes shortcomings such as excessive subjectivity and poor rationality of weight analysis. The method can accurately determine the main factors affecting moisture redistribution in the vadose zone of a subsidence area caused by coal mining, as well as their sensitivity and weights.

[0042] Advantages of additional aspects of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0044] Figure 1 Flow chart of the sensitivity analysis method of factors affecting water redistribution in the vadose zone of the settlement area in Example 1 of the present invention;

[0045] Figure 2 This is a schematic diagram of the coal mining subsidence settlement area and coal mining subsidence crack area involved in Example 1 of the present invention. DETAILED DESCRIPTION

[0046] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present invention belongs.

[0047] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or their combinations;

[0048] Example 1:

[0049] The first embodiment of the present invention provides a sensitivity analysis method for factors affecting the redistribution of water in the aeration zone of a settlement area, such as Figure 1As shown in the figure, the method includes the following steps: first, based on the probability integral method and the "Code for Prevention and Control of Coal Mining Subsidence" (GB 51023-2014), the boundary range of the coal mining subsidence zone is comprehensively determined, and then the in-situ random sampling of the coal mining subsidence zone is carried out; the disturbance stress path of the coal mining subsidence zone is determined, and the soil-water characteristic curve test under the disturbance stress path of the coal mining subsidence zone is carried out to obtain the VG soil-water characteristic curve model suitable for the coal mining subsidence zone; at the same time, the main factors affecting the redistribution of water in the vadose zone of the subsidence zone under the disturbance of coal mining subsidence and the value range are determined, based on which, the orthogonal experimental design is carried out; the random crack code is written based on MATLAB, and the random crack code and VG are combined. The model was imported into COMSOL, and the redistribution of moisture in the vadose zone of the subsidence area under coal mining disturbance, characterized by saturation, was determined based on COMSOL numerical simulation. A sensitivity analysis of the main factors affecting the redistribution of moisture in the vadose zone of the subsidence area under coal mining subsidence disturbance was performed based on the range analysis method and the multiple linear regression analysis method. The sensitivity ranking of the main influencing factors of the redistribution of moisture in the vadose zone of the subsidence area under coal mining subsidence disturbance was determined, and the weight of each main influencing factor was determined using the hierarchical analysis AHP method based on multiple linear regression and range analysis in combination with the sensitivity analysis results. This embodiment has important scientific research significance and application value for studying the law of moisture redistribution in the vadose zone of the subsidence area under coal mining subsidence disturbance, accurately determining the sensitivity of the factors affecting the redistribution of moisture in the vadose zone of the subsidence area under coal mining subsidence disturbance, and realizing the rapid repair of coal mining subsidence subsidence areas.

[0050] The specific steps include:

[0051] Step 1: Conduct soil-water characteristic curve tests under disturbance stress paths in coal mining subsidence areas.

[0052] Step 1.1: Determine the boundary of the coal mining subsidence area based on the probability integral method.

[0053] Step 1.1.1: Establish a probability integral model to determine the boundary range of the coal mining subsidence area.

[0054] Take a unit i mined in an inclined coal seam. According to the basic principle of the probability integral method, the final value of the subsidence of any point (x, y) on the surface caused by the unit mining is:

[0055] (1).

[0056] in, is the final value of the subsidence of any point (x, y) on the surface, r is the main impact radius, ; H0 is the average mining depth; β is the main influencing angle; , i is the number of a mining unit, H1 is the plane coordinate of the mining unit i to the center point of the i-th unit (x i , y i) is the vertical distance, θ is the maximum sinking angle; (x i , y i ) is the plane coordinate of the center point of the i-th unit; (x, y) is the coordinate of any point on the surface.

[0057] Step 1.1.2: Based on the actual observation experience parameters accumulated over a long period of time in similar mining areas and combined with actual coal mining, determine the parameter values in the probability integral model that affect the boundary range of the coal mining subsidence area.

[0058] Step 1.1.3: Based on the probability integral model, determine the boundary range of the coal mining subsidence area, and combine the settlement boundary demarcation standards in the "Code for Prevention and Control of Coal Mining Subsidence" (GB 51023-2014) to determine the coal mining subsidence area and coal mining crack area, such as Figure 2 shown.

[0059] Step 1.2: Carry out in-situ random sampling of the coal mining subsidence area according to the determined boundary range.

[0060] In this embodiment, after determining the boundary range, in-situ random sampling is performed in the coal mining subsidence area, and a total of 3 random sampling points are selected.

[0061] Step 1.3: Determine the disturbance stress path in the coal mining subsidence area.

[0062] In this embodiment, based on the measured values of the collapse and movement deformation of the mining soil, the principal stress distribution in the coal mining subsidence settlement area is analyzed in combination with the elastic-plastic theory, and the disturbance stress path of the coal mining subsidence settlement area is determined. Among them, the stress state in the process of obtaining the disturbance stress path of the coal mining subsidence settlement area is sequentially passed through: triaxial isostatic pressure to the original horizontal stress state, continuing to increase the axial pressure to the original rock stress state, increasing the confining pressure until the sample is about to fail, and unloading the confining pressure in stages until creep to the original stress state.

[0063] Step 1.4: Conduct soil-water characteristic curve tests under the disturbance stress path in the coal mining subsidence area based on random sampling.

[0064] Step 1.4.1: After preparing the sample according to the instrument size and saturating the sample, carry out the sample dehumidification process under the disturbance stress path of the coal mining subsidence settlement area until the residual moisture content of the sample is reached.

[0065] Step 1.4.2: Record the water content data at each matrix suction.

[0066] Step 2: Obtain the VG soil-water characteristic curve model applicable to the coal mining subsidence area.

[0067] Specifically, based on the moisture content data at various matrix suctions recorded during the soil-water characteristic curve test under the disturbed stress path in the coal mining subsidence settlement area, the VG soil-water characteristic curve model applicable to the coal mining subsidence settlement area was fitted using the Origin data processing software.

[0068] The Van Genuchten (VG) model is one of the most commonly used models in soil moisture characteristic curves. It describes the functional relationship between soil matrix suction and volumetric water content through a mathematical equation and is widely used in research areas such as soil water transport, soil salinization, and slope stability.

[0069] Step 3: Determine the water redistribution in the aeration zone of the subsidence area under coal mining subsidence disturbance under various working conditions characterized by saturation.

[0070] Step 3.1: Based on the VG soil-water characteristic curve model, determine the main influencing factors and value ranges that affect the redistribution of water in the vadose zone of the subsidence area disturbed by coal mining, and carry out orthogonal experimental design.

[0071] Step 3.1.1: The factors affecting the redistribution of moisture in the vadose zone of the subsidence area caused by coal mining subsidence are relatively complex. Due to the interaction between the mining area's stratigraphic structure, hydrogeological conditions, and mining conditions, the soil type, porosity, number of cracks, permeability coefficient of the vadose zone, permeability coefficient of cracks, and coal seam mining thickness are selected as the main influencing factors of moisture redistribution in the vadose zone of the subsidence area caused by coal mining subsidence.

[0072] Based on the data of field measurement, numerical simulation, indoor test, etc., the value range of each major influencing factor is determined, and the value range of each factor is set according to 、 、 、 Sort by i=1, 2, 3, 4, 5, 6; Indicates the minimum value in the range of a factor; Indicates the maximum value in the value range of a factor.

[0073] Step 3.1.2: Select the orthogonal array based on the determined main influencing factors.

[0074] Orthogonal experiment is a scientific experimental design method based on orthogonal tables. It aims to efficiently analyze the impact of multiple factors on the results and find the optimal combination through a small number of representative experiments. It has the characteristics of efficiency, balance and analyzability. It can achieve a uniform combination of factor levels while significantly reducing the number of experiments, avoiding data bias, and distinguishing main effects from interactions to identify key factors. The main tool of orthogonal experimental design is the orthogonal table. The experimenter can find the corresponding orthogonal table based on specific needs such as the number of factors affecting the experiment, the number of levels to be considered under the factors, and whether there is a mutual coupling relationship. Based on its orthogonality, some representative points are selected from the comprehensive experiment to conduct orthogonal experiments, which can achieve the maximum amount of experimental results with the least number of experiments.

[0075] In orthogonal experiments, indicators are the result variables that need to be measured or optimized. They are used to evaluate the effects of different factor combinations, directly reflect the goals of orthogonal experiments, and are the basis for judging the magnitude of factor influence. Independent variables that may affect indicators in the experiment, that is, controllable conditions or parameters that need to be studied, are called factors. The level is the specific value or state set for each factor in the experiment, which is used to explore the influence of the factor on the indicator. L N ( p q ) represents the orthogonal array, where L is the code for the orthogonal array; N is the total number of trials; p is the number of levels of the factors; and q is the number of columns in the orthogonal array, i.e., the maximum number of factors that can be arranged.

[0076] This embodiment conducts an orthogonal test based on the main influencing factors and value ranges of water redistribution in the aeration zone of the subsidence area under coal mining subsidence disturbance. Specifically, according to the orthogonal table design principle, six factors and four levels L are selected. 32 (4 6 ), that is, a total of 32 working conditions.

[0077] Step 3.2: Use MATLAB to write a random crack code based on the orthogonal test conditions.

[0078] In a specific embodiment, a random crack code is written based on MATLAB, which can realize random cracks of a specified number, random position, and a given range of length:

[0079] % ---------- Parameter settings -----------

[0080] numfractures = 100; % number of fractures

[0081] domainSize = [0, 1000, 0, 1600]; % Region range [xmin, xmax, ymin, ymax]

[0082] minLength = 20; % minimum crack length

[0083] maxLength = 180; % Maximum crack length

[0084] % ---------- Initialize graphics window -----------

[0085] figure;

[0086] hold on;

[0087] axis equal; % Keep the horizontal and vertical axis ratios consistent

[0088] axis([0 1000 0 1600]); % Force display of the full area range

[0089] grid on; % Display grid lines

[0090] title('Fissure Distribution Map (X:0-1000, Y:0-1600)');

[0091] xlabel('X axis');

[0092] ylabel('Y axis');

[0093] % ---------- Generate and draw cracks----------

[0094] fractures = zeros(numfractures, 4); % Pre-allocate matrix to store fracture coordinates

[0095] for i = 1:numfractures

[0096] % Randomly generate a starting point (within domainSize)

[0097] x1 = domainSize(1) + (domainSize(2)-domainSize(1)) * rand;

[0098] y1 = domainSize(3) + (domainSize(4)-domainSize(3)) * rand;

[0099] % Randomly generate direction and length

[0100] angle = 2 * pi * rand; % Random angle [0, 2π]

[0101] length = minLength + (maxLength-minLength)*rand; % random length

[0102] % Calculation end point

[0103] x2 = x1 + length * cos(angle);

[0104] y2 = y1 + length * sin(angle);

[0105] % Ensure that the end point does not exceed the region boundary

[0106] x2 = max(min(x2, domainSize(2)), domainSize(1)); % X-axis constraint

[0107] y2 = max(min(y2, domainSize(4)), domainSize(3)); % Y-axis constraint

[0108] % Save the crack coordinates to the matrix

[0109] fractures(i, :) = [x1, y1, x2, y2];

[0110] % Draw the current crack (red line + circle mark endpoints)

[0111] plot([x1, x2], [y1, y2], 'r', 'LineWidth', 1.5, 'MarkerSize', 4);

[0112] end

[0113] hold off.

[0114] Step 3.3: Import the random crack code and VG model into COMSOL, and input the values of the main influencing factors under each working condition into COMSOL for numerical simulation.

[0115] Step 3.4: Arrange multiple monitoring lines in the numerical simulation to obtain their saturation. Take the average saturation of each monitoring line as the saturation at the current depth to determine the water redistribution in the vadose zone of the subsidence area under coal mining subsidence disturbance under various working conditions.

[0116] Water saturation refers to the ratio of the volume of water in the soil to the total pore volume and is generally used to describe the relative saturation of water in the soil. The saturation varies at different depths, and even at the same depth, due to factors such as cracks, pores, and permeability, the saturation can vary. Therefore, this example uses saturation to measure relative water content.

[0117] Step 4: Based on the range analysis method and multiple linear regression analysis method, a sensitivity analysis is conducted on the main influencing factors affecting the redistribution of moisture in the vadose zone of the subsidence area under coal mining subsidence disturbance, and the sensitivity of each main influencing factor is ranked.

[0118] Step 4.1: Based on the range analysis method and multiple linear regression analysis method, sensitivity analysis is conducted on the main influencing factors affecting the redistribution of moisture in the vadose zone of the subsidence area under coal mining subsidence disturbance.

[0119] Step 4.1.1: Perform multivariate linear analysis on the average saturation of representative monitoring lines and the values of the main influencing factors under each working condition.

[0120] In a specific embodiment, a multivariate linear analysis is performed on the average saturation of a representative monitoring line and the values of the main influencing factors under each working condition, and the regression equation is:

[0121] (2).

[0122] Where β0, β1, β2...β6 are constants and correlation coefficients, respectively; Y is the average saturation of a representative monitoring line under each operating condition; and the values of the main influencing factors are X1, X2, X3...X6, respectively. The larger the correlation coefficient between each main influencing factor, the greater the impact of a change in the level of that factor on the test indicator, that is, the greater the sensitivity of the factor. In this embodiment, sensitivity refers to the degree of influence of the main influencing factor. The greater the sensitivity of the main influencing factor, the greater the impact of a change in the level of that factor on the test indicator, that is, the greater the influence of the factor on the water redistribution in the vadose zone of the coal mining subsidence settlement area.

[0123] It should be noted that, generally speaking, since COMSOL numerical simulation software has a built-in monitoring line placement function, an unlimited number of monitoring lines can theoretically be placed. However, the representativeness of the monitoring lines is determined based on the specific regional conditions. Therefore, when analyzing the same region, range analysis and multivariate linear analysis use the same set of monitoring lines. For example, in the aeration zone moisture distribution of mining areas in the arid and semi-arid regions of Northwest China, monitoring lines are generally placed along the x-direction at positions 6.2m, 7m, and 7.8m from the ground surface, and a monitoring line is placed along the y-direction in the middle of the model width. The above monitoring lines serve as representative monitoring lines for the aeration zone moisture distribution of mining areas in the arid and semi-arid regions of Northwest China.

[0124] Step 4.1.2: Perform range analysis on the average saturation of representative monitoring lines and the values of the main influencing factors under each working condition.

[0125] In a specific embodiment, the average saturation of the representative monitoring line and the values of the main influencing factors under each working condition are subjected to range analysis, and the range value R j It is the evaluation standard of the sensitivity of the main influencing factors analyzed by the range method, which is the average saturation E of the representative monitoring line at each level of the factor. ij The difference between the maximum and minimum values of . The calculation formula is:

[0126] (3).

[0127] Where, E mj is the average of the test results of factor j at level m, m=1, 2, 3, 4; j=1, 2, 3, 4, 5, 6.

[0128] Range R j The larger the value is, the greater the impact of the change in the level of the factor on the test index, that is, the greater the sensitivity of the factor; on the contrary, the range R j The smaller it is, the less sensitive the factor is;

[0129] Step 4.1.3: Comprehensively consider the results of range analysis and multivariate linear regression analysis to conduct sensitivity analysis on the main influencing factors affecting the redistribution of moisture in the vadose zone under coal mining subsidence disturbance, and finally obtain the sensitivity ranking of each main influencing factor.

[0130] In this embodiment, a sensitivity analysis ranking is obtained for a monitoring line using the range analysis method. Similarly, a sensitivity analysis ranking is obtained for a monitoring line using the multiple linear regression analysis method. The average value of the cumulative ranking of each influencing factor is statistically calculated to perform a comprehensive ranking.

[0131] For example, four representative monitoring lines were selected. The cumulative ranking of the number of fractures using the range analysis method was assumed to be 1+2+1=4, and the cumulative ranking of the number of fractures using the multivariate linear regression analysis method was assumed to be 2+2+2=6. The average value was (6+4) / 6=3.333. This was used as the ranking value for each influencing factor. A comprehensive ranking was performed based on these ranking values to obtain the sensitivity analysis results of the main factors affecting the redistribution of moisture in the vadose zone under coal mining subsidence. After obtaining the sensitivity ranking, artificial intervention can be used to act on the top few sensitive factors affecting the redistribution of moisture in the vadose zone, thereby promoting ecological restoration and land reclamation in the coal mining subsidence area.

[0132] Step 4.2: Based on the sensitivity analysis results for each major factor, use the Analytic Hierarchy Process (AHP) method, which uses multiple linear regression and range analysis, to determine the weights of each major influencing factor and verify the sensitivity ranking of each major influencing factor. Specifically, the calculated weights can verify the sensitivity ranking, and the two are mutually verified.

[0133] In a specific embodiment, based on the sensitivity analysis results of the main influencing factors obtained by range analysis and multivariate linear analysis, the importance of the main influencing factors of water redistribution in the vadose zone under coal mining subsidence disturbance to the water redistribution in the vadose zone is compared pairwise, that is, two main influencing factors mi and mj are taken each time to Quantitative characterization and The relative importance of water redistribution in the vadose zone of the subsidence area under coal mining subsidence disturbance is expressed in the matrix Indicates that the calculation result retains 3 significant figures, where N is the judgment matrix of the main influencing factors obtained based on the sensitivity analysis results.

[0134] Calculate the maximum eigenvalue of the judgment matrix N And the eigenvector W, and then after normalizing the eigenvector W, the relative weight coefficient of the influencing factors of water redistribution in the aeration zone of the subsidence area under coal mining subsidence disturbance can be obtained; then the consistency ratio of the judgment matrix N is calculated, and the CI value is calculated first:

[0135] .

[0136] The RI is then calculated using the Saaty scaling method, and the consistency ratio (CR) is calculated using the CI / RI ratio. The RI is a random consistency index, which is related to the order of the judgment matrix (if n influencing factors are selected, the order of the judgment matrix is n). Scaling is performed using an existing correspondence table, which is the Saaty scaling method. If the consistency ratio meets the design requirements, the weight coefficient calculated above becomes the final weight of the factors affecting moisture redistribution in the vadose zone of the subsidence area caused by coal mining subsidence disturbance. Otherwise, the judgment matrix is reconstructed.

[0137] The present invention has important scientific research significance and application value in studying the water redistribution law of the vadose zone in the coal mining subsidence settlement area, accurately determining the sensitivity of the factors affecting the water redistribution of the vadose zone in the settlement area under coal mining subsidence disturbance, and realizing the rapid repair of coal mining subsidence areas.

[0138] Example 2:

[0139] A second embodiment of the present invention provides a sensitivity analysis system for factors affecting water redistribution in aeration zones of a settlement area, comprising:

[0140] The test module is configured to carry out soil-water characteristic curve tests under the disturbance stress path in coal mining subsidence areas;

[0141] A model building module is configured to obtain a VG soil-water characteristic curve model applicable to the coal mining subsidence area;

[0142] A distribution determination module is configured to determine the redistribution of moisture in the vadose zone of the subsidence area under the disturbance of coal mining subsidence under various working conditions characterized by saturation;

[0143] The influencing factor sensitivity analysis module is configured to conduct sensitivity analysis on the main influencing factors affecting the redistribution of moisture in the aeration zone of the subsidence area caused by coal mining based on the range analysis method and the multivariate linear regression analysis method, and to rank the sensitivity of each main influencing factor.

[0144] Example 3:

[0145] A third embodiment of the present invention provides a medium having a program stored thereon, which, when executed by a processor, implements the steps of the sensitivity analysis method for factors affecting moisture redistribution in the aeration zone of a settlement area as described in the first embodiment of the present invention.

[0146] Example 4:

[0147] Embodiment 4 of the present invention provides a device, including a memory, a processor, and a program stored in the memory and runnable on the processor. When the processor executes the program, the steps in the sensitivity analysis method of factors affecting moisture redistribution in the aeration zone of the settlement area as described in Embodiment 1 of the present invention are implemented.

[0148] The steps involved in the above embodiments 2, 3 and 4 correspond to those in the method embodiment 1. For the specific implementation methods, please refer to the relevant description part of the embodiment 1.

[0149] Those skilled in the art will appreciate that the modules or steps of the present invention described above can be implemented using a general-purpose computer device. Alternatively, they can be implemented using program code executable by a computing device, which can then be stored in a storage device and executed by the computing device. Alternatively, they can be fabricated into separate integrated circuit modules, or multiple modules or steps can be fabricated into a single integrated circuit module for implementation. The present invention is not limited to any specific combination of hardware and software.

[0150] Although the above describes the specific embodiments of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without any creative work are still within the scope of protection of the present invention.

Claims

1. A sensitivity analysis method for factors affecting water redistribution in the vadose zone of a settlement area, characterized in that: The following steps are involved: Conduct soil-water characteristic curve tests under disturbance stress paths in coal mining subsidence areas; Obtain the VG soil-water characteristic curve model applicable to the coal mining subsidence area; Determine the water redistribution in the aeration zone of the subsidence area under various mining subsidence disturbances characterized by saturation. The specific steps are as follows: Based on the VG soil-water characteristic curve model, the main influencing factors and value ranges affecting the redistribution of water in the vadose zone of the subsidence area under coal mining subsidence disturbance were determined, and an orthogonal experimental design was carried out. Write random crack code based on orthogonal test conditions; The random crack code and VG model were imported into COMSOL, and the values of the main influencing factors under each working condition were input into COMSOL for numerical simulation; By arranging multiple monitoring lines in the numerical simulation to obtain the saturation of each monitoring line, the average saturation of each monitoring line is taken as the saturation at the current depth, so as to determine the water redistribution in the vadose zone of the subsidence area under the disturbance of coal mining collapse in various working conditions. Based on the range analysis method and multiple linear regression analysis method, a sensitivity analysis of the main influencing factors affecting the redistribution of moisture in the vadose zone of the subsidence area caused by coal mining subsidence was carried out, and the sensitivity of each main influencing factor was ranked.

2. The sensitivity analysis method for factors affecting water redistribution in the vadose zone of a settlement area according to claim 1, characterized in that: The specific steps for conducting soil-water characteristic curve tests under disturbance stress paths in coal mining subsidence areas are as follows: Determine the boundary range of coal mining subsidence area based on probability integral method; Carry out in-situ random sampling of the coal mining subsidence area according to the determined boundary range; Determine the disturbance stress path in coal mining subsidence areas; Based on random sampling, soil-water characteristic curve tests were carried out under disturbance stress paths in coal mining subsidence areas.

3. The sensitivity analysis method for factors affecting water redistribution in the vadose zone of a settlement area according to claim 2, characterized in that: The specific steps to determine the disturbance stress path in the coal mining subsidence area are as follows: Based on the measured values of soil collapse and movement deformation caused by mining, the principal stress distribution in the coal mining subsidence zone was analyzed in combination with the elastic-plastic theory, and the disturbance stress path in the coal mining subsidence zone was determined. Among them, the stress states in the process of obtaining the disturbance stress path in the coal mining subsidence zone were as follows: triaxial isostatic compression to the original horizontal stress state, continuing to increase the axial compression to the original rock stress state, increasing the confining pressure until the sample is about to fail, and unloading the confining pressure in stages until creep reaches the original stress state.

4. The sensitivity analysis method for factors affecting water redistribution in the vadose zone of a settlement area according to claim 1, characterized in that: Due to the interaction between the mining area's stratigraphic structure, hydrogeological conditions, and mining conditions, the soil type, porosity, number of cracks, permeability coefficient of the vadose zone, permeability coefficient of the cracks, and coal seam mining thickness were selected as the main influencing factors of moisture redistribution in the vadose zone in the subsidence area under coal mining subsidence disturbance.

5. The sensitivity analysis method for factors affecting water redistribution in the vadose zone of a settlement area according to claim 1, characterized in that: The specific steps of conducting sensitivity analysis on the main influencing factors affecting the redistribution of moisture in the aeration zone of the subsidence area under coal mining subsidence disturbance based on the range analysis method and the multiple linear regression analysis method are as follows: Multivariate linear analysis was conducted on the average saturation of representative monitoring lines and the values of the main influencing factors under various working conditions; The average saturation of representative monitoring lines and the values of main influencing factors under various working conditions are analyzed for range; The results of range analysis and multivariate linear regression analysis were comprehensively considered to conduct sensitivity analysis of the main influencing factors affecting the redistribution of moisture in the vadose zone under coal mining subsidence disturbance, and finally the sensitivity ranking of the main influencing factors was obtained.

6. The sensitivity analysis method for factors affecting water redistribution in the vadose zone of a settlement area according to claim 5, characterized in that: Based on the sensitivity analysis results of each major factor, the weight of each major influencing factor was determined using the AHP method based on multiple linear regression and range analysis, and the sensitivity analysis ranking of each major influencing factor was verified.

7. A sensitivity analysis system for factors affecting water redistribution in the vadose zone of a settlement area, characterized by: include: The test module is configured to carry out soil-water characteristic curve tests under the disturbance stress path in coal mining subsidence areas; A model building module is configured to obtain a VG soil-water characteristic curve model applicable to the coal mining subsidence area; The distribution determination module is configured to determine the redistribution of moisture in the aeration zone of the subsidence area under various working conditions characterized by saturation. The specific steps are as follows: Based on the VG soil-water characteristic curve model, the main influencing factors and value ranges affecting the redistribution of water in the vadose zone of the subsidence area under coal mining subsidence disturbance were determined, and an orthogonal experimental design was carried out. Write random crack code based on orthogonal test conditions; The random crack code and VG model were imported into COMSOL, and the values of the main influencing factors under each working condition were input into COMSOL for numerical simulation; By arranging multiple monitoring lines in the numerical simulation to obtain the saturation of each monitoring line, the average saturation of each monitoring line is taken as the saturation at the current depth, so as to determine the water redistribution in the vadose zone of the subsidence area under the disturbance of coal mining collapse in various working conditions. The influencing factor sensitivity analysis module is configured to conduct sensitivity analysis on the main influencing factors affecting the redistribution of moisture in the aeration zone of the subsidence area caused by coal mining based on the range analysis method and the multivariate linear regression analysis method, and to rank the sensitivity of each main influencing factor.

8. A computer-readable storage medium, characterized in that A plurality of instructions are stored therein, and the instructions are suitable for being loaded by a processor of a terminal device and executing the sensitivity analysis method of factors affecting moisture redistribution in the aeration zone of a settlement area according to any one of claims 1 to 6.

9. A terminal device, characterized in that: It includes a processor and a computer-readable storage medium, the processor is used to implement each instruction; the computer-readable storage medium is used to store multiple instructions, and the instructions are suitable for being loaded by the processor and executing the sensitivity analysis method of factors affecting moisture redistribution in the settlement area aeration zone according to any one of claims 1-6.

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