A method for self-adapting online determination of basic parameters of coal seam

Abstract

This invention discloses an adaptive online measurement method for basic coal seam parameters, belonging to the field of coal seam parameter acquisition technology. The method includes the following steps: Step S1, deploying a multi-parameter sensor array in the coal seam borehole to collect raw gas pressure, temperature, humidity, coal strain, and acoustic emission signals in real time; Step S2, calculating and correcting the gas pressure using a composite environmental compensation model; Step S3, constructing an unsteady diffusion-seepage equation to invert the gas concentration and pressure field; Step S4, performing time-frequency analysis on the acoustic emission signals to calculate the amount of gas released by micro-fractures; Step S5, calculating the dynamic gas content based on the amount of gas released by micro-fractures; Step S6, constructing an objective function to dynamically optimize the parameters in real time. This invention, by collecting and accurately correcting coal seam parameters, can help solve problems in coal seam mining and accelerate the production progress of the working face.

Description

Technical Field

[0001] This invention relates to the field of coal seam parameter acquisition technology, specifically to an adaptive online measurement method for basic coal seam parameters. Background Technology

[0002] Coalbed methane (CBM) is a potentially clean energy source. In the current energy-scarce situation, accelerating its development and utilization is of significant practical importance for improving the energy structure, ensuring full energy utilization, and reducing environmental pollution. The most common coal seam development methods are underground gas extraction and surface drilling. Underground extraction yields relatively small amounts of CBM with low methane concentrations and is easily affected by coal mine operations, so it is primarily aimed at ensuring safe coal mine production, resulting in lower CBM utilization rates. Surface drilling, on the other hand, produces large quantities of gas over long periods with high methane content, thus supporting large-scale commercial utilization. This extraction method allows CBM to be extracted to the surface through wells and utilized like conventional natural gas, truly recognizing it as a mineral resource and classifying it as a mineral resource of significant economic value.

[0003] However, my country's coalfields have complex geological structures, and some coal-bearing basins have undergone significant post-construction alteration, resulting in diverse structural morphologies. The occurrence conditions of coal reservoirs and coalbed methane resources are relatively simple in large and medium-sized basins, but more complex in small and medium-sized basins. This makes coalbed methane management and utilization quite difficult, and many key problems remain unsolved in theoretical and technical research and application. This is because basic research on coalbed methane development and utilization is weak. For example, the mechanism and influencing factors of blowout phenomena during the drilling process of extraction boreholes are not clearly understood, and existing coalbed methane exploration and development technologies cannot adapt to complex geological conditions. In particular, during in-situ coalbed methane extraction, as the gas continuously migrates, the fracture field of the coal seam, as well as the diffusion field and seepage field of the gas migration, will constantly change. Accurately grasping the evolution law of these physical fields is crucial for achieving efficient coalbed methane extraction.

[0004] For example, Chinese Patent CN116381185A discloses a multi-physics field synchronous measurement system and method for in-situ coal seam gas extraction, relating to the field of coal mine gas extraction technology. The specific steps are as follows: sampling and analyzing the coal seam area to be tested to obtain relevant parameters, and determining experimental parameters based on these parameters; building a measurement system for the coal seam area based on the experimental parameters and configuring initial parameters; collecting various data from the measurement system and processing the data to obtain multiple physical field parameters; and constructing a mapping relationship between multiple physical field parameters and coal seams at different burial depths under different geostress conditions. This invention achieves synchronous measurement of multiple physical fields through experimentation, providing a more accurate theoretical basis for coal mine mining.

[0005] Chinese patent CN112145229B discloses a non-contact dynamic continuous measurement system and method for coal seam gas content in coal roadway tunneling faces. This measurement system comprises three main parts: a multi-parameter dynamic acquisition system, a monitoring system, and a gas content calculation system. The multi-parameter dynamic acquisition system acquires parameters such as coal roadway return air gas concentration, roadway cross-sectional area, roadway perimeter, sensor distance from the tunneling head, and face wind speed at the parameter collection points. This data is then transmitted to the gas content calculation system via the monitoring system. The gas content calculation system acquires, processes, and displays the multi-parameter data signals and controls the drive module of the multi-parameter dynamic acquisition system. The corresponding method can perform a comprehensive "point-line-surface-volume" analysis and inversion of the acquired multi-parameter information. This invention can be widely applied to the observation and research of coal seam gas occurrence patterns in coal roadway tunneling faces.

[0006] All of the above patents suffer from the problems mentioned in this background technology: traditional borehole sealing pressure measurement methods require single-point static measurement and cannot capture dynamic changes; existing sensors do not consider the coupling effect of ground stress-temperature-humidity, resulting in insufficient model accuracy; and traditional gas content models have high prediction errors. Summary of the Invention

[0007] The technical problem to be solved by the present invention is to provide an adaptive online method for determining the basic parameters of coal seams, which addresses the shortcomings of the existing technology.

[0008] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0009] An adaptive online method for determining basic parameters of coal seams includes the following steps:

[0010] Step S1: Deploy a multi-parameter sensor array in the coal seam borehole to collect raw gas pressure, temperature, humidity, coal strain and acoustic emission signals in real time;

[0011] Step S2: Calculate the corrected gas pressure using a composite environmental compensation model;

[0012] Step S3: Construct the unsteady diffusion-seepage equation to invert the gas concentration and pressure field;

[0013] Step S4: Perform time-frequency analysis on the acoustic emission signal and calculate the amount of gas released by the micro-rupture;

[0014] Step S5: Calculate the dynamic gas content based on the amount of gas released from micro-fractures;

[0015] Step S6: Construct the objective function and perform dynamic parameter optimization in real time.

[0016] Furthermore, in step S2, the formula for calculating the corrected gas pressure is:

[0017]

[0018] in, This indicates the corrected gas pressure. This indicates the original gas pressure collected. This represents the linear temperature compensation coefficient. This represents the nonlinear temperature compensation coefficient. Indicates real-time temperature. Indicates the reference temperature. Indicates the humidity compensation coefficient. Indicates real-time humidity. Indicates the reference humidity. Represents the stress coupling coefficient. This represents the elastic modulus of the coal. Indicates the strain of the coal body. Indicates the reference stress.

[0019] Furthermore, in the modified gas pressure formula, the compensation coefficient... , and Through orthogonal experimental calibration, under temperature gradients of 15℃, 25℃, and 35℃ and humidity gradients of 30%, 50%, and 70%, the calculation formula is obtained by matrix operations:

[0020]

[0021] in, This represents a 9×3 design matrix, where each row corresponds to one experiment and contains three independent variables: temperature deviation, the square of the temperature deviation, and the humidity deviation. This represents a 9×1 column vector consisting of the compensation bias from 9 experiments, which is the ratio of the actual pressure to the original pressure minus 1.

[0022] Furthermore, in step S3, the specific formula for the unsteady diffusion-seepage equation is as follows:

[0023]

[0024] in, Indicates the free gas molar concentration. Indicates the porosity of the coal seam. Represents a time variable. Indicates the effective diffusion coefficient. Indicates dynamic penetration rate. The second derivative of the gas concentration. Denotes the divergence operator, Indicates the viscosity of methane. The first derivative representing gas pressure, Indicates the density of the coal body. Indicates the amount of gas adsorbed;

[0025] The steps for solving the pressure field are as follows:

[0026] Dynamic permeability, adsorption capacity, and effective diffusion coefficient are calculated using environmental data.

[0027] Solving the unsteady diffusion-seepage equation yields the free gas molar concentration;

[0028] The free gas molar concentration is converted into a pressure field using the ideal gas law.

[0029] Furthermore, in the unsteady diffusion-seepage equation, the formula for calculating the effective diffusion coefficient is:

[0030]

[0031] in, Indicates the baseline diffusivity. Indicates the diffusion activation energy. Represents the gas constant;

[0032] The formula for calculating dynamic permeability is:

[0033]

[0034] in, Indicates permeability under stress-free conditions. Represents the stress sensitivity coefficient. Indicates ground stress;

[0035] The formula for calculating the amount of adsorbed gas is:

[0036]

[0037] in, and These represent the Langmuir volume constant and the Langmuir pressure constant, respectively. Indicates the stress adsorption enhancement coefficient. Indicates the non-uniformity index. This indicates ground stress.

[0038] Furthermore, in step S4, the specific formula for the amount of gas released by micro-fractures is as follows:

[0039]

[0040] in, This indicates the amount of gas released by the micro-fracture. Indicates the acoustic emission conversion coefficient. and Indicates the integration time interval. Represents the acoustic emission energy spectral density. Indicates frequency.

[0041] Furthermore, in step S5, the formula for calculating the dynamic gas content is:

[0042]

[0043] in, This represents the dynamic gas content over time t.

[0044] Furthermore, in step S6, the formula for calculating the objective function is:

[0045]

[0046] in, Describe the objective function. The optimized parameter vector includes: stress sensitivity coefficient, stress adsorption enhancement coefficient, and non-uniformity index. This represents the gas pressure at the location of the gas pressure sensor, representing the pressure field inverted in step S3. This indicates a time window, meaning data within a 10-minute period is being calculated.

[0047] Furthermore, the constraints of the objective function include: stress sensitivity coefficient greater than or equal to 0.01 and less than or equal to 0.2; stress adsorption enhancement coefficient greater than or equal to 0.1 and less than or equal to 0.5; and non-uniformity index greater than or equal to 0.5 and less than or equal to 1.5.

[0048] Furthermore, the convergence condition of the objective function includes:

[0049]

[0050] in, This represents the gradient convergence threshold.

[0051] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0052] 1. This invention achieves dynamic updates of the pressure field every 10 minutes through the inversion of the unsteady diffusion-seepage equation, captures sudden changes in gas pressure in real time, and the pressure field can accurately locate the outburst danger zone.

[0053] 2. This invention uses a multi-physics coupling model to perform dynamic parameter optimization, automatically calibrating the stress sensitivity coefficient, adsorption enhancement coefficient and non-uniformity index every 10 minutes, and the model can adapt to geological changes.

[0054] 3. This invention constructs an intelligent compensation model, which can correct the error of pressure sensor under coal seam environmental conditions by simultaneously correcting temperature, humidity and strain interference through multi-sensor fusion.

[0055] 4. This invention provides a strong basis for coal seam outburst risk identification and regional prediction by continuously and dynamically measuring coal seam gas pressure and content. It can help solve problems such as the connection between mine drainage and mining, accelerate the production progress of the working face, and thus improve the efficiency of coal mining, which has good economic and social benefits. Attached Figure Description

[0056] Other features, objects, and advantages of the invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0057] Figure 1 This is a flowchart illustrating an embodiment of the present invention;

[0058] Figure 2 This is a schematic diagram of the system structure according to an embodiment of the present invention;

[0059] Figure 3 This is a comparison chart of gas pressure in an embodiment of the present invention. Detailed Implementation

[0060] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0061] like Figure 1 As shown, an adaptive online method for determining basic parameters of coal seams includes the following steps:

[0062] Step S1: Deploy a multi-parameter sensor array in the coal seam borehole to collect raw gas pressure, temperature, humidity, coal strain and acoustic emission signals in real time;

[0063] Step S2: Calculate the corrected gas pressure using a composite environmental compensation model;

[0064] Step S3: Construct the unsteady diffusion-seepage equation to invert the gas concentration and pressure field;

[0065] Step S4: Perform time-frequency analysis on the acoustic emission signal and calculate the amount of gas released by the micro-rupture;

[0066] Step S5: Calculate the dynamic gas content based on the amount of gas released from micro-fractures;

[0067] Step S6: Construct the objective function and perform dynamic parameter optimization in real time.

[0068] In step S2, the formula for calculating the corrected gas pressure is:

[0069]

[0070] in, This indicates the corrected gas pressure. This indicates the original gas pressure collected. This represents the linear temperature compensation coefficient. This represents the nonlinear temperature compensation coefficient. Indicates real-time temperature. Indicates the reference temperature. Indicates the humidity compensation coefficient. Indicates real-time humidity. Indicates the reference humidity. Represents the stress coupling coefficient. This represents the elastic modulus of the coal. Indicates the strain of the coal body. Indicates the reference stress.

[0071] The specific parameter settings are shown in Table 1. The unit is 1 / K. The unit is 1 / K². The unit is 1 / %. The unit is 1 / Pa;

[0072] Table 1

[0073]

[0074] In the modified gas pressure formula, the compensation coefficient , and Through orthogonal experimental calibration, under temperature gradients of 15℃, 25℃, and 35℃ and humidity gradients of 30%, 50%, and 70%, the calculation formula is obtained by matrix operations:

[0075]

[0076] in, This represents a 9×3 design matrix, where each row corresponds to one experiment and contains three independent variables: temperature deviation, the square of the temperature deviation, and the humidity deviation. This represents a 9×1 column vector consisting of the compensation bias from 9 experiments, which is the ratio of the actual pressure to the original pressure minus 1.

[0077] In Table 1, the stress coupling coefficients are... The results were obtained through triaxial loading experiments, specifically including:

[0078] The confining pressure gradient was controlled at 5, 10, 15, and 20 MPa.

[0079] Measure the actual pressure and sensor readings at each stress level;

[0080] Simultaneous measurement of coal body strain;

[0081] Calculate the relative deviation for each stress level;

[0082] Calculate the relative stress change;

[0083] The stress coupling coefficient is obtained by solving linear regression.

[0084] In step S3, the specific formula for the unsteady diffusion-seepage equation is as follows:

[0085]

[0086] in, Indicates the free gas molar concentration. Indicates the porosity of the coal seam. Represents a time variable. Indicates the effective diffusion coefficient. Indicates dynamic penetration rate. The second derivative of the gas concentration. Denotes the divergence operator, Indicates the viscosity of methane. The first derivative representing gas pressure, This indicates the density of the coal body, and the amount of adsorbed methane. Represents the gas constant;

[0087] Among them, free gas molar concentration The unit is mol / m³, and the porosity of the coal seam is... Dimensionless, time variable The unit is s, and the effective diffusion coefficient is... The unit is m² / s, dynamic permeability. The unit is m², and the viscosity of methane is... The unit is Pa·s, the gas constant. The unit is J / (mol·K), temperature The unit is K, the density of coal. The unit is kg / m³, which represents the amount of gas adsorbed. The unit is mol / kg;

[0088] The viscosity of methane is set to a constant: 1.08 × 10⁻⁵ Pa·s;

[0089] The steps for solving the pressure field are as follows:

[0090] Dynamic permeability, adsorption capacity, and effective diffusion coefficient are calculated using environmental data.

[0091] Solving the unsteady diffusion-seepage equation yields the free gas molar concentration;

[0092] The free gas molar concentration is converted into a pressure field using the ideal gas law.

[0093] In the aforementioned unsteady diffusion-seepage equation, the formula for calculating the effective diffusion coefficient is:

[0094]

[0095] in, Indicates the baseline diffusivity. Indicates the diffusion activation energy. Represents the gas constant;

[0096] The formula for calculating dynamic permeability is:

[0097]

[0098] in, Indicates permeability under stress-free conditions. Represents the stress sensitivity coefficient. Indicates ground stress;

[0099] The formula for calculating the amount of adsorbed gas is:

[0100]

[0101] in, and These represent the Langmuir volume constant and the Langmuir pressure constant, respectively. Indicates the stress adsorption enhancement coefficient. Indicates the non-uniformity index. This indicates ground stress.

[0102] Wherein, Langmuir volume constant The unit is mol / kg, Langmuir pressure constant. The unit is 1 / Pa, stress adsorption coefficient Dimensionless, non-uniformity index Dimensionless, the unit of geostress is Pa.

[0103] The specific setting range of the parameters is shown in Table 2.

[0104] Table 2

[0105]

[0106] The Langmuir adsorption isotherm is the fundamental formula describing the adsorption equilibrium of a monolayer. Its standard form is θ=(bP) / (1+bP) or q=ap / (1+ap), where θ is the surface coverage, q is the amount of adsorption, P is the gas pressure, and a and b are the adsorption equilibrium constants related to temperature and heat of adsorption.

[0107] This formula is based on the following core assumptions:

[0108] Adsorption is achieved by a monolayer covering the solid surface; the solid surface is uniform and the adsorption sites have the same energy; there is no interaction between adsorbed molecules; and adsorption and desorption reach a dynamic equilibrium.

[0109] In step S4, the specific formula for the amount of gas released by micro-rupture is as follows:

[0110]

[0111] in, This indicates the amount of gas released by the micro-fracture. Indicates the acoustic emission conversion coefficient. and Indicates the integration time interval. Represents the acoustic emission energy spectral density. Indicates frequency.

[0112] The acoustic emission conversion coefficient was determined through coal sample destructive experiments. It characterizes the number of moles of gas released per unit mass of coal per unit time per unit acoustic emission energy, expressed in mol / (J·s·kg). The amount of gas released from micro-fractures was then calculated. The unit is mol / kg.

[0113] In step S5, the formula for calculating the dynamic gas content is:

[0114]

[0115] in, This represents the dynamic gas content over time t, expressed in mol / kg.

[0116] In step S6, the formula for calculating the objective function is:

[0117]

[0118] in, Describe the objective function. The optimized parameter vector includes: stress sensitivity coefficient, stress adsorption enhancement coefficient, and non-uniformity index. This represents the gas pressure at the location of the gas pressure sensor, representing the pressure field inverted in step S3. This indicates a time window, meaning data within a 10-minute period is being calculated.

[0119] During the optimization process, for each candidate parameter, the diffusion-seepage equation needs to be solved again to obtain a new pressure field, and then the pressure values ​​at the sensor location are extracted to form a sequence. Since solving the diffusion-seepage equation is computationally intensive, in practice, data with a sliding time window (such as 10 minutes) is usually used for optimization, rather than full-time data.

[0120] Improved objective function form: Since solving the diffusion-permeation equation is time-consuming, in the optimization iteration, other parameters (such as diffusion coefficient, initial permeability, etc.) are usually fixed, and only the influence of the optimization parameter vector on permeability and adsorption model is updated, and linear approximation or pre-calculated interpolation table is used to speed up the process.

[0121] The constraints of the objective function include: stress sensitivity coefficient greater than or equal to 0.01 and less than or equal to 0.2; stress adsorption enhancement coefficient greater than or equal to 0.1 and less than or equal to 0.5; and non-uniformity index greater than or equal to 0.5 and less than or equal to 1.5.

[0122] The convergence conditions of the objective function include:

[0123]

[0124] in, This represents the gradient convergence threshold.

[0125] The gradient convergence threshold is set to 1e-4.

[0126] Objective function optimization process: Use iterative algorithms such as gradient descent or Levenberg-Marquardt method to adjust θ and minimize J(θ).

[0127] Repeat this process in each iteration until the convergence condition is met.

[0128] The iterative process of the objective function is illustrated in Table 3.

[0129] Table 3

[0130]

[0131] Coal seam gas (mainly composed of methane) is typically treated as an ideal gas in engineering applications. According to the ideal gas law: PV = nRT, the equation can be transformed into P = (n / V)RT, where n / V is the molar concentration, representing the molar concentration of free gas (free gas) per unit volume of coal seam pores, i.e., the gas concentration C.

[0132] In the unsteady diffusion-seepage equation, the gas concentration C is one of the main variables to be solved. Pressure and concentration are directly related through the ideal gas law; therefore, once C is determined, P can be obtained. This equation assumes that the gas is an ideal gas, which is a reasonable approximation for coal seam gas pressures (typically <10 MPa). Therefore, in the numerical solution process: the concentration field is obtained by solving the partial differential equation, and then the pressure field is calculated using P=CRT.

[0133] like Figure 2 As shown, the present invention is achieved by constructing a three-layer system architecture, including a sensor array, an edge computing unit, and a mine monitoring center.

[0134] The borehole sensor array includes: pressure sensor, temperature and humidity sensor, strain sensor, and acoustic emission sensor;

[0135] The edge computing unit includes: an environmental compensation module, a diffusion-percolation solver, an acoustic emission analysis module, and a parameter optimization engine;

[0136] The mine monitoring center includes: pressure field display and dynamic content display.

[0137] like Figure 3 The image shows a comparison of three pressure curves:

[0138] Dark color: Corrected gas pressure P_c; Dashed line: Pressure at the sensor before optimization; Light color: Pressure at the sensor after optimization.

[0139] The optimized model pressure field is closer to the corrected gas pressure, with the residual changing from 0.18 MPa to 0.02 MPa.

[0140] The examples described herein are merely preferred embodiments of the invention and are not intended to limit the concept and scope of the invention. Any modifications and improvements made by those skilled in the art to the technical solutions of the invention without departing from the design concept of the invention should fall within the protection scope of the invention.

Claims

1. A method for self-adapting online determination of basic parameters of a coal seam, characterized in that, The method comprises the following steps: Step S1, deploying a multi-parameter sensor array in a coal seam borehole to collect original gas pressure, temperature, humidity, coal body strain and acoustic emission signals in real time; Step S2, constructing a composite environment compensation model to calculate corrected gas pressure by the collected temperature, humidity and coal body strain; Step S3, constructing a non-steady diffusion-seepage equation to invert gas concentration and pressure field; Step S4, performing time-frequency analysis on the acoustic emission signals to calculate the gas amount released by micro-fractures; Step S5, calculating dynamic gas content based on the gas amount released by micro-fractures; Step S6, constructing a target function to perform real-time parameter dynamic optimization.

2. The method of claim 1, wherein, In the step S2, the calculation formula of the composite environment compensation model is: ； wherein, represents the corrected gas pressure, represents the collected original gas pressure, represents the linear temperature compensation coefficient, represents the non-linear temperature compensation coefficient, represents the real-time temperature, represents the reference temperature, represents the humidity compensation coefficient, represents the real-time humidity, represents the reference humidity, represents the stress coupling coefficient, represents the coal body elastic modulus, represents the coal body strain, represents the reference stress.

3. The method of claim 2, wherein, The compensation coefficient , and Through orthogonal experiment calibration, under the conditions of temperature gradient of 15℃, 25℃, 35℃ and humidity gradient of 30%, 50%, 70%, through matrix operation solution, the calculation formula is: ； wherein denotes a 9 x 3 design matrix, each row corresponds to one experiment, containing three independent variables: temperature deviation, square of temperature deviation, humidity deviation, denotes a 9 x 1 column vector consisting of the compensation deviations of the 9 experiments, i.e. the ratio of the true pressure to the original pressure minus 1.

4. The method of claim 3, wherein, In the step S3, the specific formula of the non-steady diffusion-seepage equation is: ； wherein, represents the free gas molar concentration, represents the coal bed porosity, represents the time variable, represents the effective diffusion coefficient, represents the dynamic permeability, represents the second derivative of the gas concentration, represents the divergence operator, represents the methane viscosity, represents the first derivative of the gas pressure, represents the coal body density, represents the adsorbed gas amount, represents the gas constant; The solving step of the pressure field is: Using environmental data including temperature and ground stress to calculate dynamic permeability, adsorbed gas amount and effective diffusion coefficient; Solving the non-steady diffusion-seepage equation to obtain free gas molar concentration; Converting the free gas molar concentration into a pressure field through an ideal gas state equation.

5. The method of claim 4, wherein, In the non-steady diffusion-seepage equation, the calculation formula of the effective diffusion coefficient is: ； wherein, represents a reference diffusivity, represents an activation energy for diffusion, represents a gas constant; The calculation formula of the dynamic permeability is: ； wherein, K0represents the permeability in the unstressed state, Ksrepresents the stress sensitivity coefficient, σ represents the ground stress; The calculation formula of the adsorbed gas amount is: ； wherein, and respectively represent Langmuir volume constant and Langmuir pressure constant, represents stress adsorption enhancement coefficient, represents non-uniformity index, represents ground stress.

6. The method of claim 5, wherein, In the step S4, the specific formula of the gas amount released by micro-fractures is: ； wherein, represents the amount of gas released by microfractures, represents the acoustic emission conversion factor, and represents the integration time interval, represents the acoustic emission energy spectrum density, represents the frequency.

7. The method of claim 6, wherein, In the step S5, the calculation formula of the dynamic gas content is: ； wherein, denotes the dynamic gas content with respect to time t, denotes the density of the coal body.

8. The method of claim 7, wherein, In the step S6, the calculation formula of the target function is: ； wherein, denotes the objective function, denotes the optimization parameter vector, including: stress sensitivity coefficient, stress adsorption enhancement coefficient and non-uniformity index, denotes the gas pressure at the gas pressure sensor position of the pressure field inverted in step S3, denotes the time window, indicating that the data within 10 minutes is calculated.

9. The method of claim 8, wherein, The constraint conditions of the target function include: the stress sensitivity coefficient is greater than or equal to 0.01 and less than or equal to 0.2; the stress adsorption enhancement coefficient is greater than or equal to 0.1 and less than or equal to 0.5; and the non-uniformity index is greater than or equal to 0.5 and less than or equal to 1.

5.

10. The method of claim 9, wherein, The convergence conditions of the target function include: ； wherein, denotes a gradient convergence threshold.

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