Heterogeneous rock difference damage thermal coupling modeling method, device and equipment

Abstract

The application discloses a heterogeneous rock differential damage thermal force coupling modeling method, device and equipment, relates to the rock mechanics technical field, and can construct a thermal force coupling model covering multiple temperature conditions, realizes accurate analysis on the thermal force response of rock. Including: obtaining the geometric structure characteristic parameters of the rock and constructing a rock geometric model; dividing every two adjacent particles in the rock geometric model into intracrystalline contact pairs or intercrystalline contact pairs, simulating the bonding behavior of the intracrystalline contact pairs, simulating the interface slip behavior of the intercrystalline contact pairs, and constructing a rock mechanics model based on the simulation results; constructing temperature-dependent functions of multiple key thermal parameters of the rock; embedding each temperature-dependent function into the rock mechanics model to obtain a thermal force coupling model considering thermal damage variables, and performing thermal force coupling analysis on the rock based on the thermal force coupling model. The application is mainly applied to the thermal force coupling analysis scene of the rock.

Description

Technical Field

[0001] This invention relates to the field of rock mechanics, and in particular to a method, apparatus and equipment for thermo-mechanical coupling modeling of differential damage in heterogeneous rocks. Background Technology

[0002] As people delve deeper into the exploration of underground resources, the need to comprehensively and multi-dimensionally understand the internal structure and mechanical properties of rocks in order to accurately predict and assess the bearing capacity, stability, and engineering risks of rock masses is becoming an urgent requirement in fields such as deep mineral mining, tunnel and underground space construction, and energy reservoir transformation.

[0003] Currently, thermal parameters of rocks are typically treated as constants to construct thermo-mechanical coupling models for subsequent thermo-mechanical coupling analysis. However, these models can only be used for thermo-mechanical coupling analysis of rocks under fixed, constant temperature conditions. In actual engineering projects, underground conditions are unstable, and temperatures change in real time. Therefore, thermo-mechanical coupling models constructed using fixed temperature conditions cannot accurately reflect the thermal response of rocks under actual working conditions. Summary of the Invention

[0004] This invention provides a method, apparatus, and equipment for thermo-mechanical coupling modeling of differential damage in heterogeneous rocks. The main feature is that it can accurately construct a thermo-mechanical coupling model covering multiple temperature conditions, thereby enabling accurate analysis of the thermo-mechanical response of rocks under actual working conditions.

[0005] According to a first aspect of the present invention, a method for thermo-mechanical coupling modeling of differential damage in heterogeneous rocks is provided, comprising:

[0006] Obtain the geometric structural feature parameters of the target heterogeneous rock, and construct a rock geometric model of the target heterogeneous rock based on the geometric structural feature parameters;

[0007] Based on the type of each particle in the rock geometry model, every two adjacent particles are divided into intracrystalline contact pairs or intercrystalline contact pairs. The intracrystalline contact pairs are simulated for internal crystal bonding behavior, and the intercrystalline contact pairs are simulated for intercrystalline interface slip behavior. Based on the simulation results of intracrystalline bonding behavior and intercrystalline interface slip behavior, a rock mechanics model of the target heterogeneous rock is constructed. In the case of the two adjacent particles in the intracrystalline contact pairs, the particle types are the same, and the particle types of the two adjacent particles in the intercrystalline contact pairs are different.

[0008] The temperature dependence functions of several key thermal parameters of the target heterogeneous rock are constructed, wherein the temperature dependence functions of several key thermal parameters include the thermal expansion coefficient function, the thermal resistance function and the friction coefficient function with temperature as the independent variable;

[0009] The temperature dependence function of each key thermal parameter is embedded into the rock mechanics model to obtain a thermo-mechanical coupling model that considers thermal damage variables, and a thermo-mechanical coupling analysis is performed on the target heterogeneous rock based on the thermo-mechanical coupling model.

[0010] Optionally, constructing the rock geometric model of the target heterogeneous rock based on the geometric structural feature parameters includes:

[0011] The model construction region of the rock geometric model is determined based on the geometric structural feature parameters. At least one initial particle is randomly generated in the model construction region, and geometric attribute information and spatial position coordinates are assigned to each initial particle based on the size information of the model construction region to obtain intermediate particles.

[0012] A spatial segmentation reference point set is constructed based on the center coordinates of each intermediate particle. The model construction region is segmented into multiple non-overlapping polyhedral units based on the spatial segmentation reference point set, and each polyhedral unit is instantiated as a rigid block unit.

[0013] Based on the mineral types and relative content ratios of the target heterogeneous rock, each rigid block unit is classified, and the rigid block units under different categories are mapped to target geometric regions of different mineral types. The intermediate particles are removed in the model construction area, and only the boundary contours of the target geometric regions are retained. The boundary contours of the target geometric regions are used as hollow geometric containers.

[0014] The target mineral type corresponding to each hollow geometric container is determined, and the particle attribute information of the particles required to constitute the target mineral type in the target heterogeneous rock is determined. Based on the particle attribute information, secondary filling particles are generated and filled in the corresponding hollow geometric container, and the secondary filling particles are given physical and mechanical properties that match the target mineral type to obtain the rock geometric model of the target heterogeneous rock.

[0015] Optionally, the simulation of the intracrystalline bonding behavior of the intracrystalline contact pairs includes:

[0016] The linear parallel bond model constructor is called to establish a linear parallel bond contact instance on the intracrystalline contact pair, the first mechanical parameter information between the intracrystalline contact pair is determined, and the first mechanical parameter information is written into the attribute field of the linear parallel bond contact instance to obtain the simulation results of the bonding behavior inside the crystal.

[0017] The simulation of the intercrystalline interface slip behavior of the intercrystalline contact pairs includes:

[0018] The smooth joint model constructor is called to establish a smooth joint contact instance on the intercrystalline contact pair, the second mechanical parameter information between the intercrystalline contact pairs is determined, and the second mechanical parameter information is written into the attribute field of the smooth joint contact instance to obtain the simulation results of the intercrystalline interface slip behavior.

[0019] The rock mechanics model of the target heterogeneous rock is constructed based on the simulation results of the internal bonding behavior of crystals and the simulation results of the intercrystalline interface slip behavior, including:

[0020] In each particle of the rock geometry model, suspended particles that have not established contact instances with any neighboring particles are identified, and these suspended particles are removed from the rock geometry model. Based on the rock geometry model after removing the suspended particles, the simulation results of the internal bonding behavior of crystals, and the simulation results of the intercrystalline interface slip behavior, a rock mechanics model of the target heterogeneous rock is constructed.

[0021] Optionally, the temperature dependence function for constructing multiple key thermal parameters of the target heterogeneous rock includes:

[0022] Construct each mineral composition in the target heterogeneous rock separately. An initial function for the coefficient of thermal expansion is obtained, and a sample dataset of the coefficient of thermal expansion is acquired. Based on the sample dataset, each undetermined coefficient of thermal expansion in the initial function is solved. Based on the solution results of the undetermined coefficients of thermal expansion, the initial function is constructed to represent the corresponding mineral composition. The thermal expansion coefficient function, wherein the thermal expansion coefficient sample dataset includes the thermal expansion coefficients of different mineral components at different temperatures, and the mineral components... Thermal expansion coefficient function based on temperature T for: , For temperature, , , These are the solution values ​​for each undetermined coefficient of thermal expansion. Mineral components Mineral-specific normalized parameters;

[0023] Construct each mineral composition in the target heterogeneous rock separately. An initial thermal resistance function is derived, a thermal resistance sample dataset is obtained, and the undetermined coefficients of thermal resistance in the initial thermal resistance function are solved based on the thermal resistance sample dataset. Based on the solution results of the undetermined thermal resistance coefficients, the initial thermal resistance function is constructed to correspond to the mineral composition. The thermal resistance function, wherein the thermal resistance sample dataset includes the thermal resistance of different mineral compositions at different temperatures, and the mineral compositions... Thermal resistance function based on temperature T for: , For reference thermal resistance, Mineral components The growth rate;

[0024] Construct each mineral composition in the target heterogeneous rock separately. An initial friction coefficient function is derived, a friction coefficient sample dataset is obtained, and the undetermined coefficients of each friction coefficient in the initial friction coefficient function are solved based on the friction coefficient sample dataset. Based on the solution results of the undetermined friction coefficient coefficients, the initial friction coefficient function is constructed to correspond to the mineral composition. The friction coefficient function, wherein the friction coefficient sample dataset includes friction coefficients of different mineral compositions at different temperatures, and the mineral compositions... Friction coefficient function based on temperature T for: , As the reference friction coefficient, , , , The solution value is the coefficient of friction, which is the undetermined coefficient. For temperature-dependent growth rate, This represents the temperature rise.

[0025] Optionally, before embedding the temperature dependence function of each of the key thermal parameters into the rock mechanics model to obtain a thermo-mechanical coupling model considering thermal damage variables, the method further includes:

[0026] Obtain the overall macroscopic elastic modulus of the target heterogeneous rock, the mapping relationship between the overall macroscopic elastic modulus of the rock and the microscopic stiffness of the rock, determine the global reference stiffness value based on the overall macroscopic elastic modulus of the rock and the mapping relationship, and assign the global reference stiffness value as the initial stiffness parameter and the preset high strength parameter to all mineral components of the rock mechanics model respectively.

[0027] The elastic response proportionality coefficient between the micro-elastic modulus of each mineral component in the rock mechanics model and the macro-elastic modulus of the rock as a whole is determined. Based on the elastic response proportionality coefficient, the initial stiffness parameter of each mineral component in the rock mechanics model is iteratively optimized. Based on the iterative optimization result, the ultimate stiffness parameter of each mineral component is determined. Based on the ultimate stiffness parameter, the calibration elastic parameter of the corresponding mineral component is determined. The elastic parameter calibration of each mineral component in the rock mechanics model is performed using the calibration elastic parameter.

[0028] The stress-strain curve of the rock mechanics model after elastic parameter calibration is determined, the simulated peak intensity in the stress-strain curve is extracted, the preset high strength parameter is iteratively adjusted based on the difference between the simulated peak intensity and the preset standard peak intensity, the calibration strength parameter is determined based on the iterative adjustment result, and the strength parameter is calibrated by the calibrated strength parameter to obtain the rock mechanics model after mechanical parameter calibration.

[0029] Optionally, after calibrating the rock mechanics model with calibrated elastic parameters using the calibrated strength parameters to obtain the rock mechanics model with calibrated mechanical parameters, the method further includes:

[0030] The mechanical parameter verification scenarios of the rock mechanics model after mechanical parameter calibration are determined, wherein the mechanical parameter verification scenarios include a preset number of mutually independent and unequal principal stress constraint scenarios and isothermal boundary condition scenarios.

[0031] In the mechanical parameter verification scenario, the rock mechanics model after mechanical parameter calibration is subjected to mechanical response simulation. Based on the mechanical response simulation, mechanical response prediction data is determined. In the mechanical parameter verification scenario, mechanical response test is conducted on the target heterogeneous rock. Based on the mechanical response test results, mechanical response physical data is determined. Based on the mechanical response prediction data and the mechanical response physical data, the mechanical parameter calibration effect of the rock mechanics model is determined.

[0032] Optionally, the thermo-mechanical coupling analysis of the target heterogeneous rock based on the thermo-mechanical coupling model includes:

[0033] The initial temperature, target arrival temperature, and temperature change interval of the simulated temperature field are determined. Based on the initial temperature, target arrival temperature, and temperature change interval, the thermo-mechanical coupling model is used to perform thermal and mechanical analysis of the target heterogeneous rock under multiple temperature gradients.

[0034] According to a second aspect of the present invention, a thermo-mechanical coupling modeling apparatus for differential damage in heterogeneous rocks is provided, comprising:

[0035] A geometric model construction unit is used to obtain the geometric structural feature parameters of the target heterogeneous rock and construct a rock geometric model of the target heterogeneous rock based on the geometric structural feature parameters.

[0036] The mechanical model construction unit is used to divide every two adjacent particles into intracrystalline contact pairs or intercrystalline contact pairs based on the type of each particle in the rock geometry model, simulate the internal bonding behavior of the intracrystalline contact pairs, simulate the intercrystalline interface slip behavior of the intercrystalline contact pairs, and construct the rock mechanical model of the target heterogeneous rock based on the simulation results of the internal bonding behavior and the simulation results of the intercrystalline interface slip behavior. In the case of the two adjacent particles in the intracrystalline contact pairs having the same particle type, the two adjacent particles in the intercrystalline contact pairs having different particle types.

[0037] The function construction unit is used to construct temperature dependence functions for multiple key thermal parameters of the target heterogeneous rock, wherein the temperature dependence functions for multiple key thermal parameters include a thermal expansion coefficient function, a thermal resistance function, and a friction coefficient function with temperature as the independent variable.

[0038] The coupling analysis unit is used to embed the temperature dependence function of each key thermal parameter into the rock mechanics model to obtain a thermo-mechanical coupling model that considers thermal damage variables, and to perform thermo-mechanical coupling analysis on the target heterogeneous rock based on the thermo-mechanical coupling model.

[0039] According to a third aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the above-described method for thermo-coupling modeling of differential damage in heterogeneous rocks.

[0040] According to a fourth aspect of the present invention, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described method for thermo-mechanical coupling modeling of differential damage in heterogeneous rocks.

[0041] The present invention provides a method, apparatus, and equipment for thermo-mechanical coupling modeling of differential damage in heterogeneous rocks. Compared with the current method of constructing a thermo-mechanical coupling model by treating the thermal parameters of rocks as constants and then conducting thermo-mechanical coupling analysis of rocks, the present invention obtains geometric structural characteristic parameters and constructs a rock geometric model, which can accurately describe the internal structure of the target heterogeneous rock. This provides an accurate geometric basis for subsequent mechanical and thermal analysis, enabling the model to more realistically reflect the actual situation of the rock and improve the reliability of the analysis results. Since the bonding behavior inside crystals and the slip behavior at the interface between crystals are important factors affecting the mechanical properties of rocks, the present invention simulates these two behaviors separately, which can consider the interaction mechanism inside the rock in more detail, making the rock mechanical model more consistent with reality. By constructing temperature dependence functions of key thermal parameters and embedding them into the rock mechanical model, the thermal and mechanical behavior of rocks at different temperatures can be described more accurately, improving the accuracy of the coupling model construction and thus improving the accuracy of the thermo-mechanical coupling analysis results of rocks. Attached Figure Description

[0042] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0043] Figure 1 The flowchart of a thermo-mechanical coupling modeling method for differential damage in heterogeneous rocks provided by an embodiment of the present invention is shown.

[0044] Figure 2 This invention provides a flowchart of another method for thermo-mechanical coupling modeling of differential damage in heterogeneous rocks.

[0045] Figure 3 This diagram illustrates the structure of a thermo-mechanical coupling modeling device for differential damage in heterogeneous rocks, provided in an embodiment of the present invention.

[0046] Figure 4 This invention provides a schematic diagram of another thermo-mechanical coupling modeling device for differential damage in heterogeneous rocks.

[0047] Figure 5 A schematic diagram of the physical structure of a computer device provided in an embodiment of the present invention is shown. Detailed Implementation

[0048] The present invention will be described in detail below with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in the present application can be combined with each other.

[0049] Currently, the thermal parameters of rocks are usually treated as constants to construct thermo-mechanical coupling models and then conduct thermo-mechanical coupling analysis of rocks. However, in actual engineering, underground conditions are unstable and temperatures change in real time. Therefore, thermo-mechanical coupling models constructed using fixed thermal parameters cannot accurately reflect the thermal response of rocks under actual working conditions.

[0050] To address the aforementioned problems, embodiments of the present invention provide a method for thermo-mechanical coupling modeling of differential damage in heterogeneous rocks, such as... Figure 1 As shown, the method includes:

[0051] 101. Obtain the geometric structural feature parameters of the target heterogeneous rock, and construct a rock geometric model of the target heterogeneous rock based on the geometric structural feature parameters.

[0052] The geometric structural characteristic parameters include, but are not limited to, the type and geometric size of the target heterogeneous rock, the type, content, spatial distribution, grain size, shape factor and pore structure data of the mineral particles inside the rock; the target heterogeneous rock can be any heterogeneous rock.

[0053] In this embodiment of the invention, geometric structural characteristic parameters such as the spatial distribution, particle size, shape factor, and pore structure of mineral particles within the rock are acquired through high-resolution computed tomography, scanning electron microscopy, or thin-section microscopy. Simultaneously, the geometric dimensions of the rock can be measured using measuring tools. Key geometric structural characteristic parameters characterizing the heterogeneity of the rock are extracted using these methods. Furthermore, in a discrete element numerical simulation environment, based on the statistically obtained geometric structural characteristic parameters, sets of spherical or polygonal particles with different radii and spatial positions are randomly generated within a preset computational domain. By adjusting the contact relationships and packing density between particles, a heterogeneous rock geometric model that reflects the true mineral composition, particle composition, and microscopic topology of the rock is reconstructed, providing an accurate geometric framework for subsequent assignment of differentiated physical and mechanical parameters and thermo-mechanical coupling analysis.

[0054] 102. Based on the type of each particle in the rock geometry model, each pair of adjacent particles is divided into intracrystalline contact pairs or intercrystalline contact pairs. The internal bonding behavior of intracrystalline contact pairs is simulated, and the intercrystalline interface slip behavior of intercrystalline contact pairs is simulated. Based on the simulation results of the internal bonding behavior and the intercrystalline interface slip behavior, a rock mechanics model of the target heterogeneous rock is constructed. In the case of intracrystalline contact pairs, the two adjacent particles have the same particle type, while in intercrystalline contact pairs, the two adjacent particles have different particle types.

[0055] In this embodiment of the invention, all adjacent particle pairs in the rock geometry model are traversed to determine the mineral type of each particle. If two adjacent particles have the same mineral type, they are defined as intracrystalline contact pairs, representing a continuous medium region inside the mineral crystal. If two adjacent particles have different mineral types, they are defined as intercrystalline contact pairs, representing the interface or weak surface region between different mineral crystals. For the above two types of contact pairs, contact constitutive models and parameter sets that conform to their physical mechanisms are assigned respectively: For intracrystalline contact pairs: a high-strength bonding model, such as a linear parallel bonding model, is used for simulation. During the simulation, higher normal / tangential bonding strength and stiffness parameters are set to characterize the strong connection characteristics of atomic bonding inside the crystal and simulate elastic deformation and transgranular fracture behavior inside the crystal. For intercrystalline contact pairs: an interface slip weakening model, such as a smooth joint model, is used for simulation. During the simulation, relatively lower bonding strength, a specific friction coefficient, and interface stiffness are set to characterize the structural weakness characteristics at the grain boundaries and prioritize the simulation of debonding, slip, and shear failure behaviors along the grain boundaries. Subsequently, all contact pairs exhibiting elastic deformation, transgranular fracture behavior, debonding, slip, and shear failure behavior are integrated into a discrete element method (DEM) framework to form the final rock mechanics model of the target heterogeneous rock. For example, a linear parallel bond model is used to simulate the mechanical behavior of intragranular grains, and a smooth joint model is used to simulate the mechanical response of intergranular contacts, thereby constructing a pure mechanical analysis model for heterogeneous rocks. This model can naturally exhibit complex failure modes controlled by microscopic grain boundary slip and intragranular fracture on a macroscopic scale, realistically reflecting the mechanical response characteristics of heterogeneous rocks under anisotropic stress. Since intragranular bonding behavior and intergranular interface slip behavior are important influencing factors of rock mechanical properties, this invention, by simulating these two behaviors separately, can consider the internal interaction mechanisms of rocks in more detail, making the rock mechanics model more realistic.

[0056] 103. Construct temperature dependence functions for multiple key thermal parameters of the target heterogeneous rock, including the thermal expansion coefficient function, thermal resistance function, and friction coefficient function with temperature as the independent variable.

[0057] Among them, several key thermal parameters include, but are not limited to, the coefficient of thermal expansion, thermal resistance, and coefficient of friction.

[0058] In this embodiment of the invention, firstly, based on high-temperature physical test data or authoritative literature of each mineral component in the target rock, discrete data points of the thermal expansion coefficient, contact thermal resistance, and friction coefficient as a function of temperature are extracted. Based on this data point set, the least squares method or nonlinear regression analysis is used to establish the mathematical fitting relationship between each parameter and temperature. The thermal expansion coefficient function describes the nonlinear growth law of mineral lattice thermal expansion with increasing temperature, especially covering the abrupt change characteristics of the phase transition temperature point; the thermal resistance function characterizes the evolution trend of dynamic increase in interparticle contact thermal resistance with increasing temperature and microcrack initiation and propagation, reflecting the damage and degradation of the heat conduction path; the friction coefficient function characterizes the softening or hardening behavior of the contact surface friction characteristics as temperature increases, simulating the dynamic decay of the interface shear strength at high temperatures.

[0059] 104. The temperature dependence function of each key thermal parameter is embedded into the rock mechanics model to obtain a thermo-mechanical coupling model that considers thermal damage variables, and thermo-mechanical coupling analysis is performed on the target heterogeneous rock based on the thermo-mechanical coupling model.

[0060] In this embodiment of the invention, the temperature dependence function of each key thermal parameter is encapsulated as a material constitutive subroutine and embedded into the rock mechanics model. In each iteration of the thermo-mechanical coupling analysis, the model automatically calls and updates the corresponding thermal parameter values ​​based on the current real-time temperature field, thereby achieving a full-process dynamic coupling simulation where temperature changes drive parameter evolution, and parameter evolution feeds back to the mechanical response. Specifically, within the discrete element method (DEM) framework, the temperature dependence functions of the coefficient of thermal expansion, contact thermal resistance, and friction coefficient are used as dynamic attributes and assigned to the particle and contact elements in the mechanical model, respectively, achieving deep integration of multiple physics fields. For example, during the simulation, the coefficient of thermal expansion function is called based on the real-time temperature of the particles to calculate instantaneous thermal strain and convert it into thermal stress. Due to the differences in the thermal expansion characteristics of different mineral particles, the mechanical model automatically generates microscopic stress concentrations at the heterogeneous interface caused by thermal expansion mismatch, simulating the initial damage caused by thermal shock. When thermal stress causes the contact pair to crack or slip, the damage variable is updated in real time. Simultaneously, the damage variable is substituted as a key parameter into the contact thermal resistance function, causing the thermal resistance at crack initiation to dynamically increase as damage intensifies. This mechanism simulates the reduction in contact area and air gap insulation effect caused by microcrack opening, thereby altering the local heat conduction path and forming a two-way positive feedback loop: temperature rise induces cracking, cracking intensifies and hinders heat transfer, and local overheating further promotes damage. In the mechanical assessment of the contact interface, the friction coefficient temperature dependence function is called in real time to accurately simulate the macroscopic mechanical property degradation caused by the natural decay of intergranular friction strength under high-temperature conditions.

[0061] Furthermore, after constructing the thermo-mechanical coupling model considering thermal damage variables, a thermo-mechanical coupling analysis of the rock needs to be performed based on this model. Specifically, based on the current contact thermal resistance network distribution, the heat conduction equation is solved, the temperature field distribution information of all particles is updated, and all particles and contact pairs in the mechanical model are traversed. Based on the latest temperature field state and the current damage degree, key thermal parameters such as the coefficient of thermal expansion, contact thermal resistance, and friction coefficient are updated in real time. Based on the updated parameters, the thermal load and contact force are calculated, and dynamic equilibrium iteration is performed to solve for the particle displacement, velocity, and contact stress state. Then, it is checked whether the stress state of each particle contact pair exceeds the strength criterion that varies with temperature. If so, newly formed microcracks are marked, the thermal damage variables are updated, and the crack type is recorded. The above solution and update steps are repeated until the preset maximum temperature loading endpoint is reached or the rock experiences macroscopic instability and failure. Through the above coupling analysis, multiphysics response data of the target heterogeneous rock under the entire temperature history are output. During the coupled analysis, the spatiotemporal evolution path of microcracks from grain boundary initiation and propagation to the formation of macroscopic cracks can be visually displayed, clearly distinguishing the failure mode dominated by thermal damage. It can also generate stress-strain relationship curves, peak strength degradation patterns, elastic modulus variation trends, and permeability evolution characteristics of rocks at different high-temperature thresholds. By constructing temperature-dependent functions of key thermal parameters and embedding them into the rock mechanics model, this invention can more accurately describe the thermal and mechanical behavior of rocks at different temperatures, improving the accuracy of the coupled model construction and thus enhancing the accuracy of the thermo-mechanical coupled analysis results of rocks.

[0062] In another embodiment of the present invention, to further overcome the shortcomings of neglecting the effect of dynamic evolution of crack geometry on heat conduction blocking when thermal resistance parameters only change with temperature, a method for dynamically correcting contact thermal resistance based on real-time crack opening is proposed. The method includes: establishing a dynamic mapping mechanism between contact thermal resistance and microcrack opening during thermo-coupling analysis of rocks based on a thermo-coupling model; monitoring the normal relative displacement of all intergranular contact pairs and damaged intragranular contact pairs in the rock mechanics model in real time within each calculation step of the thermo-coupling analysis, defining it as the real-time crack opening; constructing a dynamic composite thermal resistance function based on the real-time crack opening, the instantaneous temperature value of the current temperature field, and a preset crack surface radiation coefficient; and using the dynamic composite thermal resistance function to adjust the contact thermal resistance of the intergranular contact pairs and damaged intragranular contact pairs. The resistance is corrected in real time. When the real-time crack opening is less than the preset contact threshold set according to actual needs, the dominant term is the temperature-based contact conduction thermal resistance. When the real-time crack opening is greater than or equal to the preset contact threshold, the dominant term switches to a parallel combination of temperature-based gap radiation thermal resistance and residual contact thermal resistance. The corrected contact thermal resistance is updated in the heat conduction matrix of the thermo-mechanical coupling model, and the temperature field distribution is resolved. This drives the next step of thermal expansion strain calculation and damage evolution, realizing a full-process dynamic closed-loop feedback of temperature-induced cracking, cracking changing thermal resistance, and thermal resistance reconstructing the temperature field.

[0063] Specifically, in each calculation step of the thermo-coupling model, all contact pairs in the rock mechanics model are traversed, especially intergranular contact pairs and intragranular contact pairs that have undergone tensile or shear failure. The real-time spatial coordinates of the centers of each pair of adjacent particles are determined, and their current normal distance is calculated. The difference between the current normal distance and the sum of the initial radii of the particles is defined as the real-time crack opening of the contact pair. If the difference is negative, it indicates that the particles are in an overlapping compression state, and the real-time crack opening is zero. If the difference is positive, it indicates that the crack has opened, and the real-time crack opening is the physical width of the crack. Based on the magnitude of the real-time crack opening, the contact pair is marked as either a close contact state or a crack-open state. A dynamic composite thermal resistance function is constructed based on the monitored real-time crack opening and the current particle temperature. This function consists of two parts and automatically switches the dominant mechanism according to the crack state. The first case: the corrected contact thermal resistance under the close contact state, i.e., when the real-time crack opening... Less than the preset micro-contact threshold At this time, heat is mainly conducted through the solid contact points, and the thermal resistance is... The expression is as follows:

[0064]

[0065] in, Given the current time t, current temperature T, and current crack opening... The actual contact thermal resistance is as follows. This is the basic contact thermal resistance function at the current temperature T (i.e., a pre-constructed thermal resistance function with temperature as the independent variable). This is the sensitivity coefficient for micro-gap. The second case: the combined thermal resistance under crack opening conditions, i.e., the thermal resistance when the real-time crack opening... Greater than or equal to the preset microscopic contact threshold At this point, the solid-to-solid contact conduction path is essentially severed, and heat transfer transforms into conduction through the gas within the crack and thermal radiation between the crack surfaces. The thermal resistance at this stage... The expression is as follows:

[0066]

[0067] in, Given the current temperature T and the current crack opening The equivalent composite thermal resistance is as follows: To depend solely on crack opening The thermal resistance of the gas. Given the current temperature T and the current crack opening The calculated reciprocal of the thermal resistance, i.e., the thermal conductance, is then written into the corresponding position of the global thermal conduction matrix of the coupled model in real time. For newly generated microcracks, the thermal resistance value jumps instantaneously, causing a sharp decrease in heat flux along that path. Based on the updated thermal conduction matrix, the temperature field equation for the next moment is solved. Due to the increased thermal resistance at the crack, heat cannot pass smoothly through the crack band, leading to heat accumulation at the crack tip or in the crack-closed region, forming local hotspots. The formation of local hotspots will again invoke the thermal expansion coefficient function, generating larger non-uniform thermal expansion strain, thereby increasing crack opening or inducing new secondary cracks. In this way, the coupled model realizes a positive feedback loop of temperature rise – thermal stress concentration – crack opening – sharp increase in thermal resistance – local overheating – increased damage. This invention addresses the problem of delayed or overly simplified thermal resistance changes after crack formation in traditional models by introducing real-time crack opening as a key variable for thermal resistance correction. Based on the original temperature-dependent function, it further integrates the dynamic control of thermal parameters by microscopic geometric deformation, thus constructing a more faithful thermo-mechanical coupling model for heterogeneous rocks.

[0068] The present invention provides a thermo-mechanical coupling modeling method for differential damage in heterogeneous rocks. Compared with the current method of treating the thermal parameters of rocks as constants to construct a thermo-mechanical coupling model and then conducting thermo-mechanical coupling analysis of rocks, the present invention obtains geometric structural characteristic parameters and constructs a rock geometric model, which can accurately describe the internal structure of the target heterogeneous rock. This provides an accurate geometric basis for subsequent mechanical and thermal analysis, enabling the model to more realistically reflect the actual situation of the rock and improve the reliability of the analysis results. Since the bonding behavior inside crystals and the slip behavior at the interface between crystals are important factors affecting the mechanical properties of rocks, the present invention simulates these two behaviors separately, which can more meticulously consider the interaction mechanism inside the rock, making the rock mechanical model more realistic. By constructing temperature dependence functions of key thermal parameters and embedding them into the rock mechanical model, the thermal and mechanical behavior of rocks at different temperatures can be described more accurately, improving the accuracy of the coupling model construction and thus improving the accuracy of the thermo-mechanical coupling analysis results of rocks.

[0069] Furthermore, to better illustrate the process of thermo-mechanical coupling modeling of differential damage in heterogeneous rocks, as a refinement and extension of the above embodiments, this invention provides another method for thermo-mechanical coupling modeling of differential damage in heterogeneous rocks, such as... Figure 2 As shown, the method includes:

[0070] 201. Obtain the geometric structural feature parameters of the target heterogeneous rock, and construct a rock geometric model of the target heterogeneous rock based on the geometric structural feature parameters.

[0071] In this embodiment of the invention, to perform thermo-coupling analysis on the rock, a geometric model of the rock needs to be constructed first. Therefore, step 201 specifically includes: determining the model construction region of the rock geometric model based on the geometric structural feature parameters; randomly generating at least one initial particle in the model construction region; and assigning geometric attribute information and spatial coordinates to each initial particle based on the size information of the model construction region to obtain intermediate particles; constructing a spatial segmentation reference point set based on the center coordinates of each intermediate particle; dividing the model construction region into multiple non-overlapping polyhedral units based on the spatial segmentation reference point set; and instantiating each polyhedral unit as a rigid block unit; based on the mineral types and mineral composition of the target heterogeneous rock... The relative content ratio of the materials is used to classify each rigid block unit, and the rigid block units under different categories are mapped to target geometric regions of different mineral types. The intermediate particles are removed in the model construction region, and only the boundary contour of the target geometric region is retained. The boundary contour of the target geometric region is used as a hollow geometric container. The target mineral type corresponding to each hollow geometric container is determined, and the particle attribute information of the particles required to constitute the target mineral type in the target heterogeneous rock is determined. Based on the particle attribute information, secondary filling particles are generated and filled in the corresponding hollow geometric container, and the secondary filling particles are given physical and mechanical properties that match the target mineral type to obtain the rock geometric model of the target heterogeneous rock.

[0072] The geometric attribute information includes the particle's geometric size, shape, radius, density, porosity, etc.; the particle attribute information includes, but is not limited to, particle type, quantity, weight, particle content, content ratio between different particles, particle structure, particle size; the physical and mechanical properties include, but are not limited to, porosity, damping coefficient, radius range, elastic modulus, Poisson's ratio, density, thermal parameters, etc.

[0073] Specifically, firstly, based on the acquired geometric structural feature parameters, the macroscopic construction region and its size information of the rock geometric model are determined. Within this construction region, at least one initial particle is generated using a random distribution algorithm. Subsequently, according to the boundary size constraints of the construction region, each initial particle is assigned specific geometric attributes, such as radius or equivalent diameter, and precise spatial coordinates, thus forming a set of intermediate particles for subsequent spatial segmentation. Using the center coordinates of all intermediate particles as the reference point set for spatial segmentation, a spatial partitioning algorithm is used to segment the entire model construction region into multiple non-overlapping, closely packed polyhedral units. The shape of each polyhedral unit is determined by the perpendicular bisector of adjacent reference points, realistically reflecting the natural mosaic relationship between mineral grains. Subsequently, these polyhedral units are instantiated into independent rigid block units, constituting the macroscopic mineral skeleton of the rock. Based on the mineral composition and relative content ratio of each mineral in the target heterogeneous rock, the rigid block units are classified and labeled. Rigid block units belonging to the same category are merged and mapped to the target geometric region corresponding to the mineral type. Next, all previously generated intermediate particles are removed from the model construction area, retaining only the boundary contours of the target geometric region enclosed by rigid block units of different types. These boundary contours together constitute multiple independent hollow geometric containers, the internal space of each container being the mineral grain region to be filled. For each hollow geometric container, its corresponding target mineral type is first determined. Then, the required particle attribute information for this target mineral type at the microscale is consulted or set, such as particle size distribution, shape factor, particle type, particle content, and the content ratio between different particles. Based on this attribute information, secondary filling particles are regenerated and densely filled inside the corresponding hollow geometric container. Finally, these secondary filling particles are assigned physical and mechanical properties matching their target mineral type, such as elastic modulus, Poisson's ratio, density, and thermal parameters. After completing the filling and attribute assignment of all hollow geometric containers, all secondary filling particles and their contact relationships are integrated as a whole, ultimately obtaining a rock geometric model that reflects the mineral type, content ratio, and microstructural characteristics of the target heterogeneous rock. This model preserves the spatial topological relationship of mineral grains on a macroscopic level, while also possessing the deformable characteristics of discrete particles on a microscopic level, laying a geometric foundation for subsequent high-precision thermo-mechanical coupling analysis.

[0074] 202. Based on the type of each particle in the rock geometry model, each pair of adjacent particles is divided into intracrystalline contact pairs or intercrystalline contact pairs. The intracrystalline contact pairs are simulated for internal bonding behavior, and the intercrystalline contact pairs are simulated for intercrystalline interface slip behavior. Based on the simulation results of intracrystalline bonding behavior and intercrystalline interface slip behavior, a rock mechanics model of the target heterogeneous rock is constructed. In the case of intracrystalline contact pairs, the two adjacent particles have the same particle type, while in intercrystalline contact pairs, the two adjacent particles have different particle types.

[0075] In this embodiment of the invention, all contacting particle pairs in the rock geometry model are detected. For each pair of adjacent particles, the mineral types to which they belong are compared. If the two adjacent particles belong to the same mineral type, the contact pair is determined to be an intracrystalline contact pair, representing the bonding interface inside the mineral crystal. If the two adjacent particles belong to different mineral types, the contact pair is determined to be an intercrystalline contact pair, representing the bonding interface between different mineral crystals. Furthermore, in order to construct the mechanical model, it is also necessary to simulate the internal bonding behavior of intracrystalline contact pairs and the intercrystalline interface slip behavior of intercrystalline contact pairs. Based on this, the method includes: calling the linear parallel bond model constructor to establish linear parallel bond contact instances on the intracrystalline contact pairs, determining the first mechanical parameter information between the intracrystalline contact pairs, and writing the first mechanical parameter information into the attribute field of the linear parallel bond contact instance to obtain the simulation result of the internal bonding behavior of the crystal; calling the smooth joint model constructor to establish smooth joint contact instances on the intercrystalline contact pairs, determining the second mechanical parameter information between the intercrystalline contact pairs, and writing the second mechanical parameter information into the attribute field of the smooth joint contact instance to obtain the simulation result of the intercrystalline interface slip behavior.

[0076] Specifically, in the simulation of intracrystalline bonding behavior, for adjacent particle combinations identified as intracrystalline contact pairs, the linear parallel bond model constructor is invoked to establish a linear parallel bond contact instance on each intracrystalline contact pair. This linear parallel bond model consists of linear contact elements and parallel bonding elements, which work together to simulate the mechanical behavior between particles within the mineral crystal, such as deformation, fragmentation, and microcracks. This linear parallel bond model can simultaneously transmit normal force, tangential force, bending moment, and torque, effectively simulating the rigid connection between atoms within the crystal. Then, the first mechanical parameter information characterizing the bonding strength within the crystal is determined. This first mechanical parameter information includes, but is not limited to, normal stiffness, tangential stiffness, parallel bond radius, normal strength, and tangential strength. This first mechanical parameter information is written into the attribute fields of the established linear parallel bond contact instance to complete parameter binding. The simulation results obtained thus accurately reflect the transgranular fracture behavior of rocks under stress, i.e., the phenomenon of cracks directly penetrating the interior of mineral particles.

[0077] Meanwhile, in the simulation of intergranular interface slip behavior, for adjacent particle combinations identified as intergranular contact pairs, the smooth joint model allows relative slippage of the contact surface in a specific direction, unrestricted by the interlocking geometry of the particles. This model simulates frictional slip at grain boundaries, completely preserving all mechanical properties between particles except for the dip angle. Furthermore, the model can realistically simulate the mechanical behavior between different crystals within a rock, including complex mechanical phenomena such as fractures, frictional slip at joint surfaces, dilatation effects, and contact separation. Next, second mechanical parameters characterizing the grain boundary interface properties are determined. These second mechanical parameters include, but are not limited to, joint normal stiffness, joint tangential stiffness, friction coefficient, cohesion, and tensile strength. These second mechanical parameters are then written into the attribute fields of the established smooth joint contact instance, completing parameter binding. The resulting simulation results accurately reflect the intergranular failure behavior of rocks under stress or heat, i.e., the phenomenon of crack propagation along mineral grain boundaries.

[0078] The rock mechanics model constructed in this embodiment of the invention can simultaneously accommodate both transgranular fracture and intergranular slip failure modes, significantly improving the realism and accuracy of the simulation of mechanical response and damage evolution of heterogeneous rocks under complex stress paths.

[0079] Furthermore, after simulating the internal bonding behavior of crystals and the intercrystalline interface slip behavior, it is necessary to construct a mechanical model based on the simulation results. Based on this, the method includes: identifying suspended particles in each particle of the rock geometry model that have not established contact instances with any neighboring particles, removing the suspended particles from the rock geometry model, and constructing a rock mechanical model of the target heterogeneous rock based on the rock geometry model after removing the suspended particles, the simulation results of the internal bonding behavior of crystals, and the simulation results of the intercrystalline interface slip behavior.

[0080] Specifically, firstly, each particle in the rock geometry model is traversed, and a neighborhood connectivity check is performed. Each particle is examined to see if it has successfully established contact instances with its neighboring particles, including linear parallel bond contacts or smooth joint contacts. If a particle is found to have no effective contact connections with any neighboring particles, it is determined to be a suspended particle. Such suspended particles typically arise from boundary effects or local voids during random filling processes and cannot participate in force transmission or heat conduction, thus constituting invalid computational units. All identified suspended particles are then removed from the geometry model, retaining only the set of valid particles that are interconnected to form a complete framework. This eliminates the risk of singularities in numerical computation and ensures the continuity and stability of the model's topology. Based on the rock geometry model after removing suspended particles, the material carrier and spatial distribution framework of the rock geometry model are established. The simulation results of the intracrystalline bonding behavior, i.e., the linear parallel bond contact instances with the first mechanical parameter information, are mapped to the contact interfaces of all homogeneous mineral particles in the geometric model, giving them intrinsic strength to resist tensile and shear fracture. The simulation results of the intercrystalline interface slip behavior, i.e., the smooth joint contact instances with the second mechanical parameter information, are mapped to the contact interfaces of all heterogeneous mineral particles in the rock geometry model, giving them frictional slip and interface weakening characteristics. This embodiment of the invention organically integrates the cleaned geometric framework, the strong intracrystalline bonding mechanism, and the weak intercrystalline slip mechanism to form a complete rock mechanics model that can realistically reflect the microstructural characteristics, mineral composition differences, and complex failure mechanisms of heterogeneous rocks. This model can be directly used for subsequent thermo-mechanical coupling loading simulations to accurately predict the crack initiation, propagation path, and macroscopic mechanical property degradation of rocks under high-temperature environments.

[0081] 203. Construct temperature dependence functions for multiple key thermal parameters of the target heterogeneous rock, including the thermal expansion coefficient function, thermal resistance function, and friction coefficient function with temperature as the independent variable.

[0082] In this embodiment of the invention, in order to construct a thermo-mechanical coupling model that considers thermal damage variables, it is also necessary to construct temperature dependence functions for multiple key thermal parameters. Based on this, step 203 specifically includes: constructing temperature dependence functions for each mineral component in the target heterogeneous rock. An initial function for the coefficient of thermal expansion is obtained, and a sample dataset of the coefficient of thermal expansion is acquired. Based on the sample dataset, each undetermined coefficient of thermal expansion in the initial function is solved. Based on the solution results of the undetermined coefficients of thermal expansion, the initial function is constructed to represent the corresponding mineral composition. The thermal expansion coefficient function, wherein the thermal expansion coefficient sample dataset includes the thermal expansion coefficients of different mineral components at different temperatures, and the mineral components... Thermal expansion coefficient function based on temperature T for: , For temperature, , , These are the solution values ​​for each undetermined coefficient of thermal expansion. Mineral components Mineral-specific normalization parameters; constructing the mineral composition of each mineral component in the target heterogeneous rock. An initial thermal resistance function is derived, a thermal resistance sample dataset is obtained, and the undetermined coefficients of thermal resistance in the initial thermal resistance function are solved based on the thermal resistance sample dataset. Based on the solution results of the undetermined thermal resistance coefficients, the initial thermal resistance function is constructed to correspond to the mineral composition. The thermal resistance function, wherein the thermal resistance sample dataset includes the thermal resistance of different mineral compositions at different temperatures, and the mineral compositions... Thermal resistance function based on temperature T for: , For reference thermal resistance, Mineral components The growth coefficient; construct the growth coefficient of each mineral component in the target heterogeneous rock respectively. An initial friction coefficient function is derived, a friction coefficient sample dataset is obtained, and the undetermined coefficients of each friction coefficient in the initial friction coefficient function are solved based on the friction coefficient sample dataset. Based on the solution results of the undetermined friction coefficient coefficients, the initial friction coefficient function is constructed to correspond to the mineral composition. The friction coefficient function, wherein the friction coefficient sample dataset includes friction coefficients of different mineral compositions at different temperatures, and the mineral compositions... Friction coefficient function based on temperature T for: , As the reference friction coefficient, , , , The solution value is the coefficient of friction, which is the undetermined coefficient. For temperature-dependent growth rate, This represents the temperature rise.

[0083] Specifically, in constructing the thermal expansion coefficient function for each mineral component, an initial thermal expansion coefficient function is constructed for each independent mineral component in the target heterogeneous rock. This initial function is an analytical expression containing multiple undetermined coefficients, used to describe the potential law of thermal expansion coefficient variation with temperature. Then, a thermal expansion coefficient sample dataset is obtained. This dataset can be derived from high-temperature physical property tests or standard material databases to determine the measured thermal expansion coefficient values ​​of different mineral components at a series of discrete temperature points. The sample data covers the entire temperature range that the target rock may experience, ensuring the reliability of subsequent fitting. Based on the above sample dataset, the linear least squares method or other numerical optimization algorithms are used to solve for each undetermined thermal expansion coefficient in the initial thermal expansion coefficient function. The solution process aims to minimize the sum of squared residuals between the theoretical calculation values ​​and the experimental sample values, thereby obtaining a set of optimal solutions for undetermined coefficients. Substituting the obtained undetermined coefficients into the initial function, the final thermal expansion coefficient function for the corresponding mineral component can be constructed.

[0084] In constructing the thermal resistance function for each mineral component, firstly, for each independent mineral component in the target heterogeneous rock, a corresponding initial thermal resistance function is constructed. This initial function can be an exponential expression containing undetermined coefficients, used to describe the nonlinear growth trend of thermal resistance with temperature. Next, a thermal resistance sample dataset is obtained. This dataset can be derived from high-temperature property testing, etc., to determine the measured thermal resistance values ​​of different mineral components at multiple temperature points through experimental results. The sample data covers the entire operating temperature range that the target rock may experience, ensuring the representativeness and applicability of subsequent parameter solutions. Based on the above sample dataset, a curve fitting algorithm or damped least squares method is used to iteratively solve for each undetermined coefficient in the initial thermal resistance function. The solution process aims to minimize the error between theoretical predictions and experimental observations, thereby obtaining the optimal combination of undetermined coefficients. Substituting the obtained undetermined coefficients into the initial function, the final thermal resistance function for the corresponding mineral component can be constructed.

[0085] In constructing the friction coefficient function, firstly, for each independent mineral component in the target heterogeneous rock, a corresponding initial friction coefficient function is constructed. This initial function is a composite expression containing multiple undetermined coefficients, used to describe the nonlinear response characteristics of the friction coefficient during temperature changes, especially considering the dynamic influence of temperature rise increments on friction performance. Next, a friction coefficient sample dataset is obtained. This dataset can be derived from high-temperature shear tests, and the measured friction coefficient values ​​of different mineral components under different temperature conditions or different temperature rise amplitudes are determined based on the test results. The sample data covers all temperature ranges and loading paths that the target rock may experience. The friction coefficient changes exponentially with temperature in the early stage and tends to saturate in the later stage. Based on the above sample dataset, a piecewise nonlinear least squares method combined with a gradient descent method is used for iterative optimization. Then, the two data segments are fitted piecewise, and global optimization is performed until the total residual is minimized. This is used to solve for each undetermined friction coefficient in the initial friction coefficient function. The solution process aims to minimize the sum of squared residuals between theoretical calculations and experimental measurements, thereby obtaining a set of optimal solutions for undetermined coefficients. Substituting these undetermined coefficients into the initial function allows the construction of the final friction coefficient function for the corresponding mineral composition. In the friction coefficient function... , ,in, For temperature-dependent growth rate, For rapid growth rate, For the slow phase growth rate, This is an S-shaped switching function. All the above coefficients can be obtained experimentally. The friction coefficient changes exponentially with temperature in the early stage and then tends to saturate in the later stage.

[0086] 204. The temperature dependence function of each key thermal parameter is embedded into the rock mechanics model to obtain a thermo-mechanical coupling model that considers thermal damage variables.

[0087] In this embodiment of the invention, to ensure that the constructed mechanical model conforms to reality, it is necessary to calibrate the mechanical parameters of the rock mechanics model. Based on this, the method includes: obtaining the overall macroscopic elastic modulus of the target heterogeneous rock, the mapping relationship between the overall macroscopic elastic modulus and the microscopic stiffness of the rock, determining a global reference stiffness value based on the overall macroscopic elastic modulus and the mapping relationship, and assigning the global reference stiffness value as an initial stiffness parameter and a preset high-strength parameter to all mineral components of the rock mechanics model; determining the elastic response proportionality coefficient between the microscopic elastic modulus of each mineral component in the rock mechanics model and the overall macroscopic elastic modulus of the rock, and applying the elastic response proportionality coefficient to each mineral component in the rock mechanics model... The initial stiffness parameters of the components are iteratively optimized. Based on the iterative optimization results, the ultimate stiffness parameters of each mineral component are determined. Based on the ultimate stiffness parameters, the calibration elastic parameters of the corresponding mineral components are determined. The calibration elastic parameters are used to calibrate the elastic parameters of each mineral component in the rock mechanics model. The stress-strain curve of the rock mechanics model after elastic parameter calibration is determined. The simulated peak strength in the stress-strain curve is extracted. Based on the difference between the simulated peak strength and the preset standard peak strength, the preset high strength parameter is iteratively adjusted. Based on the iterative adjustment results, the calibration strength parameter is determined. The calibration strength parameter is used to calibrate the rock mechanics model after elastic parameter calibration to obtain the rock mechanics model after mechanical parameter calibration.

[0088] Specifically, firstly, the overall macroscopic elastic modulus of the target heterogeneous rock is obtained under standard test conditions. This value reflects the average stiffness characteristics of the material at the macroscopic scale. Simultaneously, a mapping function is established between the macroscopic elastic modulus and the stiffness of the micro-particles or units within the rock. This function can be obtained through empirical formulas or finite element inversion. Based on the aforementioned macroscopic elastic modulus and mapping relationship, a global reference stiffness value applicable to the entire model is calculated and determined. This value is used as the initial stiffness parameter for all mineral components and uniformly assigned to each mineral particle or mesh unit in the rock mechanics model. Furthermore, to reserve adjustment space for subsequent strength calibration, a set of preset high-strength parameters is simultaneously assigned to all mineral components. These parameters are typically slightly higher than the expected peak strength to avoid early failure interfering with the elastic stage calibration. After completing the initial assignment, for each mineral component in the model, the elastic response proportionality coefficient between its microscopic elastic modulus and the aforementioned overall macroscopic elastic modulus of the rock is calculated. This coefficient characterizes the contribution weight of the mineral to the overall stiffness in the composite system and can be weighted based on microstructural characteristics such as volume fraction, spatial distribution, and contact topology. Based on the elastic response proportionality coefficients corresponding to each mineral, the initial stiffness parameters assigned earlier are iteratively optimized and adjusted. In each iteration, the stiffness values ​​of each mineral are dynamically corrected according to the deviation between the current simulated macroscopic stress-strain curve and the target macroscopic elastic modulus, until the simulated macroscopic elastic modulus converges to within the allowable error range of the measured value. Finally, the ultimate stiffness parameters of each mineral after iterative optimization are recorded and converted into corresponding calibration elastic parameters. Based on these calibration elastic parameters, the elastic parameters of the mechanical model are calibrated.

[0089] Further, after completing the elastic parameter calibration, a stress-strain curve of the calibrated mechanical model is generated. The simulated peak strength, i.e., the stress value corresponding to the highest point of the curve, is extracted from it. This simulated value is compared with the preset standard peak strength set according to actual needs, and the difference between the two is calculated. If the difference exceeds the allowable range, an iterative adjustment mechanism for the strength parameters is initiated: based on the preset high strength parameters, the parameters are finely adjusted downwards by a certain step size or an adaptive algorithm, the simulation is rerun, and a new peak strength is extracted. This process is repeated until the simulated peak strength matches the preset standard peak strength. The finally determined adjusted parameters are the calibrated strength parameters, including key strength indicators such as compressive strength, cohesion, and internal friction angle. The calibrated strength parameters are substituted into the mechanical model that has completed the elastic calibration to complete the final strength parameter calibration, thereby obtaining the rock mechanics model after mechanical parameter calibration. This embodiment of the invention combines macroscopic constraints and microscopic response proportionality coefficients to achieve systematic calibration of multi-mineral component parameters of heterogeneous rocks. It is particularly suitable for modeling real rock samples containing multiple minerals, complex pore structures, and significant anisotropy, greatly improving the physical realism of numerical simulation and the accuracy of engineering prediction.

[0090] Furthermore, after calibrating the mechanical parameters of the mechanical model, in order to verify the calibration effect, it is also necessary to verify the calibration results. Based on this, the method includes: determining the mechanical parameter verification scenario of the rock mechanical model after mechanical parameter calibration, wherein the mechanical parameter verification scenario includes a preset number of mutually independent and unequal principal stress constraint scenarios and isothermal boundary condition scenarios; performing mechanical response simulation on the rock mechanical model after mechanical parameter calibration under the mechanical parameter verification scenario, determining mechanical response prediction data based on the mechanical response simulation, and conducting mechanical response tests on the target heterogeneous rock under the mechanical parameter verification scenario, determining mechanical response physical data based on the mechanical response test results, and determining the mechanical parameter calibration effect of the rock mechanical model based on the mechanical response prediction data and the mechanical response physical data.

[0091] Specifically, firstly, a set of scenarios for mechanical parameter verification is established. This set consists of a predetermined number of independent test conditions, comprehensively covering the complex stress and environmental conditions that the target heterogeneous rock may encounter in actual engineering. In determining the mechanical parameter verification scenarios, a series of independent principal stress constraint conditions with unequal values ​​are designed first. These conditions include, but are not limited to, uniaxial compression, triaxial compression, true triaxial loading, and unloading tests along specific paths. Under each condition, the stress constraint values ​​in the three principal directions are specifically set to ensure significant differences in stress states between scenarios, thereby fully stimulating the mechanical response characteristics of the rock under different stress paths and avoiding the bias of verification caused by a single stress state. Based on the above stress constraint scenarios, different isothermal boundary conditions are superimposed, i.e., a series of fixed temperature values ​​are set as the ambient temperature field of the model, covering a wide range from room temperature to high temperature. In each verification scenario, a constant temperature constraint is applied to the model boundary to simulate the rock behavior under high-temperature conditions such as deep geothermal environments or fires, ensuring that the verification process simultaneously considers the thermo-mechanical coupling effect or the influence of temperature on material parameters. The final verification scenario library is a combination of the aforementioned principal stress constraint scenarios and isothermal boundary condition scenarios, ensuring that each verification point possesses unique stress-temperature dual attributes. Under each constructed mechanical parameter verification scenario, forward numerical simulation calculations are performed on the rock mechanics model after elastic and strength parameter calibration. During the simulation, the calculation step size is executed according to the set principal stress constraint loading path and isothermal boundary conditions. The global and local responses of the mechanical model throughout the loading process are recorded, and key mechanical response prediction data are extracted. This mechanical response prediction data includes, but is not limited to: stress-strain curves, peak strength values, residual strength values, elastic modulus evolution, Poisson's ratio changes, failure mode morphology, crack propagation paths, and energy dissipation characteristics. All prediction data are stored according to scenario classification, forming a complete numerical simulation dataset. Simultaneously, under a mechanical parameter verification scenario completely consistent with the numerical simulation, physical and mechanical tests were conducted on real rock samples of the target heterogeneous rock. Before the tests, rock specimens from the same source, batch, and with similar properties as the modeled object were selected. The principal stress constraint conditions in the numerical simulation were accurately reproduced in the experimental equipment, such as setting the same confining pressure, axial compression loading rate, and isothermal environment. During the tests, high-precision sensors were used to collect the mechanical response of the specimens in real time, obtaining physical data of the mechanical response. The data types collected were consistent with those extracted from the numerical simulation, including stress, strain, strength indices, deformation characteristics, and failure morphology images, forming a physical test dataset, which consisted of multiple mechanical response physical data. Finally, a comparative analysis was conducted based on the mechanical response prediction data and the mechanical response physical data under the same verification scenario to determine the calibration effect of the rock mechanics model's mechanical parameters.During the calibration process, the relative or absolute errors of key indicators such as peak strength, elastic modulus, and peak strain are calculated. For example, the overlap between simulated and experimental curves is compared, and the root mean square error or correlation coefficient is calculated. If the error is within the preset allowable threshold range, the calibration result for that scenario is deemed acceptable. The failure modes obtained from the simulation, such as shear band location and tensile crack distribution, are compared with the actual fracture morphology of the specimen after physical testing. If the two are highly consistent in terms of macroscopic failure characteristics and microscopic crack evolution trends, the physical authenticity of the calibration parameters is further confirmed. The comparison results of all independent verification scenarios are summarized. If the model's predicted data maintains a high degree of consistency with the physical data under all preset complex stress and temperature scenarios, the mechanical parameter calibration effect of the rock mechanics model is deemed acceptable, and the model possesses high reliability and engineering applicability, and can be used for subsequent prediction of unknown complex working conditions. Conversely, if the deviation is large in certain specific scenarios, the parameters need to be recalibrated until the calibration results meet the requirements. The embodiments of the present invention effectively avoid overfitting during the parameter calibration process through the above-mentioned multi-scenario and multi-dimensional verification process, ensuring that the calibrated rock mechanics model not only performs well under the calibration conditions, but also accurately predicts complex mechanical behaviors.

[0092] Furthermore, after calibrating the parameters of the mechanical model, each computational unit in the model, such as each particle, is traversed to identify its mineral composition type. Based on the identification results, the thermal expansion coefficient function, thermal resistance function, and friction coefficient function of the corresponding mineral are directly bound to the computational unit. At this point, each unit in the mechanical model no longer has a fixed thermal constant value, but carries a set of attribute rules that are dynamically updated with the real-time temperature field. Then, thermal damage variables are introduced into the constitutive relation of the model, and a linkage mechanism between them and the above three functions is established to obtain a thermo-mechanical coupling model considering thermal damage variables. After establishing the linkage mechanism with the above three functions, during the temperature field solution process, the thermal expansion coefficient function is automatically called to calculate the instantaneous thermal expansion strain of each mineral. Since the expansion functions of different minerals are different, microscopic thermal stress will be automatically generated at the grain boundaries. When this stress exceeds the local strength threshold, the damage evolution equation is triggered, generating the initial thermal damage variables. In the temperature field reconstruction process based on thermal resistance: the thermal conduction matrix of the mechanical model is dynamically updated using the thermal resistance function. As the temperature rises, the change in thermal resistance alters the distribution of the local temperature field, thus affecting the calculation results of thermal expansion strain, forming a feedback loop of temperature, thermal resistance, and thermal stress, mitigating the accumulation of local thermal damage. In the strength degradation process based on the friction coefficient: the friction coefficient function is directly applied to the shear constitutive relationship of the contact surface. As the temperature rises, the dynamic change in the friction coefficient directly leads to real-time adjustment of the shear strength of the contact surface. When the friction coefficient decreases, it accelerates the slip propagation of microcracks, thus macroscopically manifesting as a rapid increase in thermal damage variables and a decrease in overall load-bearing capacity. This invention constructs a thermo-mechanical coupling model by embedding the temperature dependence functions of multiple key thermal parameters into the rock mechanics model. This allows the thermo-mechanical coupling model to dynamically update the thermal properties of each computational unit based on the real-time calculated temperature field, truly reflecting the continuous degradation or abrupt change in material properties with increasing temperature. The thermo-mechanical coupling model can accurately reproduce the nonlinear physical evolution process, avoiding the huge errors caused by constant assumptions.

[0093] In another embodiment of the present invention, the method of embedding the temperature-dependent function into the mechanical model further includes: in PFC (Particle Flow Code) software, activating the mechanical calculation module, configuring mechanical calculation, setting the scaling mode of the mechanical calculation time step, configuring the thermal calculation environment, enabling the thermal calculation module, setting the default contact heat conduction model, initial thermal contact parameters and applying them to all contacts, setting the basic thermophysical properties of the particles, including but not limited to specific heat capacity, density, initial thermal expansion coefficient, etc., and setting the velocity and displacement of the particles to zero, configuring thermal calculation, setting the thermal calculation time step and the initial temperature of all particles, and saving the contact parameters into a specific array according to the contact model type, such as normal stiffness, tangential stiffness, cohesion, tensile strength, friction coefficient, friction angle, etc. The thermal expansion coefficients and thermal resistances of different mineral components are calculated and updated in real time. Pre-constructed independent variables, including thermal expansion coefficient functions, thermal resistance functions, and friction coefficient functions based on temperature, are introduced. Update frequencies and flags are set, and different reference thermal expansion coefficients, reference thermal resistance coefficients, and reference friction coefficients are assigned to different mineral components. The results of the temperature-dependent functions are then multiplied or divided by the corresponding reference coefficients to obtain the thermal expansion coefficients, thermal resistance coefficients, and friction coefficients of the corresponding mineral components at the real-time temperature. The temperature-dependent functions are executed at each calculation step to adjust the material's thermal parameters according to temperature. Through this method, the constructed heterogeneous rock mechanics model is transformed into a thermo-mechanical coupling model, considering the influence of changes in thermal expansion coefficients, thermal resistance coefficients, and friction coefficients caused by real-time temperature.

[0094] 205. Determine the initial temperature, target arrival temperature, and temperature change interval of the simulated temperature field. Based on the initial temperature, target arrival temperature, and temperature change interval, use a thermo-mechanical coupling model to perform thermal and mechanical analysis of the target heterogeneous rock under multiple temperature gradients.

[0095] Specifically, the initial temperature of the coupled model is set to the ambient temperature or the in-situ geothermal temperature of the rock, serving as the baseline zero point for thermal damage evolution and ensuring that the initial stress field and thermal parameters within the model are in an undisturbed natural state. Target arrival temperature setting: The final temperature threshold is determined based on actual needs. This temperature should cover the period before or after the critical point when the rock undergoes key physicochemical changes, such as mineral phase transformation, dehydration, or melting. For example, for granite rocks, the target temperature can be set to 800 to 1000 degrees Celsius to fully capture the quartz phase transformation and subsequent high-temperature softening process. Temperature change interval setting: Several discrete temperature nodes are defined between the initial temperature and the target arrival temperature, forming a multi-temperature gradient sequence. The selection of temperature change intervals needs to balance computational efficiency and result accuracy: in the range of room to medium temperature, since the changes in rock properties are relatively gradual, a larger temperature interval can be used, such as every 50 degrees Celsius as a node; in the high-temperature sensitive range, a smaller temperature interval should be used, such as every 10 or 20 degrees Celsius as a node, to accurately capture the nonlinear response caused by abrupt changes in the coefficient of thermal expansion, a surge in thermal resistance, and drastic fluctuations in the coefficient of friction. This ultimately forms an ordered temperature sequence that gradually increases from the initial temperature to the target temperature. Using a thermo-mechanical coupling model with embedded temperature dependence functions of key thermal parameters (coefficient of thermal expansion function, thermal resistance function, coefficient of friction function), the process of gradient heating, thermal field reconstruction, coupled response, and damage evolution of the rock is calculated iteratively step-by-step according to the set temperature sequence, sequentially traversing all preset temperature nodes until the set target temperature is reached. The thermo-mechanical coupling calculation in this embodiment of the invention employs a step-by-step coupling algorithm, that is, at each temperature change interval, thermal and mechanical calculations are performed separately and sequentially, which can efficiently reproduce the thermo-mechanical coupling effect during the slow heating process.

[0096] For example, the initial temperature, target temperature, and temperature change interval of the simulated temperature field are determined, and the temperature conditions are set in the PFC particle flow software. In one embodiment of the invention, the initial temperature is 25°C, the target temperature is 100°C, and the temperature change interval is 10°C, expressed in the software as "(25,100,10)"; the boundary temperature is set, and the temperature of all walls is set to the current target temperature; thermal calculations are performed separately, and the process of heat conduction is fully simulated by looping 2000 times in the PFC particle flow software until the temperature field reaches equilibrium; then the thermal calculations are turned off, the mechanical calculations are activated, the mechanical time step is automatically adjusted, the equilibrium conditions are set, the equilibrium is reached, the deformation force generated by thermal expansion is applied to the particle system, and it is determined whether it causes damage. The above thermal and mechanical calculation process is repeated until the current temperature reaches the target temperature to obtain the final simulation result.

[0097] The present invention provides another method for thermo-mechanical coupling modeling of differential damage in heterogeneous rocks. Compared with the current method of treating the thermal parameters of rocks as constants to construct a thermo-mechanical coupling model and then conducting thermo-mechanical coupling analysis of rocks, the present invention obtains geometric structural characteristic parameters and constructs a rock geometric model, which can accurately describe the internal structure of the target heterogeneous rock. This provides an accurate geometric basis for subsequent mechanical and thermal analysis, enabling the model to more realistically reflect the actual situation of the rock and improve the reliability of the analysis results. Since the bonding behavior inside crystals and the slip behavior at the interface between crystals are important factors affecting the mechanical properties of rocks, the present invention simulates these two behaviors separately, which can consider the interaction mechanism inside the rock in more detail, making the rock mechanical model more realistic. By constructing temperature dependence functions of key thermal parameters and embedding them into the rock mechanical model, the thermal and mechanical behavior of rocks at different temperatures can be described more accurately, improving the accuracy of the coupling model construction and thus improving the accuracy of the thermo-mechanical coupling analysis results of rocks.

[0098] Furthermore, as Figure 1 In specific implementation, embodiments of the present invention provide a thermo-mechanical coupling modeling device for differential damage in heterogeneous rocks, such as... Figure 3 As shown, the device includes: a geometric model building unit 31, a mechanical model building unit 32, a function building unit 33, and a coupling analysis unit 34.

[0099] The geometric model construction unit 31 can be used to obtain the geometric structural feature parameters of the target heterogeneous rock and construct the rock geometric model of the target heterogeneous rock based on the geometric structural feature parameters.

[0100] The mechanical model construction unit 32 can be used to divide every two adjacent particles into intracrystalline contact pairs or intercrystalline contact pairs based on the type of each particle in the rock geometry model, simulate the internal bonding behavior of the intracrystalline contact pairs, simulate the intercrystalline interface slip behavior of the intercrystalline contact pairs, and construct the rock mechanics model of the target heterogeneous rock based on the simulation results of the internal bonding behavior and the simulation results of the intercrystalline interface slip behavior. In this model, the two adjacent particles in the intracrystalline contact pairs have the same particle type, and the two adjacent particles in the intercrystalline contact pairs have different particle types.

[0101] The function construction unit 33 can be used to construct temperature dependence functions for multiple key thermal parameters of the target heterogeneous rock, wherein the temperature dependence functions for multiple key thermal parameters include a thermal expansion coefficient function, a thermal resistance function, and a friction coefficient function with temperature as the independent variable.

[0102] The coupling analysis unit 34 can be used to embed the temperature dependence function of each key thermal parameter into the rock mechanics model to obtain a thermo-mechanical coupling model that considers thermal damage variables, and to perform thermo-mechanical coupling analysis on the target heterogeneous rock based on the thermo-mechanical coupling model.

[0103] In specific application scenarios, in order to construct a rock geometry model of the target heterogeneous rock, such as Figure 4 As shown, the geometric model construction unit 31 includes a particle generation module 311, a block generation module 312, a container determination module 313, and a geometric model construction module 314.

[0104] The particle generation module 311 can be used to determine the model construction area of ​​the rock geometric model based on the geometric structure feature parameters, randomly generate at least one initial particle in the model construction area, and assign geometric attribute information and spatial position coordinates to each initial particle based on the size information of the model construction area to obtain intermediate particles.

[0105] The block generation module 312 can be used to construct a spatial segmentation reference point set based on the center coordinates of each intermediate particle, segment the model construction region into multiple non-overlapping polyhedral units based on the spatial segmentation reference point set, and instantiate each polyhedral unit into a rigid block unit.

[0106] The container determination module 313 can be used to classify each rigid block unit based on the mineral type and relative content ratio of the target heterogeneous rock, and map the rigid block units under different categories to target geometric regions of different mineral types. The intermediate particles are removed in the model construction region, and only the boundary contour of the target geometric region is retained. The boundary contour of the target geometric region is used as a hollow geometric container.

[0107] The geometric model construction module 314 can be used to determine the target mineral type corresponding to each hollow geometric container, determine the particle attribute information of the particles required to constitute the target mineral type in the target heterogeneous rock, generate and fill secondary filling particles in the corresponding hollow geometric container based on the particle attribute information, and assign physical and mechanical properties matching the target mineral type to the secondary filling particles to obtain the rock geometric model of the target heterogeneous rock.

[0108] In specific application scenarios, in order to simulate the bonding behavior inside the crystal and the sliding behavior at the interface between crystals, and to build a mechanical model based on the simulation results, the mechanical model building unit 32 includes a simulation module 321 and a mechanical model building module 322.

[0109] The simulation module 321 can be used to call the linear parallel bond model constructor to establish a linear parallel bond contact instance on the intracrystalline contact pair, determine the first mechanical parameter information between the intracrystalline contact pairs, and write the first mechanical parameter information into the attribute field of the linear parallel bond contact instance to obtain the simulation result of the bonding behavior inside the crystal.

[0110] The simulation module 321 can also be used to call the smooth joint model constructor to establish a smooth joint contact instance on the intercrystalline contact pair, determine the second mechanical parameter information between the intercrystalline contact pairs, and write the second mechanical parameter information into the attribute field of the smooth joint contact instance to obtain the simulation results of the intercrystalline interface sliding behavior.

[0111] The mechanical model construction module 322 can be used to identify suspended particles in each particle of the rock geometry model that have not established contact instances with any neighboring particles, remove the suspended particles in the rock geometry model, and construct a rock mechanical model of the target heterogeneous rock based on the rock geometry model after removing the suspended particles, the simulation results of the bonding behavior inside the crystal, and the simulation results of the intercrystalline interface slip behavior.

[0112] In specific application scenarios, in order to construct temperature dependence functions for multiple key thermal parameters of the target heterogeneous rock, the function construction unit 33 can be specifically used to construct the temperature dependence functions for each mineral component in the target heterogeneous rock. An initial function for the coefficient of thermal expansion is obtained, and a sample dataset of the coefficient of thermal expansion is acquired. Based on the sample dataset, each undetermined coefficient of thermal expansion in the initial function is solved. Based on the solution results of the undetermined coefficients of thermal expansion, the initial function is constructed to represent the corresponding mineral composition. The thermal expansion coefficient function, wherein the thermal expansion coefficient sample dataset includes the thermal expansion coefficients of different mineral components at different temperatures, and the mineral components... Thermal expansion coefficient function based on temperature T for: , For temperature, , , These are the solution values ​​for each undetermined coefficient of thermal expansion. Mineral components Mineral-specific normalization parameters; constructing the mineral composition of each mineral component in the target heterogeneous rock. An initial thermal resistance function is derived, a thermal resistance sample dataset is obtained, and the undetermined coefficients of thermal resistance in the initial thermal resistance function are solved based on the thermal resistance sample dataset. Based on the solution results of the undetermined thermal resistance coefficients, the initial thermal resistance function is constructed to correspond to the mineral composition. The thermal resistance function, wherein the thermal resistance sample dataset includes the thermal resistance of different mineral compositions at different temperatures, and the mineral compositions... Thermal resistance function based on temperature T for: , For reference thermal resistance, Mineral components The growth coefficient; construct the growth coefficient of each mineral component in the target heterogeneous rock respectively. An initial friction coefficient function is derived, a friction coefficient sample dataset is obtained, and the undetermined coefficients of each friction coefficient in the initial friction coefficient function are solved based on the friction coefficient sample dataset. Based on the solution results of the undetermined friction coefficient coefficients, the initial friction coefficient function is constructed to correspond to the mineral composition. The friction coefficient function, wherein the friction coefficient sample dataset includes friction coefficients of different mineral compositions at different temperatures, and the mineral compositions... Friction coefficient function based on temperature T for: , As the reference friction coefficient, , , , The solution value is the coefficient of friction, which is the undetermined coefficient. For temperature-dependent growth rate, This represents the temperature rise.

[0113] In specific application scenarios, in order to calibrate the mechanical parameters of the rock mechanics model, the device also includes a calibration unit 35.

[0114] The calibration unit 35 can be used to obtain the overall macroscopic elastic modulus of the target heterogeneous rock, the mapping relationship between the overall macroscopic elastic modulus and the microscopic stiffness of the rock, determine a global reference stiffness value based on the overall macroscopic elastic modulus and the mapping relationship, and assign the global reference stiffness value as an initial stiffness parameter and a preset high-strength parameter to all mineral components of the rock mechanics model respectively; determine the elastic response proportionality coefficient between the microscopic elastic modulus and the overall macroscopic elastic modulus of the rock for each mineral component in the rock mechanics model, and iteratively optimize the initial stiffness parameter of each mineral component in the rock mechanics model based on the elastic response proportionality coefficient, and based on the iterative optimization... The final stiffness parameter of each mineral component is determined by the chemical analysis results. Based on the final stiffness parameter, the calibration elastic parameter of the corresponding mineral component is determined. The elastic parameter of each mineral component in the rock mechanics model is calibrated using the calibration elastic parameter. The stress-strain curve of the rock mechanics model after elastic parameter calibration is determined. The simulated peak strength in the stress-strain curve is extracted. The preset high strength parameter is iteratively adjusted based on the difference between the simulated peak strength and the preset standard peak strength. The calibration strength parameter is determined based on the iterative adjustment result. The strength parameter of the rock mechanics model after elastic parameter calibration is calibrated using the calibration strength parameter to obtain the rock mechanics model after mechanical parameter calibration.

[0115] In specific application scenarios, in order to verify the calibration results of the mechanical model, the device also includes a verification unit 36.

[0116] The verification unit 36 ​​can be used to determine the mechanical parameter verification scenarios of the rock mechanics model after mechanical parameter calibration. The mechanical parameter verification scenarios include a preset number of mutually independent and unequal principal stress constraint scenarios and isothermal boundary condition scenarios. Under the mechanical parameter verification scenarios, the rock mechanics model after mechanical parameter calibration is subjected to mechanical response simulation. Based on the mechanical response simulation, mechanical response prediction data is determined. Under the mechanical parameter verification scenarios, mechanical response tests are conducted on the target heterogeneous rock. Based on the mechanical response test results, mechanical response physical data is determined. Based on the mechanical response prediction data and the mechanical response physical data, the mechanical parameter calibration effect of the rock mechanics model is determined.

[0117] In specific application scenarios, in order to perform thermo-mechanical coupling analysis on rocks, the coupling analysis unit 34 can be used to determine the initial temperature, target arrival temperature and temperature change interval of the simulated temperature field. Based on the initial temperature, the target arrival temperature and the temperature change interval, the thermo-mechanical coupling model is used to perform multi-temperature gradient thermal and mechanical analysis on the target heterogeneous rock.

[0118] It should be noted that other corresponding descriptions of the functional modules involved in the thermo-mechanical coupling modeling device for differential damage in heterogeneous rocks provided in this embodiment of the invention can be found in [reference needed]. Figure 1 The corresponding description of the method shown will not be repeated here.

[0119] Based on the above, Figure 1 The method shown, correspondingly, also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, performs the following steps: obtaining geometric structural feature parameters of the target heterogeneous rock; constructing a rock geometric model of the target heterogeneous rock based on the geometric structural feature parameters; dividing every two adjacent particles into intracrystalline contact pairs or intercrystalline contact pairs based on the type of each particle in the rock geometric model; simulating the intracrystalline bonding behavior of the intracrystalline contact pairs; simulating the intercrystalline interface slip behavior of the intercrystalline contact pairs; and performing simulations based on the simulation results of the intracrystalline bonding behavior and the simulation results of the intercrystalline interface slip behavior. A rock mechanics model of the target heterogeneous rock is constructed based on the proposed results. In this model, two adjacent particles in an intragranular contact pair have the same particle type, while two adjacent particles in an intergranular contact pair have different particle types. Temperature dependence functions for several key thermal parameters of the target heterogeneous rock are constructed, including functions for the coefficient of thermal expansion, thermal resistance, and coefficient of friction, all with temperature as the independent variable. The temperature dependence function of each key thermal parameter is embedded into the rock mechanics model to obtain a thermo-mechanical coupling model considering thermal damage variables. Thermo-mechanical coupling analysis is then performed on the target heterogeneous rock based on this model.

[0120] Based on the above, Figure 1 The method shown and as Figure 3 The embodiment of the device shown in the invention also provides a physical structure diagram of a computer device, such as... Figure 5As shown, the computer device includes: a processor 41, a memory 42, and a computer program stored in the memory 42 and executable on the processor. Both the memory 42 and the processor 41 are mounted on a bus 43. When the processor 41 executes the program, it performs the following steps: acquiring geometric structural feature parameters of the target heterogeneous rock; constructing a rock geometric model of the target heterogeneous rock based on the geometric structural feature parameters; dividing every two adjacent particles into intracrystalline contact pairs or intercrystalline contact pairs based on the type of each particle in the rock geometric model; simulating the intracrystalline bonding behavior of the intracrystalline contact pairs; simulating the intercrystalline interface slip behavior of the intercrystalline contact pairs; and simulating the intracrystalline bonding behavior... The simulation results and the simulation results of intercrystalline interface slip behavior are used to construct a rock mechanics model of the target heterogeneous rock. In this model, the two adjacent particles in the intracrystalline contact pair have the same particle type, while the two adjacent particles in the intercrystalline contact pair have different particle types. Temperature dependence functions of multiple key thermal parameters of the target heterogeneous rock are constructed. These functions include the thermal expansion coefficient function, thermal resistance function, and friction coefficient function, all with temperature as the independent variable. The temperature dependence function of each key thermal parameter is embedded into the rock mechanics model to obtain a thermo-mechanical coupling model that considers thermal damage variables. The thermo-mechanical coupling analysis of the target heterogeneous rock is then performed based on this model.

[0121] Through the technical solution of this invention, by acquiring geometric structural characteristic parameters and constructing a rock geometric model, the internal structure of the target heterogeneous rock can be accurately described, providing an accurate geometric basis for subsequent mechanical and thermal analysis. This allows the model to more realistically reflect the actual situation of the rock and improves the reliability of the analysis results. Since the bonding behavior inside crystals and the intercrystalline interface slip behavior are important influencing factors of rock mechanical properties, this invention can simulate these two behaviors separately, allowing for a more detailed consideration of the interaction mechanism inside the rock, making the rock mechanical model more realistic. By constructing temperature dependence functions for key thermal parameters and embedding them into the rock mechanical model, the thermal and mechanical behavior of the rock at different temperatures can be described more accurately, improving the accuracy of the coupled model construction and thus improving the accuracy of the thermo-mechanical coupling analysis results of the rock.

[0122] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0123] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A thermo-mechanical coupling modeling method for differential damage in heterogeneous rocks, characterized in that, include: Obtain the geometric structural feature parameters of the target heterogeneous rock, and construct a rock geometric model of the target heterogeneous rock based on the geometric structural feature parameters; Based on the type of each particle in the rock geometry model, every two adjacent particles are divided into intracrystalline contact pairs or intercrystalline contact pairs. The intracrystalline contact pairs are simulated for internal crystal bonding behavior, and the intercrystalline contact pairs are simulated for intercrystalline interface slip behavior. Based on the simulation results of intracrystalline bonding behavior and intercrystalline interface slip behavior, a rock mechanics model of the target heterogeneous rock is constructed. In the case of the two adjacent particles in the intracrystalline contact pairs, the particle types are the same, and the particle types of the two adjacent particles in the intercrystalline contact pairs are different. The temperature dependence functions of several key thermal parameters of the target heterogeneous rock are constructed, wherein the temperature dependence functions of several key thermal parameters include the thermal expansion coefficient function, the thermal resistance function and the friction coefficient function with temperature as the independent variable; The temperature dependence function of each key thermal parameter is embedded into the rock mechanics model to obtain a thermo-mechanical coupling model that considers thermal damage variables, and a thermo-mechanical coupling analysis is performed on the target heterogeneous rock based on the thermo-mechanical coupling model.

2. The thermo-mechanical coupling modeling method for differential damage in heterogeneous rocks according to claim 1, characterized in that, The construction of the rock geometric model of the target heterogeneous rock based on the geometric structural feature parameters includes: The model construction region of the rock geometric model is determined based on the geometric structural feature parameters. At least one initial particle is randomly generated in the model construction region, and geometric attribute information and spatial position coordinates are assigned to each initial particle based on the size information of the model construction region to obtain intermediate particles. A spatial segmentation reference point set is constructed based on the center coordinates of each intermediate particle. The model construction region is segmented into multiple non-overlapping polyhedral units based on the spatial segmentation reference point set, and each polyhedral unit is instantiated as a rigid block unit. Based on the mineral types and relative content ratios of the target heterogeneous rock, each rigid block unit is classified, and the rigid block units under different categories are mapped to target geometric regions of different mineral types. The intermediate particles are removed in the model construction area, and only the boundary contours of the target geometric regions are retained. The boundary contours of the target geometric regions are used as hollow geometric containers. The target mineral type corresponding to each hollow geometric container is determined, and the particle attribute information of the particles required to constitute the target mineral type in the target heterogeneous rock is determined. Based on the particle attribute information, secondary filling particles are generated and filled in the corresponding hollow geometric container, and the secondary filling particles are given physical and mechanical properties that match the target mineral type to obtain the rock geometric model of the target heterogeneous rock.

3. The thermo-mechanical coupling modeling method for differential damage in heterogeneous rocks according to claim 1, characterized in that, The simulation of the intracrystalline bonding behavior of the intracrystalline contact pairs includes: The linear parallel bond model constructor is called to establish a linear parallel bond contact instance on the intracrystalline contact pair, the first mechanical parameter information between the intracrystalline contact pair is determined, and the first mechanical parameter information is written into the attribute field of the linear parallel bond contact instance to obtain the simulation results of the bonding behavior inside the crystal. The simulation of the intercrystalline interface slip behavior of the intercrystalline contact pairs includes: The smooth joint model constructor is called to establish a smooth joint contact instance on the intercrystalline contact pair, the second mechanical parameter information between the intercrystalline contact pairs is determined, and the second mechanical parameter information is written into the attribute field of the smooth joint contact instance to obtain the simulation results of the intercrystalline interface slip behavior. The rock mechanics model of the target heterogeneous rock is constructed based on the simulation results of the internal bonding behavior of crystals and the simulation results of the intercrystalline interface slip behavior, including: In each particle of the rock geometry model, suspended particles that have not established contact instances with any neighboring particles are identified, and these suspended particles are removed from the rock geometry model. Based on the rock geometry model after removing the suspended particles, the simulation results of the internal bonding behavior of crystals, and the simulation results of the intercrystalline interface slip behavior, a rock mechanics model of the target heterogeneous rock is constructed.

4. The thermo-mechanical coupling modeling method for differential damage in heterogeneous rocks according to claim 1, characterized in that, The temperature dependence function for constructing multiple key thermal parameters of the target heterogeneous rock includes: Construct each mineral composition in the target heterogeneous rock separately. An initial function for the coefficient of thermal expansion is obtained, and a sample dataset of the coefficient of thermal expansion is acquired. Based on the sample dataset, each undetermined coefficient of thermal expansion in the initial function is solved. Based on the solution results of the undetermined coefficients of thermal expansion, the initial function is constructed to represent the corresponding mineral composition. The thermal expansion coefficient function, wherein the thermal expansion coefficient sample dataset includes the thermal expansion coefficients of different mineral components at different temperatures, and the mineral components... Thermal expansion coefficient function based on temperature T for: , For temperature, , , These are the solution values ​​for each undetermined coefficient of thermal expansion. Mineral components Mineral-specific normalized parameters; Construct each mineral composition in the target heterogeneous rock separately. An initial thermal resistance function is derived, a thermal resistance sample dataset is obtained, and the undetermined coefficients of thermal resistance in the initial thermal resistance function are solved based on the thermal resistance sample dataset. Based on the solution results of the undetermined thermal resistance coefficients, the initial thermal resistance function is constructed to correspond to the mineral composition. The thermal resistance function, wherein the thermal resistance sample dataset includes the thermal resistance of different mineral compositions at different temperatures, and the mineral compositions... Thermal resistance function based on temperature T for: , For reference thermal resistance, Mineral components The growth rate; Construct each mineral composition in the target heterogeneous rock separately. An initial friction coefficient function is derived, a friction coefficient sample dataset is obtained, and the undetermined coefficients of each friction coefficient in the initial friction coefficient function are solved based on the friction coefficient sample dataset. Based on the solution results of the undetermined friction coefficient coefficients, the initial friction coefficient function is constructed to correspond to the mineral composition. The friction coefficient function, wherein the friction coefficient sample dataset includes friction coefficients of different mineral compositions at different temperatures, and the mineral compositions... Friction coefficient function based on temperature T for: , As the reference friction coefficient, , , , The solution value is the coefficient of friction, which is the undetermined coefficient. For temperature-dependent growth rate, This represents the temperature rise.

5. The thermo-mechanical coupling modeling method for differential damage in heterogeneous rocks according to claim 1, characterized in that, Before embedding the temperature dependence function of each of the key thermal parameters into the rock mechanics model to obtain a thermo-mechanical coupling model considering thermal damage variables, the method further includes: Obtain the overall macroscopic elastic modulus of the target heterogeneous rock, the mapping relationship between the overall macroscopic elastic modulus of the rock and the microscopic stiffness of the rock, determine the global reference stiffness value based on the overall macroscopic elastic modulus of the rock and the mapping relationship, and assign the global reference stiffness value as the initial stiffness parameter and the preset high strength parameter to all mineral components of the rock mechanics model respectively. The elastic response proportionality coefficient between the micro-elastic modulus of each mineral component in the rock mechanics model and the macro-elastic modulus of the rock as a whole is determined. Based on the elastic response proportionality coefficient, the initial stiffness parameter of each mineral component in the rock mechanics model is iteratively optimized. Based on the iterative optimization result, the ultimate stiffness parameter of each mineral component is determined. Based on the ultimate stiffness parameter, the calibration elastic parameter of the corresponding mineral component is determined. The elastic parameter calibration of each mineral component in the rock mechanics model is performed using the calibration elastic parameter. The stress-strain curve of the rock mechanics model after elastic parameter calibration is determined, the simulated peak intensity in the stress-strain curve is extracted, the preset high strength parameter is iteratively adjusted based on the difference between the simulated peak intensity and the preset standard peak intensity, the calibration strength parameter is determined based on the iterative adjustment result, and the strength parameter is calibrated by the calibrated strength parameter to obtain the rock mechanics model after mechanical parameter calibration.

6. The thermo-mechanical coupling modeling method for differential damage in heterogeneous rocks according to claim 5, characterized in that, After calibrating the rock mechanics model with calibrated elastic parameters using the calibrated strength parameters to obtain the rock mechanics model with calibrated mechanical parameters, the method further includes: The mechanical parameter verification scenarios of the rock mechanics model after mechanical parameter calibration are determined, wherein the mechanical parameter verification scenarios include a preset number of mutually independent and unequal principal stress constraint scenarios and isothermal boundary condition scenarios. In the mechanical parameter verification scenario, the rock mechanics model after mechanical parameter calibration is subjected to mechanical response simulation. Based on the mechanical response simulation, mechanical response prediction data is determined. In the mechanical parameter verification scenario, mechanical response test is conducted on the target heterogeneous rock. Based on the mechanical response test results, mechanical response physical data is determined. Based on the mechanical response prediction data and the mechanical response physical data, the mechanical parameter calibration effect of the rock mechanics model is determined.

7. The thermo-mechanical coupling modeling method for differential damage in heterogeneous rocks according to claim 1, characterized in that, The thermo-coupling analysis of the target heterogeneous rock based on the thermo-coupling model includes: The initial temperature, target arrival temperature, and temperature change interval of the simulated temperature field are determined. Based on the initial temperature, target arrival temperature, and temperature change interval, the thermo-mechanical coupling model is used to perform thermal and mechanical analysis of the target heterogeneous rock under multiple temperature gradients.

8. A thermo-mechanical coupling modeling device for differential damage in heterogeneous rocks, characterized in that, include: A geometric model construction unit is used to obtain the geometric structural feature parameters of the target heterogeneous rock and construct a rock geometric model of the target heterogeneous rock based on the geometric structural feature parameters. The mechanical model construction unit is used to divide every two adjacent particles into intracrystalline contact pairs or intercrystalline contact pairs based on the type of each particle in the rock geometry model, simulate the internal bonding behavior of the intracrystalline contact pairs, simulate the intercrystalline interface slip behavior of the intercrystalline contact pairs, and construct the rock mechanical model of the target heterogeneous rock based on the simulation results of the internal bonding behavior and the simulation results of the intercrystalline interface slip behavior. In the case of the two adjacent particles in the intracrystalline contact pairs having the same particle type, the two adjacent particles in the intercrystalline contact pairs having different particle types. The function construction unit is used to construct temperature dependence functions for multiple key thermal parameters of the target heterogeneous rock, wherein the temperature dependence functions for multiple key thermal parameters include a thermal expansion coefficient function, a thermal resistance function, and a friction coefficient function with temperature as the independent variable. The coupling analysis unit is used to embed the temperature dependence function of each key thermal parameter into the rock mechanics model to obtain a thermo-mechanical coupling model that considers thermal damage variables, and to perform thermo-mechanical coupling analysis on the target heterogeneous rock based on the thermo-mechanical coupling model.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

Images