Numerical simulation method and system for multi-field coupling disaster simulation of coal mine and medium

Abstract

The application discloses a numerical simulation method and system for coal mine multi-field coupling disaster simulation and a medium, and belongs to the technical field of electric digital data processing. The application builds four-field fully coupled control equation groups, and on this basis, real-time correction is performed on cross-field transmission errors. Further, the global Jacobian matrix is used to realize the synchronous update of four-field variables in the same calculation level, which fundamentally eliminates the loose coupling lag error and realizes the strict conservation of energy and momentum. After convergence, the disaster-causing evolution characteristic quantity is input into the preset instability risk evaluation model for threshold comparison to output the simulation result, which truly restores the cooperative evolution mechanism between physical fields, significantly improves the coal mine disaster precursor recognition accuracy, provides a reliable simulation basis for the accurate prediction and prevention and control of coal mine multi-field coupling disasters, and effectively solves the low reliability technical problem of the existing numerical simulation method in processing deep coal mine multi-field coupling disasters.

Description

Technical Field

[0001] This invention relates to the field of electronic digital data processing technology, and in particular to numerical simulation methods, systems and media for simulating multi-field coupled disasters in coal mines. Background Technology

[0002] To improve the disaster prevention and control capabilities of coal mines and ensure the safety of miners, it is of great practical significance and necessity to carry out numerical simulation research on multi-field coupled disasters in coal mines.

[0003] In existing technologies, numerical simulation technology for multi-field coupled disasters in coal mines simulates the occurrence and evolution of disasters by integrating multiple physical fields (such as stress fields, airflow fields, and temperature fields). First, the simulation objective is defined and relevant disaster scenarios are selected. Then, mathematical models for each physical field are established, such as models of mechanics, airflow, and heat conduction, and appropriate numerical methods (such as the finite element method and the finite difference method) are selected for solving. Subsequently, reasonable boundaries and initial conditions are set, and appropriate coupling strategies (strong or weak coupling) are designed based on the coupling effects between different physical fields. The coupling equations are solved numerically and iteratively to obtain dynamic data on the disaster evolution process. The results are then post-processed and risk assessed to provide emergency response recommendations. Finally, the simulation results are verified and applied to coal mine safety management to optimize mine prevention and control measures. The combination of real-time monitoring and dynamic simulation can provide disaster early warning, emergency decision-making, and risk management support for mines.

[0004] For example, Chinese patent application CN117313205A discloses a numerical simulation method for combined anchor bolt and anchor cable support in high-gas and water-rich roadways, which includes: firstly, constructing a geometric model of the roadway before excavation and calculating the initial stress field distribution of the roadway before excavation; secondly, constructing a geometric model of the roadway after excavation and calculating the plastic deformation of the surrounding rock after excavation; and finally, constructing a geometric model of combined anchor bolt and anchor cable support after excavation and calculating the evolution of key parameters during the combined anchor bolt and anchor cable support process under multi-physics coupling conditions.

[0005] However, in the process of implementing the inventive technical solution in the embodiments of this application, it was found that the above-mentioned technology has at least the following technical problems: Existing numerical simulation methods still have significant limitations in addressing multi-field coupled disasters in deep coal mines at the numerical solution level. Specifically, most mainstream methods employ "loose coupling" or "explicit iteration." This approach often neglects the instantaneous strong interactions between different physical fields (such as stress and seepage fields) within the same time step during time-step evolution, leading to severe lag errors in the calculation. Furthermore, due to the lack of precise handling of nonlinear mapping relationships at field boundaries, existing algorithms struggle to achieve strict conservation of energy and momentum. Consequently, simulation results cannot accurately reproduce the collaborative evolution mechanism between physical fields when simulating sudden disasters such as water inrush and outbursts in deep coal and rock masses, making it difficult to provide reliable simulation data for the accurate prediction and prevention of multi-field coupled disasters in coal mines. Summary of the Invention

[0006] To address the technical problems of existing technologies, such as neglecting the instantaneous strong interaction between different physical fields within the same time step in multi-field coupled numerical solution, difficulty in achieving strict conservation of energy and momentum, and inability to realistically reproduce the cooperative evolution mechanism between physical fields, thus leading to low reliability of coal mine disaster simulation results, this invention provides a numerical simulation method, system, and medium for multi-field coupled disaster simulation in coal mines. The technical solution is as follows: On the one hand, a numerical simulation method for simulating multi-field coupled disasters in coal mines is provided. This method includes: acquiring geological structure data, initial physical field parameters, and simulation step size parameters of the mining area to be simulated; constructing a three-dimensional spatial grid model to characterize the heterogeneous features of coal and rock mass using the geological structure data, and establishing a set of strongly coupled multi-field control equations covering the cross-mapping relationship between stress, fluid, thermal energy, and chemical damage on the topological nodes of the three-dimensional spatial grid model in combination with the initial physical field parameters; entering iterative calculation according to the time step sequence determined by the simulation step size parameters; defining the state variables of each physical field as the synchronous parameters to be solved within the current single time step, and calling the built-in interface conservation constraint operator to handle the synchronous parameters to be solved during the cross-physical field transfer process. The energy flux and momentum transfer are corrected in real time to eliminate nonlinear lag biases generated during the spatiotemporal discrete solution of different physical fields. A fully implicit simultaneous solution mechanism is adopted to perform inter-field collaborative calculation on the corrected synchronous parameters to be solved. By constructing a global Jacobian matrix containing each field component, the synchronous update of each physical field variable at the same calculation level is realized, and the residual convergence index during the iteration process is monitored in real time. The multi-field collaborative convergence state of the current time step is determined by the residual convergence index. After the multi-field collaborative convergence state is reached, the disaster-causing evolution characteristics of coal and rock mass under the combined action of stress response and physicochemical damage in the current calculation step are extracted, and the disaster-causing evolution characteristics are input into the preset instability risk assessment model for threshold comparison, and the simulation results are output.

[0007] On the other hand, a numerical simulation method system for simulating multi-field coupled disasters in coal mines is provided, including: a simulation data acquisition module, a multi-field coupling equation construction module, a cross-field conservation correction module, an inter-field coordination judgment module, and a simulation result output module; the simulation data acquisition module is used to acquire geological structure data, initial physical field parameters, and simulation step size parameters of the mining area to be simulated; the multi-field coupling equation construction module is used to construct a three-dimensional spatial grid model to characterize the heterogeneous features of coal and rock mass using geological structure data, and, combined with the initial physical field parameters, establish a set of strongly coupled multi-field control equations covering the cross-mapping relationship between stress, fluid, thermal energy, and chemical damage on the topological nodes of the three-dimensional spatial grid model; the cross-field conservation correction module is used to enter iterative calculation according to the time step sequence determined by the simulation step size parameters, define the state variables of each physical field as the synchronization parameters to be solved within the current single time step, and adjust... The built-in interface conservation constraint operator is used to correct the energy flux and momentum transfer of the synchronization parameters to be solved in real time during the cross-physics field transfer process, so as to eliminate the nonlinear lag bias generated by different physics fields in the spatiotemporal discrete solution process. The inter-field coordination judgment module is used to perform inter-field coordination calculation on the corrected synchronization parameters to be solved using a fully implicit simultaneous solution mechanism. By constructing a global Jacobian matrix containing each field component, the synchronous update of each physics field variable at the same calculation level is realized, and the residual convergence index during the iteration process is monitored in real time. The multi-field coordination convergence state of the current time step is determined by the residual convergence index. The simulation result output module is used to extract the disaster-causing evolution characteristics of coal and rock mass under the combined action of stress response and physicochemical damage in the current calculation step after the multi-field coordination convergence state is reached. The disaster-causing evolution characteristics are input into the preset instability risk assessment model for threshold comparison and output simulation results.

[0008] On the other hand, a computer-readable storage medium is provided, in which at least one instruction is stored, which is loaded and executed by a processor to implement the above-mentioned numerical simulation method for simulating multi-field coupled disasters in coal mines.

[0009] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following: This invention constructs a set of strongly coupled multi-field control equations and introduces interface conservation constraint operators and a fully implicit simultaneous solution mechanism to achieve instantaneous strong interactive collaborative calculation of different physical fields within the same time step. This effectively ensures the conservation of energy and momentum, significantly reduces numerical lag errors, and improves the stability and accuracy of multi-field coupled simulation. It can realistically depict the collaborative evolution process of deep coal and rock masses under the combined effects of stress, seepage, heat, and chemical damage, enhance the credibility of simulations of coal mine water inrush, outbursts, and other disasters, and provide reliable numerical support for accurate prediction and risk prevention of coal mine disasters.

[0010] Specifically, existing technologies often employ "loose coupling" or "explicit iteration" methods, which tend to ignore the instantaneous equilibrium of different physical fields within the same time step during time-step evolution. This leads to a failure to strictly conserve energy and momentum during cross-field transfer, resulting in significant cumulative errors. To address this issue, this invention introduces an interface conservation constraint operator into the iterative calculation to correct the energy flux and momentum transfer of each physical field's state variables during cross-field transfer in real time. Compared to existing technologies, this invention ensures the conservation of multi-field interaction interfaces from a mathematical and physical mechanism perspective, effectively eliminating nonlinear lag biases in the spatiotemporal discrete solution process, and significantly improving the physical realism and stability of numerical calculations.

[0011] Furthermore, existing technologies, when dealing with multi-field coupling problems in deep coal mines, often struggle to capture the instantaneous strong interactions between physical fields such as stress and fluid within the same time step due to algorithmic limitations. This results in simulations that fail to accurately reproduce the evolution mechanisms of sudden disasters such as water inrush and outbursts. This invention abandons the traditional separate solution mode and adopts a fully implicit simultaneous solution mechanism. By constructing a global Jacobian matrix containing all field components, it achieves synchronous updates of all physical field variables at the same computational level. Compared to existing technologies, this invention can accurately capture the instantaneous strong coupling effects between multiple physical fields, overcoming the numerical lag caused by explicit iteration, thereby accurately simulating the collaborative evolution process of deep coal and rock masses under complex working conditions.

[0012] Furthermore, existing technologies often struggle to accurately characterize the heterogeneous features of coal and rock masses and their multi-field cross-mapping relationships, leading to significant deviations between the model and actual geological conditions. This invention utilizes geological structural data to construct a three-dimensional spatial grid model characterizing the heterogeneous features of coal and rock masses, and establishes a set of strongly coupled multi-field governing equations encompassing stress, fluid, thermal energy, and chemical damage, combined with initial physical field parameters. This approach not only improves the adaptability of the geological model to complex structures but also ensures the convergence and accuracy of the simulation results through the organic combination of fully implicit simultaneous solutions and interface conservation constraints. Finally, by extracting disaster-causing evolutionary features and performing threshold comparisons, this invention achieves a precise leap from numerical simulation to disaster early warning, providing a more reliable scientific basis than existing technologies for the prevention and control of multi-field coupled disasters in coal mines.

[0013] In summary, compared with existing technologies, this invention has significant advantages in terms of multi-field coupled numerical simulation accuracy, energy and momentum conservation, computational efficiency and stability. It can simulate the evolution of coal mine disasters more realistically and accurately, providing strong numerical support and decision-making basis for safe production and risk prevention in coal mines. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0015] Figure 1 A flowchart illustrating a numerical simulation method for simulating multi-field coupled disasters in coal mines, provided in an embodiment of this application; Figure 2 A schematic diagram of the construction of a three-dimensional spatial mesh model for a numerical simulation method for simulating multi-field coupled disasters in coal mines, provided in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of a numerical simulation system for simulating multi-field coupled disasters in coal mines, provided in an embodiment of this application. Detailed Implementation

[0016] Embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of the present disclosure are shown in the drawings, it should be understood that embodiments of the present disclosure may be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure.

[0017] It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure. In the description of the embodiments of this disclosure, the term "comprising" and similar terms should be understood as open-ended inclusion, i.e., "including but not limited to". The term "based on" should be understood as "at least partially based on". The term "one embodiment" or "this embodiment" should be understood as "at least one embodiment". The terms "first", "second", etc., may refer to different or the same objects.

[0018] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0019] With the continuous advancement of deep coal mining, mine safety issues are becoming increasingly serious, especially coal mine disasters (such as water inrush, outbursts, and fires), which pose a huge threat to the lives of miners and the production of mining areas. The occurrence of coal mine disasters is often the result of the combined effects of multiple physical fields (stress field, seepage field, thermal field, chemical damage field, etc.), and their evolution process is complex and exhibits strong nonlinearity and coupling characteristics. Traditional disaster prediction and prevention methods are insufficient to comprehensively and accurately simulate the multi-field coupled disaster evolution process; therefore, there is an urgent need to develop a numerical simulation method that can more realistically and accurately reflect the occurrence mechanism of coal mine disasters.

[0020] Most existing numerical simulation methods for coal mine disasters employ loose coupling or explicit iterative approaches, which have significant limitations when dealing with multi-physics coupling. Specifically, loose coupling methods often neglect the instantaneous strong interactions between different physical fields within the same time step, leading to lag errors in the numerical calculation process and significantly reducing the reliability of the simulation results. Explicit iterative methods, on the other hand, are insufficient in convergence speed and computational efficiency, making them unable to handle complex coal mine disaster scenarios. More critically, due to the lack of precise handling of the nonlinear mapping relationships at the boundaries of physical fields, existing algorithms cannot achieve strict conservation of energy and momentum when simulating coal mine disasters, further reducing the accuracy of the simulation results.

[0021] Therefore, to address the aforementioned technical problems, there is an urgent need for a novel numerical simulation method capable of accurately describing the multi-field coupling mechanisms in coal mine disasters and ensuring the conservation of physical quantities, thereby providing reliable technical support for the accurate prediction and prevention of coal mine disasters. This invention is proposed against this backdrop, aiming to overcome the bottlenecks of existing technologies, significantly improve the accuracy and stability of coal mine disaster simulation, and thus provide a more scientific and effective technical guarantee for coal mine safety management.

[0022] Firstly, such as Figure 1 The diagram shows a flowchart of a numerical simulation method for simulating multi-field coupled disasters in coal mines, provided in an embodiment of this application. The method includes the following steps: acquiring geological structure data, initial physical field parameters, and simulation step size parameters of the mining area to be simulated; constructing a three-dimensional spatial grid model to characterize the heterogeneous features of coal and rock mass using the geological structure data, and establishing a set of strongly coupled multi-field control equations covering the cross-mapping relationships between stress, fluid, thermal energy, and chemical damage on the topological nodes of the three-dimensional spatial grid model, in conjunction with the initial physical field parameters; entering iterative calculation based on the time step sequence determined by the simulation step size parameters; defining the state variables of each physical field as the synchronous parameters to be solved within the current single time step, and calling the built-in interface conservation constraint operator to determine the energy of the synchronous parameters to be solved during the cross-physical field transfer process. Real-time corrections are made to flux and momentum transfer to eliminate nonlinear lag biases generated during the spatiotemporal discrete solution of different physical fields. A fully implicit simultaneous solution mechanism is adopted to perform inter-field collaborative calculations on the corrected synchronous parameters to be solved. By constructing a global Jacobian matrix containing each field component, synchronous updates of each physical field variable are achieved at the same computational level. The residual convergence index is monitored in real time during the iteration process. By judging the stability of the residual convergence index under the preset convergence criterion, the multi-field collaborative convergence state in the current time step is determined. After determining that the multi-field collaborative convergence state has been reached, the disaster-causing evolution characteristics of coal and rock mass under the combined action of stress response and physicochemical damage in the current calculation step are extracted. The disaster-causing evolution characteristics are input into the preset instability risk assessment model for threshold comparison, and the simulation results are output.

[0023] The steps of this invention achieve high efficiency and stability in coal mine disaster simulation through precise synergy. The acquisition of geological structural data and initial physical field parameters provides a realistic foundation for the three-dimensional spatial grid model, ensuring the accuracy of subsequent multi-physics coupled calculations. By constructing a set of strongly coupled multi-field control equations and introducing interface conservation constraint operators, hysteresis errors and information transmission distortions between different physical fields are eliminated, improving the real-time synergy between physical fields. Supported by a fully implicit simultaneous solution mechanism and synchronous updates of the Jacobian matrix, each physical field variable can be updated synchronously at the same computational level, ensuring energy and momentum conservation and optimizing computational efficiency. The residual convergence monitoring and multi-field collaborative convergence determination mechanism further guarantee the stability and accuracy of the simulation process. Finally, the extracted disaster-causing evolutionary characteristics are combined with the instability risk assessment model, providing a scientific basis for accurate prediction and risk prevention of coal mine disasters. Overall, the steps of this invention work closely together to ensure the high accuracy and reliability of the simulation results, greatly enhancing the decision support capability for coal mine safety management.

[0024] It should be noted that the geological structure data, initial physical field parameters, and simulation step size parameters of the mining area to be simulated are obtained. The geological structure data includes information such as drilling records, 3D seismic exploration results, fault distribution maps, and lithological columnar sections, providing a realistic geological basis for the subsequent construction of the 3D spatial mesh model; the initial physical field parameters include the original rock stress state, initial pore pressure field, geothermal gradient, and initial chemical damage distribution, providing quantitative input for setting the initial conditions of each physical field control equation; the simulation step size parameters include the initial time step and the maximum time step, used to control the timing progression strategy of the iterative calculation.

[0025] As a further approach, a three-dimensional spatial grid model is constructed using geological structural data to characterize the heterogeneous features of coal and rock masses, specifically including: like Figure 2 The diagram illustrates the construction of a three-dimensional spatial mesh model for a numerical simulation method used in coal mine multi-field coupled disaster simulation according to an embodiment of this application. First, the geological structural data is spatially geometrically interpreted and reconstructed to generate a three-dimensional geometric model of the mining area containing coal seams, roof and floor strata, and fault structures. In implementing this step, the acquired geological structural data of the mining area to be simulated is first preprocessed and spatially geometrically interpreted. Specifically, using borehole columnar sections, geological profiles, and three-dimensional seismic exploration data, stratigraphic interfaces are fitted and structurally modeled in three-dimensional modeling software (such as GOCAD and Petrel). Through spatial interpolation and topology repair techniques, a three-dimensional geometric model of the mining area containing coal seams, roof strata, floor strata, and key structures such as faults and folds is generated. This model accurately characterizes the spatial distribution and contact relationships of each geological unit, providing a geometric framework for subsequent numerical calculations.

[0026] Next, unstructured mesh generation techniques were used to discretize the three-dimensional geometric model of the mining area, with local mesh refinement in fault fracture zones and coal seam stress concentration areas, generating a three-dimensional spatial mesh model composed of tetrahedral or hexahedral elements. After generating the three-dimensional geometric model, unstructured mesh generation techniques (such as Delaunay triangulation or frontal advancement) were used to discretize the geometric model. Considering the specific characteristics of coal mine disaster simulation, an adaptive mesh refinement strategy was implemented: for critical areas with abrupt geometric changes or large stress gradients, such as fault fracture zones, fold axes, and coal seam stress concentration areas, smaller mesh size control parameters were set for local refinement to capture the discontinuities in the microstructure; for boundary strata far from the study area, larger mesh sizes were used to reduce the computational scale. Finally, a three-dimensional spatial mesh model composed of tetrahedral (suitable for complex geometric boundaries) or hexahedral (suitable for areas with high accuracy requirements) elements was generated, ensuring that the mesh quality met the positive definiteness requirement of the Jacobian matrix for finite element calculations.

[0027] Secondly, based on the lithological distribution information in the geological structure data, the Weibull distribution probability model and the spatial correlation algorithm are used to assign differentiated physical and mechanical parameters to each grid unit in the three-dimensional spatial grid model in order to characterize the heterogeneous characteristics of the coal and rock mass.

[0028] To accurately represent the heterogeneous physical and mechanical properties of coal and rock masses, this embodiment introduces statistical damage mechanics theory to assign parameters to the mesh model. The specific process is as follows: Based on lithological distribution information from geological structural data, the macroscopic average physical and mechanical parameters (such as elastic modulus, compressive strength, and permeability) of each rock layer (e.g., coal seam, sandstone, mudstone) are determined. Subsequently, the Weibull probability distribution model is used to describe the discreteness of the rock microstructure parameters, with the following probability density function: In the formula, These are the physical and mechanical parameter values ​​of the mesh element; These are the average physical and mechanical parameters (scale parameters) of this type of lithology; The homogeneity coefficient (shape parameter) reflects the degree of material homogeneity; a larger value indicates more uniform material properties, and vice versa. It is important to note that, to ensure the overall average mechanical parameters of the mesh are strictly equal to the macroscopic average physical and mechanical parameters obtained from geological surveys... Here, we introduce the conversion relationship between the mean and the scale parameter: ;in This is the gamma function. Using the above formula, we can determine the actual measured values... and the set homogeneity coefficient Inversely calculate accurate scale parameters This ensures that after assigning values ​​to heterogeneous parameters, the overall mechanical properties of the model remain consistent with the actual measured values ​​of the formation, eliminating the error of the overall average parameters of the grid deviating from the measured values ​​of the formation.

[0029] During the assignment process, spatial correlation algorithms (such as Monte Carlo simulation or geostatistical methods) are used to generate differentiated physical and mechanical parameters for each grid cell in the three-dimensional spatial grid model, which follow the aforementioned Weibull distribution. In this way, the strength and stiffness of each cell within the model exhibit a random but statistically regular heterogeneous distribution in space, thus realistically characterizing the differences in physical and mechanical properties caused by the uneven distribution of microfractures and pores within the coal and rock mass at the numerical model level.

[0030] Building upon the above, it should also be noted that a multi-field strongly coupled governing equation system is established on the topological nodes of the three-dimensional spatial mesh model, encompassing the cross-mapping relationships between stress, fluid, thermal energy, and chemical damage. Specifically, this includes: First, the fundamental unknowns of the multiphysics coupled system are defined. At each topological node of the 3D spatial mesh model, a state vector containing four types of core variables is constructed. Specifically, it is expressed as: ;in, For displacement vector variables (corresponding to stress field). This represents the pore pressure variable (corresponding to the fluid field). For temperature variables (corresponding to thermal fields). This is a chemical damage variable (corresponding to the chemical field, with values ​​typically ranging from 0 to 1, where 0 represents no damage and 1 represents complete destruction).

[0031] Next, firstly, based on the theory of porous media mechanics, a stress balance equation with the effective stress principle as its core is established. To reflect the weakening effect of chemical corrosion on the mechanical properties of coal and rock masses, this embodiment introduces chemical damage variables into the constitutive relation.

[0032] Specifically, the effective stress of coal and rock mass Represented as: In the formula, For the total stress tensor, For Biot coefficient, Let be the unit tensor. The elastic constitutive relation considering chemical damage is modified as follows: ,in, The initial elasticity matrix, The strain tensor is used. Simultaneously, a chemical damage variable is introduced into the yield criterion to reduce and correct the cohesion and internal friction angle, thereby establishing a stress field governing equation that incorporates the coupling effects of stress, pore pressure, and chemical damage.

[0033] Secondly, based on Darcy's law and the law of conservation of mass, a fluid seepage control equation is established. This equation not only describes the fluid flow but also couples the effects of the stress field and the chemical damage field.

[0034] In practical implementation, the continuity equation is expressed as: In the formula, For the permeability tensor, For fluid dynamic viscosity, The volumetric strain (obtained from the stress field solution) reflects the influence of pore deformation caused by the stress field on seepage. For Biot modulus, For source and sink items.

[0035] In particular, the permeability tensor Defined as a function of the chemical damage variable D, for example, using an exponential relationship model. ,in Initial penetration rate, This is the damage influence coefficient, which is used to realize the coupling mechanism of chemical damage-induced permeability evolution.

[0036] Thirdly, based on Fourier's law and the law of conservation of energy, equations for heat conduction and convection are established. In practical implementation, the energy conservation equation is expressed as: In the formula, For equivalent volumetric heat capacity, The equivalent thermal conductivity coefficient, The heat capacity of the fluid. The seepage velocity is obtained by solving the fluid field. The heat source intensity is denoted in this equation. The term refers to the thermal convection term caused by fluid seepage, which realizes a strong coupling between the temperature field and the fluid field.

[0037] Fourth, a chemical damage evolution equation is established based on the theory of chemical reaction kinetics to describe the damage mechanism of chemical solution erosion on the microstructure of coal and rock mass; in specific implementation, it is assumed that chemical damage is mainly affected by the concentration of specific ions in the fluid. and reaction time Control. Specifically, the concentration of a particular ion. The evolution of porous fluids follows the convection-diffusion-reaction equation to characterize its dynamic changes with fluid seepage and reaction: In the formula, The seepage velocity is obtained by solving the fluid field. For the effective diffusion coefficient, Let be the rate of chemical reaction consumption. Based on this, and combined with the Arrhenius equation, the law of chemical damage evolution is further quantified as follows: in, The reaction order is [number]. The reaction rate constant is affected by temperature T and satisfies , Pre-exponential factor, The activation energy of the reaction. Here, is the ideal gas constant. This set of equations quantitatively describes the dynamic accumulation of ions with fluid migration and chemical damage over time and concentration, and provides reliable variable inputs for the aforementioned stress intensity reduction and fluid field permeability evolution. The stress field control equations, fluid field control equations, thermal field control equations, and chemical damage evolution equations established above are mathematically combined. At the topological nodes, these equations are expressed through state variables and their derivative terms (such as...). These equations are intertwined and serve as source terms for each other, ultimately forming a nonlinear, strongly coupled system of partial differential equations. This system of equations is the core mathematical model for subsequent numerical solutions.

[0038] Furthermore, the built-in interface conservation constraint operator is invoked to correct the energy flux and momentum transfer of the synchronization parameters to be solved in the cross-physics field process in real time. Specific implementation methods include: At the current time step First, the interface regions of different physical fields such as stress field, fluid field, and thermal field in the spatial mesh model are located. Then, the state variables (such as displacement, pore pressure, and temperature) of each physical field near the interface are extracted and denoted as state vectors. and Since different physical fields may use different mesh discretization scales (e.g., stress fields use four-node tetrahedral elements, while fluid fields use eight-node hexahedral elements), it is necessary to construct an interpolation matrix that allows for the transfer of variables across physical fields. This matrix is ​​established based on the principle of shape function interpolation and is used to map and project the state variables of the source field grid nodes onto the target field grid nodes, thereby realizing the initial spatial transfer of data.

[0039] Next, based on the principles of energy and momentum conservation, the physical consistency of the interpolated data is verified. Specifically, the deviation between the theoretical flux transfer values ​​(theoretical solutions that satisfy the conservation laws) and the actual interpolated transfer values ​​(approximate solutions after numerical mapping) of each physical field at the interface is calculated.

[0040] For momentum transfer (such as the coupling of stress field and fluid field), calculate the theoretical force vector at the interface. Interpolated nodal force vectors Force deviation between For energy flux transfer (such as the coupling of thermal and fluid fields), calculate the theoretical heat flux density. Interpolated heat flux density Energy deviation between This deviation reflects the non-physical dissipation error and numerical oscillation caused by grid mismatch interpolation and spatiotemporal discretization.

[0041] Furthermore, to eliminate the aforementioned bias, the Lagrange multiplier method is introduced to construct a constrained optimization model. This model is designed to minimize the bias (i.e., ...). or The objective function is to satisfy flux conservation. Lagrangian function with constraints : In the formula, This is a diagonal weight matrix, where the diagonal elements are set to the control volume (or interface area) of the corresponding interpolation target grid node to ensure that the error minimization process conforms to the integral consistency of energy physical dimensions. Let Lagrange multiplier vectors be used. Here is the conservation constraint matrix. Let be the theoretical flux vector. By differentiating the Lagrange function and setting it to zero, a system of linear equations is established and solved to obtain the correction coefficient matrix that can correct for propagation errors. .

[0042] Using the correction coefficient matrix obtained by the solution The synchronization parameters to be solved are compensated and corrected in real time in the cross-physics transport term. The corrected transport flux is then applied. Represented as: Through this correction mechanism, the energy flux and momentum transfer at the interface are strictly guaranteed to obey the conservation law at the numerical calculation level. This effectively eliminates non-physical dissipation caused by interpolation errors and nonlinear hysteresis bias caused by differences in time integration step size, thus ensuring the accuracy and stability of multi-physics coupled data interaction.

[0043] As a further approach, when implementing a fully implicit simultaneous solution, firstly, based on the corrected synchronization parameters to be solved, a system containing displacement field variables is constructed. Fluid field pore pressure variables Thermal field temperature variables and chemical damage variables The global unknown vector is then determined. Subsequently, for the multi-field strongly coupled control equation system, the partial derivatives of each physical field control equation with respect to the aforementioned global unknown vector are derived. Specifically, a global Jacobian matrix reflecting the cross-coupling effect between physical fields is constructed. Its mathematical expression is: In the formula, These represent the residual vectors for the stress field, fluid field, thermal field, and chemical damage equations, respectively. The off-diagonal elements in the matrix precisely describe the strong coupling mechanisms between the various physical fields.

[0044] Based on the Newton-Raphson iterative algorithm, the nonlinear equation system is linearized to construct a linear algebraic equation system. The system of equations is solved using a parallel computing solver to obtain incremental solutions for each physical field variable. The incremental solution is then superimposed with the initial variable values ​​of the current iteration step, i.e. This enables the synchronous updating of all physical field state variables at the same computational level.

[0045] As a further measure, to determine the convergence status of the iterative calculation, the following residual monitoring and judgment process is implemented: First, the vector norms of the unbalanced stress field, the residual vector norms of the fluid field mass conservation, the residual vector norms of the thermal field energy conservation, and the residual vector norms of the chemical damage evolution are calculated respectively.

[0046] Subsequently, to eliminate the influence of dimensional differences on convergence judgment, the above-mentioned norm values ​​were dimensionlessized to construct a residual convergence index that includes both relative and absolute residuals. The residual convergence index of each physical field was then compared with a preset convergence tolerance threshold (e.g., ...). The results are compared. If the residual convergence indices of each physical field are all less than the convergence tolerance threshold, then the current time step is determined to have reached the multi-field co-convergence state.

[0047] If the convergence condition is not met within the maximum number of iterations, an adaptive time step reduction mechanism is triggered, which reduces the current time step by a preset ratio (such as halving) and re-performs the iterative calculation within that time step to ensure the robustness of the numerical solution process.

[0048] Based on the above, after determining that a multi-field coordinated convergence state has been reached, characteristic quantities are extracted for the disaster-causing mechanism of coal and rock mass: First, the three-dimensional spatial mesh model is scanned, and the global maximum value of the cumulative chemical damage variable is extracted as the damage extremum feature. Second, based on yield criteria (such as the Drucker-Prager criterion or the Mohr-Coulomb criterion), the mesh cells currently in the plastic yield state are identified, and the volume of the plastic zone is statistically analyzed. And calculate its expansion rate relative to the previous time step. .

[0049] Simultaneously, the local energy release rate of the coal and rock mass is calculated by combining the energy dissipation theory. Specifically, based on the elastic strain energy density in the lossless state. The elastic strain energy density of a chemically damaged object is expressed as: Local energy release rate Defined as the effect of damaged elastic strain energy density on chemical damage variable The negative value of the partial derivative, i.e.: In the formula, For strain tensor, This is the initial elasticity matrix. This formula quantitatively calculates the energy released externally during the microstructural damage and degradation process, providing accurate energy-driven characteristic inputs for subsequent instability risk assessment.

[0050] Finally, the expansion rate of the plastic zone, the local energy release rate, and the extreme values ​​of the cumulative chemical damage variables were constructed into a multidimensional feature vector as a disaster-causing evolution characteristic quantity characterizing the precursors of coal and rock mass instability.

[0051] Furthermore, the extracted disaster-causing evolutionary features are input into a pre-defined instability risk assessment model for post-processing: First, the disaster-causing evolutionary features are dimensionless using the maximum normalization method to eliminate dimensional differences. Then, the weight coefficient vector from the pre-defined model is invoked. It should be noted that the weighting coefficient vector is obtained through pre-training using an objective weighting method (such as the entropy weighting method) combined with historical disaster-causing sample data. Specifically, the information entropy of each disaster-causing evolutionary feature in the historical samples is calculated to assess the degree of variation of each feature component and assign objective weights, thereby avoiding subjective errors from manual assignment. Using the determined weighting coefficient vector, a weighted summation calculation is performed to generate a comprehensive instability risk index characterizing the current stability of the coal and rock mass. : ;in, , , These are the dimensionless characteristic components.

[0052] Finally, the overall instability risk index will be used. The simulation results are compared with preset disaster classification threshold ranges. For example, the threshold range [0, 0.3) is set as low risk, [0.3, 0.7) as medium risk, and [0.7, 1.0] as high risk. Based on the comparison results, the current instability risk level is determined, and the simulation results, including the risk level, the distribution cloud map of the plastic zone, and the evolution curves of key physical fields, are output.

[0053] This invention significantly improves the accuracy and reliability of coal mine disaster simulation in several aspects by employing a fully implicit simultaneous solution mechanism to perform inter-field collaborative calculations on the corrected synchronization parameters. First, by constructing a global unknown vector containing variables such as displacement, pore pressure, temperature, and chemical damage, and deriving the partial derivatives of the governing equations for each physical field, a global Jacobian matrix reflecting the cross-coupling effect between physical fields is formed, ensuring the accurate calculation of the interactions between them. This process precisely captures the complex coupling relationships between the various physical fields, thereby improving the overall accuracy and realism of the simulation.

[0054] Secondly, the Newton-Raphson iterative algorithm is used to linearize the global Jacobian matrix, which can efficiently solve the incremental solutions of each physical field variable and superimpose them with the initial variables of the current time step, thereby synchronously updating the state variables of all physical fields. This iterative calculation process ensures the accuracy of numerical calculation and improves computational efficiency through effective iterative convergence.

[0055] Furthermore, by monitoring the residual convergence index in real time and combining it with an adaptive time step reduction mechanism, the time step can be automatically adjusted when the residual convergence index of the physical field fails to reach a preset threshold, ensuring the stability and accuracy of the calculation process. This mechanism effectively avoids error accumulation caused by unstable convergence and guarantees the reliability of simulation results under complex and variable physical conditions.

[0056] Finally, by extracting disaster-causing evolution characteristics (such as the expansion rate of the plastic zone, the local energy release rate, and the extreme value of cumulative chemical damage) and inputting them into the instability risk assessment model for threshold comparison, the stability and instability risk of coal and rock masses can be accurately assessed. The comprehensive instability risk index provides a scientific basis for mine safety management and timely decision support for disaster early warning and prevention.

[0057] The close collaboration of the above four parts, through fully implicit solution and collaborative calculation of the physical field, ensures synchronous updates and high-precision calculations of each physical field variable, eliminates lag errors, and enhances the stability and accuracy of simulation results. Simultaneously, through the extraction of disaster-causing evolutionary characteristics and instability risk assessment, it provides accurate disaster prediction capabilities and real-time risk assessment, offering strong technical support for mine disaster prevention and control.

[0058] Secondly, such as Figure 3 The diagram shown is a structural schematic of a numerical simulation system for simulating multi-field coupled disasters in coal mines, provided in an embodiment of this application. This embodiment of the application also provides a numerical simulation system for simulating multi-field coupled disasters in coal mines, which includes: a simulation data acquisition module, a multi-field coupling equation construction module, a cross-field conservation correction module, an inter-field coordination judgment module, and a simulation result output module.

[0059] Specifically, the simulation data acquisition module is used to acquire geological structure data, initial physical field parameters, and simulation step size parameters of the mining area to be simulated.

[0060] The multi-field coupled equation construction module is used to construct a three-dimensional spatial grid model to characterize the heterogeneous features of coal and rock masses using geological structural data. Combined with the initial physical field parameters, it establishes a set of multi-field strongly coupled control equations on the topological nodes of the three-dimensional spatial grid model, covering the cross-mapping relationship between stress, fluid, thermal energy and chemical damage.

[0061] The cross-field conservation correction module is used to enter the iterative calculation based on the time step sequence determined by the simulation step size parameter. Within the current single time step, the state variables of each physical field are defined as the synchronization parameters to be solved, and the built-in interface conservation constraint operator is called to correct the energy flux and momentum transfer of the synchronization parameters to be solved in the cross-physical field transfer process in real time, so as to eliminate the nonlinear lag deviation generated by different physical fields in the spatiotemporal discrete solution process.

[0062] The inter-field collaborative determination module is used to perform inter-field collaborative calculations on the corrected synchronous parameters to be solved using a fully implicit simultaneous solution mechanism. By constructing a global Jacobian matrix containing each field component, it realizes the synchronous update of each physical field variable at the same computational level and monitors the residual convergence index in real time during the iteration process. By judging the stability of the residual convergence index under the preset convergence criterion, it determines the multi-field collaborative convergence status in the current time step.

[0063] The simulation result output module is used to extract the disaster-causing evolution characteristics of coal and rock mass under the combined action of stress response and physicochemical damage in the current calculation step after determining that the multi-field collaborative convergence state has been reached. The disaster-causing evolution characteristics are then input into the preset instability risk assessment model for threshold comparison, and the simulation results are output.

[0064] Thirdly, the embodiments of this application provide a computer-readable storage medium, which stores at least one instruction. The at least one instruction is loaded and executed by a processor to implement the above-mentioned numerical simulation method for simulating multi-field coupled disasters in coal mines.

[0065] In summary, this invention overcomes a series of limitations in existing technologies when dealing with multi-physics coupled disasters in coal mines, such as hysteresis errors, insufficient conservation of energy and momentum, and inaccurate reconstruction of the physical field co-evolution mechanism. By simultaneously calculating the strong coupling effect of multiple physical fields, accurately handling nonlinear boundary mapping relationships, and achieving strict conservation of energy and momentum, this invention can realistically reproduce the disaster evolution process of deep coal and rock masses under complex physical conditions.

[0066] Compared with existing loosely coupled or explicit iterative methods, this invention provides a more accurate multi-field coupled simulation scheme, significantly improving the accuracy and reliability of disaster prediction. This method can provide a more scientific and reliable basis for risk assessment and prevention of coal mine disasters, and has significant application value, especially in the prediction and prevention of sudden disasters such as water inrush and outbursts.

[0067] Therefore, this invention not only has significant advantages in the accuracy and stability of coal mine disaster simulation, but also provides a brand-new technical path for mine safety management, disaster prevention and control and risk assessment, with broad application prospects and huge social and economic benefits.

[0068] Through the above description of the implementation methods, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the above functions can be divided into different functional modules to complete all or part of the functions described above.

[0069] In the embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between devices or units, and may be electrical, mechanical, or other forms.

[0070] The units described as separate components may or may not be physically separate. A component shown as a unit can be one or more physical units, located in one place or distributed in multiple different locations. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0071] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0072] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to the solution, or all or part of the technical solution, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0073] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A numerical simulation method for simulating multi-field coupled disasters in coal mines, characterized in that, Includes the following steps: Acquire the geological structure data, initial physical field parameters, and simulation step size parameters of the mining area to be simulated; A three-dimensional spatial grid model for characterizing the heterogeneous features of coal and rock masses was constructed using geological structural data. In conjunction with the initial physical field parameters, a set of multi-field strongly coupled control equations covering the cross-mapping relationship between stress, fluid, thermal energy and chemical damage was established on the topological nodes of the three-dimensional spatial grid model. The iterative calculation is entered based on the time step sequence determined by the simulation step size parameter. Within the current single time step, the state variables of each physical field are defined as the synchronization parameters to be solved, and the built-in interface conservation constraint operator is called to correct the energy flux and momentum transfer of the synchronization parameters to be solved in the cross-physical field transfer process in real time, so as to eliminate the nonlinear lag deviation generated by different physical fields in the spatiotemporal discrete solution process. A fully implicit simultaneous solution mechanism is adopted to perform inter-field collaborative calculation on the corrected synchronous parameters to be solved. By constructing a global Jacobian matrix containing each field component, the synchronous update of each physical field variable at the same computational level is realized. The residual convergence index is monitored in real time during the iteration process, and the multi-field collaborative convergence status at the current time step is determined by the residual convergence index. The determination of the multi-field collaborative convergence state at the current time step using the residual convergence index specifically includes: The norm values ​​of the unbalanced force in the stress field, the mass conservation residual in the fluid field, the energy conservation residual in the thermal field, and the chemical damage evolution residual are calculated respectively. The norm values ​​are then dimensionless, and a residual convergence index including relative and absolute residuals is constructed. The residual convergence index is compared with the preset convergence tolerance threshold. If the residual convergence index of each physical field is less than the convergence tolerance threshold, it is determined that the current time step has reached the multi-field co-convergence state. Conversely, an adaptive time step reduction mechanism is triggered to recalculate the time step by reducing its size. After reaching a multi-field co-convergence state, the disaster-causing evolution characteristics of coal and rock mass under the combined action of stress response and physicochemical damage in the current calculation step are extracted, and the disaster-causing evolution characteristics are input into the preset instability risk assessment model for threshold comparison, and the simulation results are output. The process of inputting disaster-causing evolutionary characteristics into a preset instability risk assessment model for threshold comparison and outputting simulation results specifically includes: After dimensionless processing of the disaster-causing evolution characteristics, the weight coefficients in the preset instability risk assessment model are called to perform weighted summation calculation to generate a comprehensive instability risk index characterizing the current stability of the coal and rock mass. The comprehensive instability risk index is compared with the preset disaster classification threshold range to determine the current instability risk level and output the simulation results.

2. The numerical simulation method for simulating multi-field coupled disasters in coal mines as described in claim 1, characterized in that, The construction of a three-dimensional spatial grid model using geological structural data to characterize the heterogeneous features of coal and rock masses specifically includes: Spatial geometric interpretation and reconstruction of geological structural data are performed to generate a three-dimensional geometric model of the mining area, including coal seams, roof and floor strata, and fault structures. The unstructured meshing technique is used to discretize the three-dimensional geometric model of the mining area, and the mesh is locally refined in the fault fracture zone and the stress concentration zone of the coal seam to generate a three-dimensional spatial mesh model composed of tetrahedral or hexahedral elements. Based on the lithological distribution information in geological structural data, the Weibull distribution probability model and spatial correlation algorithm are used to assign corresponding physical and mechanical parameters to each grid cell in the three-dimensional spatial grid model to characterize the heterogeneous characteristics of coal and rock masses.

3. The numerical simulation method for simulating multi-field coupled disasters in coal mines as described in claim 1, characterized in that, The establishment of a multi-field strongly coupled control equation system on the topological nodes of the three-dimensional spatial mesh model, encompassing the cross-mapping relationships between stress, fluid, thermal energy, and chemical damage, specifically includes: Construct a multiphysics state vector that includes displacement variables, pore pressure variables, temperature variables, and chemical damage variables; Based on the theory of porous media mechanics, a stress field control equation with the effective stress principle as its core is established. Chemical damage variables are introduced into the stress field control equation to correct the elastic modulus and strength parameters of coal and rock mass. The fluid field control equations are established based on Darcy's law and the law of conservation of mass, and the pore deformation term caused by stress field and the permeability evolution term caused by chemical damage are coupled. The thermal field control equations are established based on Fourier's law and the law of conservation of energy, coupled with the thermal convection terms caused by fluid seepage. A chemical damage evolution equation was established based on the theory of chemical reaction kinetics to describe the damage mechanism of chemical solution erosion on the microstructure of coal and rock mass. By combining the above equations, a set of strongly coupled multi-field control equations can be constructed.

4. The numerical simulation method for simulating multi-field coupled disasters in coal mines as described in claim 1, characterized in that, The invocation of the built-in interface conservation constraint operator to perform real-time correction of the energy flux and momentum transfer of the synchronization parameters to be solved during the cross-physics process specifically includes: Extract the state variables of the grid nodes on the interfaces of each physics field within the current time step, and construct the interpolation matrix for cross-physics field variable transmission; Based on the principles of energy conservation and momentum conservation, the deviation between the theoretical flux transfer value and the actual interpolated transfer value of each physical field at the interface is calculated. A Lagrange multiplier constraint equation is constructed with the objective of minimizing the deviation, and the correction coefficient matrix is ​​obtained by solving it. The energy flux and momentum transfer terms transferred across physical fields are compensated and corrected in real time using the correction coefficient matrix, so as to eliminate non-physical dissipation and nonlinear hysteresis bias caused by interpolation errors during the spatiotemporal discretization process of different physical fields.

5. The numerical simulation method for simulating multi-field coupled disasters in coal mines as described in claim 1, characterized in that, The method employs a fully implicit simultaneous solution mechanism to perform inter-field collaborative calculations on the corrected synchronization parameters to be solved, specifically including: Based on the corrected synchronous parameters to be solved, a global unknown vector containing displacement, pore pressure, temperature and chemical damage variables is constructed, and the partial derivatives of the control equations of each physical field to be solved synchronous parameters are derived to construct a global Jacobian matrix that reflects the cross-coupling effect between physical fields. Based on the corrected synchronization parameters to be solved, the Newton-Raphson iterative algorithm is used to linearize the global Jacobian matrix and obtain the incremental solutions for each physical field variable. The incremental solution is superimposed with the initial variable values ​​of the current iteration step, and the state variables of all physical fields are updated synchronously.

6. The numerical simulation method for simulating multi-field coupled disasters in coal mines as described in claim 1, characterized in that, The extraction of disaster-causing evolution characteristics of coal and rock mass under the combined effects of stress response and physicochemical damage within the current calculation step specifically includes: Based on the calculation results after convergence at the current time step, the damage extreme value characteristics of the cumulative chemical damage variable are extracted; Based on the yield criterion, plastic yield elements are identified, the volume of the plastic region is statistically analyzed, and its expansion rate relative to the previous time step is calculated. At the same time, the local energy release rate is calculated in conjunction with the energy dissipation theory. The expansion rate of the plastic zone, the local energy release rate, and the extreme values ​​of the cumulative chemical damage variables are constructed into a multidimensional feature vector, which serves as a disaster-causing evolution characteristic quantity characterizing the precursors of coal and rock mass instability.

7. A numerical simulation system for simulating multi-field coupled disasters in coal mines, employing the numerical simulation method for simulating multi-field coupled disasters in coal mines as described in any one of claims 1-6, characterized in that, include: The simulation data acquisition module, the multi-field coupling equation construction module, the cross-field conservation correction module, the inter-field coordination judgment module, and the simulation result output module are all included. The simulation data acquisition module is used to acquire geological structure data, initial physical field parameters, and simulation step size parameters of the mining area to be simulated. The multi-field coupling equation construction module is used to construct a three-dimensional spatial grid model to characterize the heterogeneous features of coal and rock mass using geological structural data, and to establish a set of multi-field strongly coupled control equations covering the cross-mapping relationship between stress, fluid, thermal energy and chemical damage on the topological nodes of the three-dimensional spatial grid model in combination with the initial physical field parameters. The cross-field conservation correction module is used to enter the iterative calculation based on the time step sequence determined by the simulation step size parameter. Within the current single time step, the state variables of each physical field are defined as the synchronization parameters to be solved, and the built-in interface conservation constraint operator is called to correct the energy flux and momentum transfer of the synchronization parameters to be solved in the cross-physical field transfer process in real time, so as to eliminate the nonlinear lag deviation generated by different physical fields in the spatiotemporal discrete solution process. The inter-field coordination determination module is used to perform inter-field coordination calculation on the corrected synchronous parameters to be solved using a fully implicit simultaneous solution mechanism. By constructing a global Jacobian matrix containing each field component, it realizes the synchronous update of each physical field variable at the same calculation level, and monitors the residual convergence index in real time during the iteration process. The residual convergence index determines the multi-field coordination convergence state at the current time step. The determination of the multi-field collaborative convergence state at the current time step using the residual convergence index specifically includes: The norm values ​​of the unbalanced force in the stress field, the mass conservation residual in the fluid field, the energy conservation residual in the thermal field, and the chemical damage evolution residual are calculated respectively. The norm values ​​are then dimensionless, and a residual convergence index including relative and absolute residuals is constructed. The residual convergence index is compared with the preset convergence tolerance threshold. If the residual convergence index of each physical field is less than the convergence tolerance threshold, it is determined that the current time step has reached the multi-field co-convergence state. Conversely, an adaptive time step reduction mechanism is triggered to recalculate the time step by reducing its size. The simulation result output module is used to extract the disaster-causing evolution characteristics of coal and rock mass under the combined action of stress response and physicochemical damage in the current calculation step after reaching the multi-field collaborative convergence state, and input the disaster-causing evolution characteristics into the preset instability risk assessment model for threshold comparison, and output the simulation results. The process of inputting disaster-causing evolutionary characteristics into a preset instability risk assessment model for threshold comparison and outputting simulation results specifically includes: After dimensionless processing of the disaster-causing evolution characteristics, the weight coefficients in the preset instability risk assessment model are called to perform weighted summation calculation to generate a comprehensive instability risk index characterizing the current stability of the coal and rock mass. The comprehensive instability risk index is compared with the preset disaster classification threshold range to determine the current instability risk level and output the simulation results.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium contains program code that can be invoked by a processor to execute the method as described in any one of claims 1-6.

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