A method for predicting thermal damage of different composition rocks based on PFC numerical research
By simulating the relationship between thermal expansion and thermal damage of rocks with different mineral compositions using PFC2D software, a thermal damage prediction model was established, which solved the challenge of rock failure under high temperature conditions to construction safety and realized the prediction of rock thermal damage and guidance for deep geological energy.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHANGZHOU UNIV
- Filing Date
- 2023-10-19
- Publication Date
- 2026-06-23
AI Technical Summary
Existing technologies are insufficient to effectively predict the impact of rock damage caused by thermal expansion and cracking on construction safety, especially since the influence of minerals with high thermal expansion coefficients, such as quartz, on the degree of thermal cracking under high-temperature conditions has not been fully considered.
A grain-based model was constructed using PFC2D software. The microcrack propagation and mechanical response of rocks with different mineral compositions under high temperature conditions were simulated through a contact model. The relationship between thermal expansion and thermal damage was analyzed, and a thermal damage prediction model was established. Thermal damage was calculated using the formula DT=1-(ET/E0). An empirical formula α=(5.64×10-5T)PQ+0.0027T+0.295 was established by fitting the relationship between the coefficient of thermal expansion and quartz content to predict thermal damage.
This paper presents a simple and practical method to predict the thermal damage of rocks in high-temperature environments using known mineral composition and loading temperature, thereby guiding the site selection, design, and construction of deep geological energy resources.
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Figure CN117473716B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of high-temperature wellbore stability analysis technology, and in particular to a method for predicting thermal damage to rocks of different compositions based on PFC numerical studies. Background Technology
[0002] With rapid economic development, our demand for coal and oil resources is increasing. However, traditional resources face increasingly serious environmental problems. On the other hand, geothermal energy is a clean and renewable energy source, and its development and utilization have received widespread attention.
[0003] Hot dry rock is a typical geothermal resource, mainly located in rock formations at depths of 3,000 to 10,000 meters below the Earth's surface. Research on rock damage under thermal stress is fundamental to geothermal reservoir development. During geothermal or deep energy extraction, rock damage and fractures caused by thermal expansion pose significant challenges to construction safety. Minerals with high thermal expansion coefficients (especially quartz) play a crucial role in the degree of thermal cracking. Summary of the Invention
[0004] In view of the problems of rock damage and the resulting disruption to construction safety caused by thermal expansion and cracking, this invention is proposed.
[0005] Therefore, the problem to be solved by this invention is how to provide a model based on grains constructed using PFC2D software to simulate the microcrack propagation and mechanical response of rocks with different mineral compositions under high temperature conditions; analyze the relationship between thermal expansion and thermal damage of rocks with different mineral compositions; and establish a thermal damage prediction model for rocks with different mineral compositions.
[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:
[0007] In a first aspect, embodiments of the present invention provide a method for predicting thermal damage of rocks with different compositions based on PFC numerical research. The method includes: establishing a particle-based numerical model using PFC2D, wherein the numerical model uses a contact model; uniformly heating the rock boundary by applying temperature, performing mechanical experimental simulation of the rock under high temperature conditions, and then directly applying axial loading to obtain stress-strain curves and microcrack propagation; calculating thermal damage using elastic modulus damage, analyzing the relationship between the thermal expansion coefficient and thermal damage of rocks with different mineral compositions, and proposing a thermal damage prediction model for rocks with different mineral compositions under high temperature conditions.
[0008] As a preferred embodiment of the PFC-based numerical study method for predicting thermal damage in rocks of different compositions as described in this invention, the contact model includes a linear parallel bond model used within grains; a smooth-joint model is used to characterize contact along grain boundaries; parameter verification is based on Lac du Bonnet granite, and the microscopic parameters of the rock model are calibrated by comparing the results of Brazilian splitting, uniaxial and triaxial compression experiments with simulation results, and rock samples with different mineral compositions are generated.
[0009] As a preferred embodiment of the method for predicting thermal damage of rocks with different compositions based on PFC numerical research according to the present invention, the rock model microstructure parameters include basic physical property parameters of all particle units, parallel bonding parameters, and smooth bonding parameters.
[0010] As a preferred embodiment of the PFC-based numerical study-based method for predicting thermal damage in rocks of different compositions as described in this invention, the thermal damage is calculated using uniaxial conditional thermal damage, as shown in the following formula:
[0011] D T =1-(E T / E0)
[0012] Where E0 is the elastic modulus; E T This represents the elastic modulus after heat loading.
[0013] As a preferred embodiment of the PFC-based numerical study method for predicting thermal damage in rocks of different compositions as described in this invention, the analysis of the relationship between the thermal expansion coefficient and thermal damage in rocks of different mineral compositions includes the following steps: Due to the linear relationship between the thermal expansion coefficient and quartz content, the relationship between the thermal expansion coefficient and quartz content of rocks under different temperature conditions is fitted as follows:
[0014] α=k (T) P Q +b (T)
[0015] Where α is the linear thermal expansion coefficient, P Q The content of quartz is T, and the heat loading temperature is T.
[0016] The coefficients k and b, calculated for different quartz contents, are fitted to the temperature variations as follows:
[0017] k (T) = (5.64 × 10 -5 T+0.0125
[0018] b (T) =0.0027T+0.295
[0019] Where k(T) and b(T) are functions of the slope k and intercept b as a function of temperature, respectively.
[0020] As a preferred embodiment of the PFC-based numerical study method for predicting thermal damage in rocks with different compositions as described in this invention, the analysis of the relationship between the thermal expansion coefficient and thermal damage of rocks with different mineral compositions further includes: substituting the fitted k(T) and b(T) into the formula α relating the thermal expansion coefficient of rocks to quartz content under different temperature conditions, to obtain the following empirical formula:
[0021] α=(5.64×10 -5 T)P Q +0.0027T+0.295
[0022] As volumetric thermal strain increases, thermal damage gradually increases.
[0023] As a preferred embodiment of the PFC-based numerical study-based method for predicting thermal damage in rocks of different compositions according to the present invention, the relationship between thermal damage and volumetric thermal strain is as follows:
[0024]
[0025] Where, ε v Let a be the volumetric thermal strain, and a, b, and c be the model parameters related to peak damage, curvature, and curve shape, respectively. Under uniaxial conditions, the volumetric thermal strain is:
[0026] ε v =ΔTα
[0027] Where ΔT is the temperature change;
[0028] Substituting the fitted parameter values into the function yields:
[0029]
[0030] The coefficient of thermal expansion α is a function of the mineral quartz content and temperature T.
[0031] Secondly, to further address the problems of rock damage caused by thermal expansion and cracking, and the resulting damage to construction safety, this invention provides a PFC-based numerical research system for predicting thermal damage in rocks of different compositions. The system includes a modeling module for establishing a particle-based numerical model using PFC2D and setting up a contact model between particles; a processing module for heating the model boundaries and then applying axial loading to conduct high-temperature mechanical numerical tests; an analysis module for calculating thermal expansion, elastic modulus, stress-strain, and microcrack propagation results; calculating thermal damage; analyzing the relationship between rock mineral composition and thermal parameters; establishing a prediction model; a microcrack model for describing crack generation and propagation behavior; a thermal damage model for calculating rock thermal damage based on thermal stress and thermal expansion; and a prediction model for integrating rock mineral composition and thermal parameter data to establish a predictive mathematical model for thermal damage under high-temperature conditions.
[0032] Thirdly, embodiments of the present invention provide a computer device, including a memory and a processor, wherein the memory stores a computer program, and the computer program, when executed by the processor, implements any step of the method for predicting thermal damage of rocks of different compositions based on PFC numerical research as described in the first aspect of the present invention.
[0033] Fourthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the method for predicting thermal damage of rocks of different compositions based on PFC numerical studies as described in the first aspect of the present invention.
[0034] The beneficial effects of this invention are as follows: Based on the PFC discrete element method, a multi-mineral rock particle model is established; the proposed simple formula is quite practical, that is, without the need for mechanical experiments, only the mineral composition of the rock and the temperature to be applied are needed to easily predict the thermal damage of the rock in a high-temperature environment; from an engineering perspective, our empirical formula provides guidance for the site selection, design and construction of deep geological energy. Attached Figure Description
[0035] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:
[0036] Figure 1 This is a microstructure diagram of the LdB rock in Example 1.
[0037] Figure 2The figures show two contact models for the numerical specimen in Example 1: (a) smooth-joint model and (b) liner parallel bond model.
[0038] Figure 3 The figure shows the numerical model of quartz content in Example 1 (from darkest to lightest: plagioclase, K feldspar, quartz, biotite, Q is the quartz content).
[0039] Figure 4 This is a damage envelope diagram of the rock in Example 2.
[0040] Figure 5 The figure shows the stress-strain curve and microcrack propagation process (uniaxial compression experiment) in Example 2.
[0041] Figure 6 This is a graph showing the relationship between the coefficient of thermal expansion and the quartz content in Example 2.
[0042] Figure 7 This is a graph showing the relationship between the fitting parameters and temperature in Example 2.
[0043] Figure 8 This is a graph showing the relationship between volumetric thermal strain and thermal damage for rocks with different quartz contents in Example 2. Detailed Implementation
[0044] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
[0045] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.
[0046] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.
[0047] Example 1
[0048] Reference Figures 1-3This is the first embodiment of the present invention, which provides a method for predicting thermal damage of rocks with different compositions based on PFC numerical research. Due to limitations in experimental conditions, PFC discrete element analysis is widely used in rock mechanics research. This invention utilizes PFC2D software to construct a grain-based model; describes the model development method and calibrates the model's microscopic parameters; simulates the microcrack propagation and mechanical response of rocks with different mineral compositions under high-temperature conditions; analyzes the relationship between thermal expansion and thermal damage of rocks with different mineral compositions; and establishes a thermal damage prediction model for rocks with different mineral compositions. Specifically, it includes the following steps:
[0049] S1: Establish a particle-based numerical model using PFC2D, in which two contact models are used.
[0050] Preferably, the microstructure of LdB granite is as follows: Figure 1 As shown, the grain structure of granite is mostly polygonal. Two contact models are used in the numerical model ( Figure 2 The internal grain structure uses a linear parallel bond model to generate deformable and brittle grains; a smooth-joint model is used to characterize contact along grain boundaries, which is assigned to the model by the initially established grain boundary structure; based on the physical and mechanical properties of LdB granite, the microscopic parameters of the rock model are calibrated by comparing the results of Brazilian splitting, uniaxial, and triaxial compression experiments with simulation results. Figure 5 and Figure 4 As shown, rock samples with different mineral compositions were generated, such as... Figure 3 As shown.
[0051] Furthermore, the microstructure parameters of the rock include the basic physical properties of all grain units (disk size 0.4mm-0.6mm, crystal size 12mm-13mm), parallel bonding parameters, and smooth bonding parameters.
[0052] S2: By uniformly heating the rock boundary with a temperature, and conducting mechanical experiments on the rock under high temperature conditions (25℃-600℃), axial loading is directly applied to obtain stress-strain curves and microcrack propagation.
[0053] Preferably, the temperature is first applied to the rock boundary, with an initial temperature of 25°C, and then increased by 1°C every 100 steps to achieve uniform heating.
[0054] S3: Thermal damage is calculated by elastic modulus damage, the relationship between thermal expansion coefficient and thermal damage of rocks with different mineral compositions is analyzed, and a thermal damage prediction model for rocks with different mineral compositions under high temperature conditions is proposed.
[0055] Preferably, a thermal damage prediction model for rocks with different mineral compositions is established by analyzing the relationship between thermal expansion and thermal damage.
[0056] By analyzing the simulation results, the propagation of microcracks and mechanical damage behavior of rocks with different mineral compositions were revealed. Thermal damage was calculated by the change of elastic modulus, and it was clarified that volumetric thermal strain is the main factor determining thermal damage of rocks.
[0057] Specifically, due to the linear relationship between the coefficient of thermal expansion and quartz content, the relationship between the coefficient of thermal expansion and quartz content of rocks under different temperature conditions is fitted. Then, the relationship between relevant parameters and temperature is fitted to establish a thermal damage prediction model considering the mineral composition of rocks under high temperature conditions. The established model is reasonable and reliable, and the prediction of thermal damage is relatively simple. It has a certain novelty and is easy to apply in practice, providing a new method and idea for the prediction of thermal damage of rocks with different mineral compositions.
[0058] Furthermore, thermal damage is calculated using uniaxial conditional thermal damage, as shown in the following formula:
[0059] D T =1-(E T / E0)
[0060] Where E0 is the elastic modulus; E T This represents the elastic modulus after heat loading.
[0061] Because of the linear relationship between the coefficient of thermal expansion and quartz content, the relationship between the coefficient of thermal expansion and quartz content of rocks under different temperature conditions is fitted, such as... Figure 6 As shown:
[0062] α=k (T) P Q +b (T)
[0063] Where α is the linear thermal expansion coefficient, P Q The quartz content is T, and the heat loading temperature is T.
[0064] The coefficients k and b calculated for different quartz contents are as follows: Figure 7 As shown; the changes of coefficients k and b with temperature can be fitted as follows:
[0065] k (T) = (5.64 × 10 -5 T+0.0125
[0066] b (T) =0.0027T+0.295
[0067] Where k(T) and b(T) are functions of the slope k and intercept b as a function of temperature, respectively.
[0068] Furthermore, the analysis of the relationship between the thermal expansion coefficient and thermal damage of rocks with different mineral compositions also includes: substituting the fitted k(T) and b(T) into the formula α relating the thermal expansion coefficient of rocks to quartz content under different temperature conditions, resulting in the following empirical formula:
[0069] α=(5.64×10 -5 T)P Q +0.0027T+0.295
[0070] With increasing volumetric thermal strain, more thermal damage occurs; furthermore, under uniaxial conditions, the relationship curves between thermal damage and volumetric thermal strain overlap for samples with different quartz contents, indicating that these curves may follow the same function or rule, such as... Figure 8 As shown, the formula relating thermal damage and volumetric thermal strain is as follows:
[0071]
[0072] Where, ε v Let a be the volumetric thermal strain, and a, b, and c be the model parameters related to peak damage, curvature, and curve shape, respectively. Under uniaxial conditions, the volumetric thermal strain is:
[0073] ε v =ΔTα
[0074] Where ΔT is the temperature change; substituting the fitted parameter values into the function yields:
[0075]
[0076] The coefficient of thermal expansion α is a function of the mineral quartz content and temperature T; therefore, we can use this empirical formula to predict the thermal damage of rocks with different quartz contents.
[0077] This embodiment also provides a PFC-based numerical research system for predicting thermal damage in rocks with different compositions. The system includes a modeling module for establishing a particle-based numerical model using PFC2D and setting up a contact model between particles; a processing module for applying temperature to the model boundary for heating, followed by axial loading to conduct high-temperature mechanical numerical tests; an analysis module for calculating thermal expansion, elastic modulus, stress-strain, and microcrack propagation results; calculating thermal damage, analyzing the relationship between rock mineral composition and thermal parameters, and establishing a prediction model; a microcrack model for describing crack generation and propagation behavior; a thermal damage model for calculating thermal damage in rocks based on thermal stress and thermal expansion; and a prediction model for integrating rock mineral composition and thermal parameter data to establish a predictive mathematical model for thermal damage under high-temperature conditions.
[0078] This embodiment also provides a computer device applicable to the prediction of thermal damage of rocks with different compositions based on PFC numerical studies, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the prediction of thermal damage of rocks with different compositions based on PFC numerical studies as proposed in the above embodiment.
[0079] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.
[0080] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements the prediction of thermal damage in rocks of different compositions based on PFC numerical studies as proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.
[0081] In summary, this invention establishes a multi-mineral rock particle model based on the PFC discrete element method; the proposed simple formula is quite practical, that is, without the need for mechanical experiments, only the mineral composition of the rock and the temperature to be applied are needed to easily predict the thermal damage of the rock in a high-temperature environment; from an engineering perspective, our empirical formula provides guidance for the site selection, design and construction of deep geological energy resources.
[0082] Example 2
[0083] Reference Figures 4-8 This is the second embodiment of the present invention. Based on the first embodiment, experimental simulation data of the present invention is provided to verify its beneficial effects.
[0084] Figure 4 The stress-strain curves and microcrack propagation process are shown. Under uniaxial conditions, the microcracks are mainly grain boundary tensile cracks, and the direction of the macroscopic cracks is approximately parallel to the axial (perpendicular) loading direction, which is consistent with the experimental results.
[0085] As shown in Table 1 and Figure 5 As shown, the experimental data and simulation data are in good agreement. The failure envelope obtained by the particle-based model can satisfy the Hoek-Brown failure criterion and the Mohr-Coulomb failure criterion under high constraint pressure.
[0086] Table 1 Comparison of Simulation and Experimental Results of Mechanical Properties of LDB Granite
[0087] Macroscopic mechanical properties Experimental results Simulation results Elastic modulus, E (GPa) 69±5.8 70.2 Poisson's ratio, ν 0.26±0.04 0.25 <![CDATA[Uniaxial compressive strength, σ c (MPa)]]> 200±22 199.6 <![CDATA[Tensile strength, σ t (MPa)]]> 7.4±1.04 7.5 <![CDATA[Ratio of compressive strength to tensile strength, σ c / σ t > 27.0 26.7
[0088] Experiments have shown that highly thermally expanding quartz minerals are one of the main components of granite and play an important role in controlling the thermal expansion of rocks; generally, thermal expansion increases with increasing quartz content. Figure 6 As shown, the simulation results demonstrate a good linear relationship between the coefficient of thermal expansion and the quartz content. To establish the relationship between the coefficient of thermal expansion and temperature, the relationship between the slope k and the intercept b and the temperature was linearly fitted. Figure 7 .
[0089] like Figure 8 As shown, with the increase of volumetric thermal strain, more thermal damage occurs. Without confining pressure, D T The thermal damage initially rises rapidly, then gradually increases after most of the quartz grains break down. Furthermore, for samples with different quartz contents, the curves showing the relationship between thermal damage and volumetric thermal strain overlap, indicating that these curves follow the same function or law.
[0090] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.
Claims
1. A method for predicting thermal damage in rocks of different compositions based on PFC numerical studies, characterized in that: include: A particle-based numerical model was established using PFC2D, in which n contact models were used. The contact models included a linear parallel bond model used within the grains and a smooth-joint model used to characterize contacts along grain boundaries. The parameter calibration was based on the Lac du Bonnet granite. The microscopic parameters of the rock model were calibrated by comparing the results of Brazilian splitting, uniaxial and triaxial compression experiments with the simulation results, and rock samples with different mineral compositions were generated. The microscopic parameters of the rock model include the basic physical properties of all grain units, parallel bonding parameters, and smooth bonding parameters; By uniformly heating the rock boundary with a temperature, and conducting mechanical experiments on the rock under high temperature conditions, axial loading was directly applied to obtain stress-strain curves and microcrack propagation. Thermal damage was calculated by elastic modulus damage, the relationship between thermal expansion coefficient and thermal damage of rocks with different mineral compositions was analyzed, and a thermal damage prediction model for rocks with different mineral compositions under high temperature conditions was proposed. The relationship between thermal damage and volumetric thermal strain is expressed by the following formula: in, For volumetric thermal strain, , , These are the model parameters related to peak damage, curvature, and curve shape, respectively. Under uniaxial conditions, the volumetric thermal strain is: Substituting the fitted parameter values into the function yields: The coefficient of thermal expansion Regarding the mineral quartz content and temperature The function.
2. The method for predicting thermal damage in rocks of different compositions based on PFC numerical studies as described in claim 1, characterized in that: The thermal damage is calculated using uniaxial conditional thermal damage, as shown in the following formula: in, It is the elastic modulus; This represents the elastic modulus after heat loading.
3. The method for predicting thermal damage in rocks of different compositions based on PFC numerical studies as described in claim 2, characterized in that: The analysis of the relationship between the thermal expansion coefficient and thermal damage of rocks with different mineral compositions includes the following steps: Due to the linear relationship between the coefficient of thermal expansion and quartz content, the relationship between the coefficient of thermal expansion and quartz content of rocks under different temperature conditions is fitted as follows: in, The coefficient of linear thermal expansion is 1. The content of quartz, This refers to the heat loading temperature; Coefficients calculated for different quartz contents and The temperature change is fitted as follows: in, and Slope and intercept The function that varies with temperature.
4. The method for predicting thermal damage in rocks of different compositions based on PFC numerical studies as described in claim 3, characterized in that: The analysis of the relationship between the thermal expansion coefficient and thermal damage of rocks with different mineral compositions also includes: Fitting the changes and Substitute into the formula relating the thermal expansion coefficient of rocks to quartz content under different temperature conditions From this, we obtain the following empirical formula: As volumetric thermal strain increases, thermal damage gradually increases.
5. A thermal damage prediction system for rocks of different compositions based on PFC numerical studies, based on the thermal damage prediction method for rocks of different compositions based on PFC numerical studies according to any one of claims 1 to 4, characterized in that: include, The modeling module is used to build particle-based numerical models using PFC2D and set the contact models between particles. The processing module is used to apply temperature to the model boundary to heat it, and then apply axial loading to conduct high-temperature mechanical numerical tests. The analysis module is used to calculate thermal expansion, elastic modulus, stress and strain, and microcrack propagation results. Calculate thermal damage, analyze the relationship between rock mineral composition and thermal parameters, and establish a prediction model; Microcrack models are used to describe the initiation and propagation behavior of cracks; A thermal damage model for calculating thermal damage to rocks based on thermal stress and thermal expansion. Predictive models are used to integrate rock mineral composition and thermal parameter data to establish predictive mathematical models of thermal damage under high-temperature conditions.
6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the method for predicting thermal damage of rocks with different compositions based on PFC numerical research as described in any one of claims 1 to 4.
7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the method for predicting thermal damage of rocks of different compositions based on PFC numerical research as described in any one of claims 1 to 4.