A freezing-thawing damage creep analysis method and system for surrounding rock of a tunnel in a cold region

Abstract

The present application is suitable for the technical field of rock mass engineering analysis, and provides a freezing-thawing damage creep analysis method and system for surrounding rock of a tunnel in a cold region, which comprises the following steps: constructing a mineral particle thermal expansion heterogeneity index; obtaining a non-uniform evolution characteristic parameter of a rock mesostructure under the action of freezing-thawing cycles, and establishing a mapping relationship between a freezing-thawing damage variable and the mineral particle thermal expansion heterogeneity index; constructing a voiceprint-creep coupling response relationship; based on the mapping relationship between the freezing-thawing damage variable and the mineral particle thermal expansion heterogeneity index, and the voiceprint-creep coupling response relationship, constructing a variable-parameter creep damage constitutive model; and based on the variable-parameter creep damage constitutive model, obtaining freezing-thawing damage creep analysis results for surrounding rock of a tunnel in a cold region. The present application can describe the evolution law of creep mechanical parameters from the aspect of mineral thermal mismatch mechanism, thereby significantly improving the accuracy and engineering applicability of the calculation results of the displacement field, stress field and plastic yield zone distribution of the surrounding rock of a typical section of a tunnel in a cold region.

Description

Technical Field

[0001] This invention belongs to the field of rock mass engineering analysis technology, and in particular relates to a method and system for analyzing freeze-thaw damage and creep in the surrounding rock of tunnels in cold regions. Background Technology

[0002] Rock mass engineering in cold regions faces complex geographical environments and climatic conditions such as seasonal freeze-thaw cycles and high-altitude cold regions. Tunnels (especially short and medium-sized tunnels), roadbeds, and slopes along the route are subjected to huge temperature changes during seasonal transitions and diurnal cycles, resulting in freeze-thaw disasters of varying degrees, such as frost heave cracking, freeze-thaw landslides, and slope instability. The stability and safety of rock mass engineering are greatly threatened.

[0003] Currently, scholars both domestically and internationally have conducted extensive research on the characterization of freeze-thaw damage and the constitutive modeling of creep in rocks. Regarding freeze-thaw damage characterization, existing techniques primarily rely on macroscopic physical and mechanical indicators such as longitudinal wave velocity attenuation, mass loss rate, and porosity changes to evaluate the degree of freeze-thaw damage. For example, ultrasonic detectors measure the change in longitudinal wave velocity of rocks before and after freeze-thaw cycles, using the velocity attenuation rate as an indirect indicator of freeze-thaw damage; or nuclear magnetic resonance (NMR) technology is used to obtain the T2 spectrum distribution curve of rock pores, using peak area changes to characterize pore structure evolution. In acoustic emission monitoring, existing studies have used parameters such as acoustic emission counts, energy, b-value, and RA-AF values ​​for real-time monitoring of rock fracture processes, and combined this with critical slowing theory for early warning of damage precursors. In deformation field measurement, the digital image correlation (DIC) method has been used for full-field strain analysis during the loading process of freeze-thawed rocks. Regarding creep constitutive modeling, existing techniques mainly employ modified Nishihara models or fractional derivative models, introducing damage variables to correct creep parameters.

[0004] However, existing technologies have the following major shortcomings that urgently need improvement: First, the characterization of freeze-thaw damage is limited to a single dimension. Current methods mostly evaluate freeze-thaw damage from a single perspective, such as macroscopic wave velocity attenuation or porosity changes, neglecting the essential driving factor of freeze-thaw damage—the non-uniform thermal mismatch stress generated between different mineral particles within the rock due to differences in their coefficients of thermal expansion. The coefficients of thermal expansion of major rock-forming minerals such as quartz, feldspar, and mica differ significantly. During repeated freeze-thaw cycles, this heterogeneity leads to cumulative thermal stress damage at the particle interfaces, which is the fundamental cause of the initiation of microscopic freeze-thaw damage. However, existing technologies lack quantitative characterization methods for this crucial factor.

[0005] Second, the multimodal monitoring data are fragmented. Although existing studies have used CT scans to obtain internal microstructure, acoustic emission monitoring to obtain crack acoustic characteristics, and DIC to obtain surface deformation fields, these three types of data are usually collected and analyzed independently. There is a lack of a unified analytical framework to link and integrate the microstructure evolution, acoustic emission response, and creep deformation.

[0006] Third, the damage variables in constitutive models lack a microphysical basis. In existing variable-parameter creep constitutive models, damage variables are usually only expressed as empirical functions of the number of freeze-thaw cycles, or simplified as the decay rate of the macroscopic elastic modulus. They lack the microphysical mechanism based on the thermal mismatch stress at the mineral grain scale as support, resulting in insufficient generalization ability of the model to complex freeze-thaw conditions. Summary of the Invention

[0007] The purpose of this invention is to provide a method for analyzing the creep of frozen-thaw damage in the surrounding rock of tunnels in cold regions, thereby solving the aforementioned technical problems.

[0008] This invention is implemented as follows: a method for analyzing freeze-thaw damage and creep in the surrounding rock of tunnels in cold regions, comprising the following steps: constructing a mineral particle thermal expansion heterogeneity index; the mineral particle thermal expansion heterogeneity index is used to quantitatively characterize the level of non-uniform thermal mismatch stress caused by the difference in thermal expansion coefficients between different mineral components inside the rock.

[0009] To obtain the non-uniform evolution characteristic parameters of rock microstructure under freeze-thaw cycles.

[0010] Based on the aforementioned non-uniform evolution characteristic parameters, a mapping relationship is established between freeze-thaw damage variables and the thermal expansion heterogeneity index of mineral particles.

[0011] Based on graded loading and unloading creep tests, the acoustic signature-creep coupling response relationship is constructed.

[0012] Based on the mapping relationship between the freeze-thaw damage variables and the thermal expansion heterogeneity index of mineral particles, as well as the acoustic signature-creep coupling response relationship, a variable parameter creep damage constitutive model is constructed.

[0013] Based on the aforementioned variable parameter creep damage constitutive model, a typical cross-section of a tunnel in a cold region was selected, and the results of the freeze-thaw damage creep analysis of the surrounding rock of the tunnel in a cold region were calculated.

[0014] Furthermore, the steps for constructing the thermal expansion heterogeneity index of mineral particles specifically include: selecting representative rock samples of the surrounding rocks of tunnels in cold regions.

[0015] Obtain the volume fraction of each mineral component, the average particle size of minerals, and the coefficient of linear thermal expansion in representative rock samples.

[0016] A mineral particle thermal expansion heterogeneity index is constructed based on the volume fraction of each mineral component, the average particle size of the mineral particles, and the linear thermal expansion coefficient.

[0017] Furthermore, the formula for calculating the thermal expansion heterogeneity index of the mineral particles is as follows: In the formula, H is the thermal expansion heterogeneity index of mineral particles; V i V jThese are the volume fractions of the i-th and j-th mineral components, respectively; , The linear thermal expansion coefficients of the i-th and j-th mineral components are respectively; d i d j , respectively, are the average particle sizes of the mineral particles of the i-th and j-th mineral components; The particle contact probability factors for the i-th and j-th mineral components are determined by the spatial correlation function method based on backscattered electron images.

[0018] Furthermore, the spatial correlation function method based on backscattered electron images includes the following steps: First, after polishing the surface of a representative rock sample, a high-resolution mineral distribution image is acquired using the backscattered electron mode of a scanning electron microscope. Different mineral components exhibit different gray levels due to their different average atomic numbers. Next, energy dispersive spectroscopy (EDS) is used to calibrate the mineral component categories corresponding to each gray level region, and a mineral phase distribution map is generated using an image segmentation algorithm, assigning a mineral component category label to each pixel. Then, a large number of pixel pairs are randomly selected from the mineral phase distribution map, and the probabilities of two pixels with a distance of r belonging to the i-th and j-th mineral components, respectively, are calculated to determine the correlation function between the two points. Extrapolating the correlation function between these two points to the limit value as r→0 is taken as the particle contact probability factor for the i-th and j-th mineral components, i.e. .

[0019] Furthermore, the steps for obtaining the non-uniform evolution characteristic parameters of the rock microstructure under freeze-thaw cycles specifically include: first, conducting multiple freeze-thaw cycle tests on representative rock samples, and acquiring three-dimensional CT volume data of the representative rock samples before and after each freeze-thaw cycle test; then, performing digital volume image correlation analysis on the three-dimensional CT volume data to extract the non-uniform evolution characteristic parameters of the pore-fracture network inside the rock under different freeze-thaw cycle numbers; the non-uniform evolution characteristic parameters include pore connectivity, fracture fractal dimension, and local strain concentration coefficient.

[0020] Furthermore, the pore connectivity is defined as the ratio of the number of largest connected cluster voxels in the pore-fracture network to the total number of all pore-fracture voxels after the freeze-thaw cycle test; the fracture fractal dimension is calculated using the box counting method to quantitatively characterize the complexity and filling capacity of the spatial distribution of the pore-fracture network under freeze-thaw cycles; the local strain concentration factor is defined as the ratio of the average equivalent strain of the largest equivalent strain voxel in the pre-preset percentage in the three-dimensional strain field after the freeze-thaw cycle test to the average equivalent strain of the entire field.

[0021] Furthermore, the step of establishing a mapping relationship between freeze-thaw damage variables and the thermal expansion heterogeneity index of mineral particles based on the aforementioned non-uniform evolution characteristic parameters specifically includes: first, calculating the freeze-thaw damage variables after each freeze-thaw cycle test based on the aforementioned pore connectivity and fracture fractal dimension; then, performing regression analysis on the freeze-thaw damage variables and the thermal expansion heterogeneity index of mineral particles to establish a mapping relationship between the freeze-thaw damage variables and the thermal expansion heterogeneity index of mineral particles.

[0022] Furthermore, the steps for constructing the acoustic emission-creep coupling response relationship based on the graded loading and unloading creep test specifically include: conducting graded loading and unloading creep tests on representative rock samples after multiple freeze-thaw cycles, and simultaneously acquiring acoustic emission signals during the graded loading and unloading creep test.

[0023] Waveform analysis and parameter extraction are performed on the acoustic emission signal to obtain acoustic signature feature parameters; the acoustic signature feature parameters include acoustic emission count rate, acoustic emission energy rate, b value, RA-AF value distribution and peak frequency-amplitude spectrum characteristics.

[0024] The creep process of the staged loading and unloading creep test is divided into a decay creep stage, a steady-state creep stage, and an accelerated creep stage, and the creep mechanical parameters of each creep stage are extracted. The creep mechanical parameters include instantaneous elastic strain, viscoelastic strain, viscoplastic strain, steady-state creep rate, and accelerated creep initiation time.

[0025] The acoustic signature feature parameters and creep mechanical parameters are aligned and correlated in the time domain to construct the acoustic signature-creep coupling response relationship.

[0026] Furthermore, based on the mapping relationship between the freeze-thaw damage variables and the thermal expansion heterogeneity index of mineral particles, as well as the acoustic signature-creep coupling response relationship, the step of constructing a variable parameter creep damage constitutive model specifically includes: establishing a damage evolution function of creep mechanical parameters, and expressing the elastic modulus, viscosity coefficient, and long-term strength as functions of the thermal expansion heterogeneity index of mineral particles, the number of freeze-thaw cycles, and deviatoric stress.

[0027] Based on the damage evolution function of creep mechanical parameters, a variable parameter creep damage constitutive model considering the thermal expansion heterogeneity of mineral particles is constructed; the variable parameter creep damage constitutive model includes three parts: instantaneous elastic strain term, viscoelastic creep strain term, and viscoplastic strain term.

[0028] The accelerated creep initiation time, predicted based on the rate of change of b value in the acoustic signature-creep coupling response relationship, is used as the triggering criterion for the viscoplastic strain term in the variable parameter creep damage constitutive model.

[0029] Another objective of this invention is to provide a system for analyzing the creep of frozen-thaw damage in the surrounding rock of tunnels in cold regions, which is used to implement the above-mentioned method for analyzing the creep of frozen-thaw damage in the surrounding rock of tunnels in cold regions. Specifically, it includes a heterogeneity index construction module for constructing a thermal expansion heterogeneity index of mineral particles.

[0030] The evolution feature extraction module is used to obtain the non-uniform evolution feature parameters of rock microstructure under freeze-thaw cycles.

[0031] The mapping relationship establishment module is used to establish a mapping relationship between freeze-thaw damage variables and the thermal expansion heterogeneity index of mineral particles based on the non-uniform evolution characteristic parameters.

[0032] The coupling relationship construction module is used to construct the acoustic signature-creep coupling response relationship based on the graded loading and unloading creep test.

[0033] The constitutive model construction module is used to construct a variable parameter creep damage constitutive model based on the mapping relationship between the freeze-thaw damage variable and the thermal expansion heterogeneity index of mineral particles, as well as the acoustic signature-creep coupling response relationship.

[0034] The analysis results output module is used to select typical cross-sections of tunnels in cold regions based on the variable parameter creep damage constitutive model, and calculate the creep analysis results of the surrounding rock freeze-thaw damage of tunnels in cold regions.

[0035] This invention provides a method for analyzing the creep of frozen-thaw damage in the surrounding rock of tunnels in cold regions. By introducing the thermal expansion heterogeneity index of mineral particles as a microscopic physical driving force index for freeze-thaw damage, and establishing the mapping relationship between freeze-thaw damage variables and the thermal expansion heterogeneity index of mineral particles, as well as the acoustic signature-creep coupling response relationship, the variable parameter creep damage constitutive model can describe the evolution law of creep mechanical parameters from the perspective of mineral thermal mismatch mechanism. This significantly improves the accuracy and engineering applicability of the calculation results of the surrounding rock displacement field, stress field, and plastic yield zone distribution of typical cross-sections of tunnels in cold regions. Attached Figure Description

[0036] Figure 1 This is a flowchart illustrating the method for analyzing freeze-thaw damage and creep in the surrounding rock of tunnels in cold regions, as provided in an embodiment of the present invention.

[0037] Figure 2 This is a flowchart illustrating step S100 in the method for analyzing freeze-thaw damage and creep in the surrounding rock of tunnels in cold regions provided in this embodiment of the invention.

[0038] Figure 3 This is a flowchart illustrating step S400 in the method for analyzing freeze-thaw damage and creep in the surrounding rock of tunnels in cold regions provided in this embodiment of the invention.

[0039] Figure 4This is a flowchart illustrating step S500 in the method for analyzing freeze-thaw damage and creep in the surrounding rock of a tunnel in a cold region, as provided in an embodiment of the present invention.

[0040] Figure 5 This is a schematic diagram of the structure of the freeze-thaw damage creep analysis system for tunnel surrounding rock in cold regions provided in an embodiment of the present invention. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0042] like Figure 1 As shown, in one embodiment of the present invention, a method for analyzing freeze-thaw damage and creep in the surrounding rock of a tunnel in a cold region is provided, comprising the following steps: S100, constructing a mineral particle thermal expansion heterogeneity index; the mineral particle thermal expansion heterogeneity index is used to quantitatively characterize the level of non-uniform thermal mismatch stress caused by the difference in thermal expansion coefficients between different mineral components inside the rock.

[0043] S200: Obtain the non-uniform evolution characteristic parameters of rock microstructure under freeze-thaw cycles.

[0044] S300. Based on the non-uniform evolution characteristic parameters, establish a mapping relationship between freeze-thaw damage variables and the thermal expansion heterogeneity index of mineral particles.

[0045] S400, based on graded loading and unloading creep test, construct the acoustic signature-creep coupling response relationship.

[0046] S500. Based on the mapping relationship between the freeze-thaw damage variables and the thermal expansion heterogeneity index of mineral particles, and the acoustic signature-creep coupling response relationship, a variable parameter creep damage constitutive model is constructed.

[0047] S600. Based on the variable parameter creep damage constitutive model, a typical cross-section of a tunnel in a cold region is selected, and the results of the freeze-thaw damage creep analysis of the surrounding rock of the tunnel in a cold region are calculated.

[0048] like Figure 2 As shown, in a preferred embodiment of the present invention, the step of constructing the thermal expansion heterogeneity index of mineral particles, namely step S100, specifically includes: S110, selecting representative rock samples of the surrounding rock of tunnels in cold regions.

[0049] S120. Obtain the volume fraction of each mineral component, the average particle size of minerals, and the coefficient of linear thermal expansion in representative rock samples.

[0050] S130. Based on the volume fraction of each mineral component, the average particle size of the mineral particles, and the linear thermal expansion coefficient, construct the thermal expansion heterogeneity index of mineral particles.

[0051] Specifically, the formula for calculating the thermal expansion heterogeneity index of mineral grains is as follows: In the formula, H is the thermal expansion heterogeneity index of mineral particles; V i V j These are the volume fractions of the i-th and j-th mineral components, respectively; , The linear thermal expansion coefficients of the i-th and j-th mineral components are respectively; d i d j , respectively, are the average particle sizes of the mineral particles of the i-th and j-th mineral components; The particle contact probability factors for the i-th and j-th mineral components can be determined using the spatial correlation function method based on backscattered electron images.

[0052] In a preferred embodiment of the present invention, the spatial correlation function method based on backscattered electron images includes the following steps: First, after polishing the surface of a representative rock sample, a high-resolution mineral distribution image is acquired using the backscattered electron mode of a scanning electron microscope. Different mineral components exhibit different gray levels due to their different average atomic numbers. Next, energy dispersive spectroscopy is used to calibrate the mineral component categories corresponding to each gray level region, and a mineral phase distribution map is generated using an image segmentation algorithm, with each pixel assigned a mineral component category label. Then, a large number of pixel pairs are randomly selected from the mineral phase distribution map, and the probabilities of two pixels with a distance of r belonging to the i-th and j-th mineral components, respectively, are calculated to determine the correlation function between the two points. Extrapolating the correlation function between these two points to the limit value as r→0 is taken as the particle contact probability factor for the i-th and j-th mineral components, i.e. .

[0053] The method for determining the two-point correlation function is as follows: Traverse all pixels in the mineral phase distribution map with a preset step size. For each pair of pixels with a spacing of r, count the number N of pixel pairs where one pixel belongs to the i-th mineral component and the other pixel belongs to the j-th mineral component. ij (r), and simultaneously count the total number N of all pixel pairs with a spacing of r. total (r), then the two-point correlation function By changing the value of the spacing r, a series of different r values ​​can be obtained. For discrete data points, the correlation function between two points can be obtained by fitting an extrapolated curve using the least squares method.

[0054] In practical applications, a typical red sandstone from a tunnel surrounding rock in a cold region is selected as a representative rock sample for illustrative purposes. After grinding the representative rock sample into powder, phase analysis is performed using an X-ray diffractometer. Quantitative analysis of the X-ray diffraction pattern is conducted using the K-value method to obtain the main mineral components (such as quartz, feldspar, calcite, mica, etc.) and their volume fractions. The representative rock sample is then ground into standard rock thin sections, observed and imaged under a polarizing microscope. Image analysis software is used to statistically analyze the equivalent diameter of each mineral particle within the field of view, obtaining the average particle size of each mineral component. Furthermore, a thermomechanical analyzer is used to measure the standard samples of each mineral component obtained above within a temperature range of -20℃ to 20℃. The average linear thermal expansion coefficient within this temperature range is then used to determine the linear thermal expansion coefficient of each mineral component in the representative rock sample. Substituting the volume fractions of each mineral component, the average particle size, and the linear thermal expansion coefficient obtained above into the calculation formula for the mineral particle thermal expansion heterogeneity index, the mineral particle thermal expansion heterogeneity index of the surrounding rock of the tunnel in the cold region can be obtained. It should be noted that due to the significant difference between the negative thermal expansion characteristics of calcite and the positive thermal expansion characteristics of quartz, and the fact that calcite, as a cementing material, has a smaller average particle size, the heterogeneity contribution of calcite and quartz has a greater contribution to the mineral particle thermal expansion heterogeneity index. This reveals from a microphysical perspective that even under the same number of freeze-thaw cycles, red sandstone with a higher calcite volume fraction will have a higher mineral particle thermal expansion heterogeneity index than red sandstone with a lower calcite volume fraction. This means that the red sandstone with a higher calcite volume fraction has greater internal thermal mismatch stress, and therefore will exhibit a faster rate of damage and deterioration in subsequent freeze-thaw cycles.

[0055] In this embodiment of the invention, by constructing a mineral particle thermal expansion heterogeneity index, the non-uniform thermal mismatch stress level caused by the difference in thermal expansion coefficients between different mineral components inside the rock is quantitatively characterized. This reveals the driving mechanism of freeze-thaw damage from a microscopic thermophysical perspective, and provides a fundamental parameter with clear physical meaning for establishing the mapping relationship between freeze-thaw damage variables and the mineral particle thermal expansion heterogeneity index.

[0056] In a preferred embodiment of the present invention, the step of obtaining the non-uniform evolution characteristic parameters of the microstructure of rocks under freeze-thaw cycles specifically includes: first, conducting multiple freeze-thaw cycle tests on representative rock samples, and obtaining three-dimensional CT volume data of representative rock samples before and after each freeze-thaw cycle test.

[0057] Then, digital volumetric image correlation analysis was performed on the three-dimensional CT volumetric data to extract the non-uniform evolution characteristic parameters of the pore-fracture network inside the rock under different freeze-thaw cycles; the non-uniform evolution characteristic parameters include pore connectivity, fracture fractal dimension and local strain concentration coefficient.

[0058] In practical applications, the aforementioned red sandstone was selected as a representative rock sample and processed into standard cylindrical specimens with a diameter of 50 mm and a height of 100 mm. A total of 6 parallel specimens were prepared. The specimens were placed in a freeze-thaw cycle test chamber, and the freeze-thaw cycle test parameters were set as follows: cooling rate: 0.5℃ / min, from 20℃ to -20℃.

[0059] First constant temperature treatment: Maintain at -20℃ for 4 hours for the first preset time.

[0060] Heating rate: 0.5℃ / min, from -20℃ to 20℃.

[0061] Second constant temperature treatment: Maintain at 20℃ for a second preset time of 4 hours.

[0062] The above process constitutes one freeze-thaw cycle test. In this embodiment of the invention, the total number of freeze-thaw cycle tests is set to 10.

[0063] After the 0th (no freeze-thaw), 1st, 3rd, 5th, 7th, and 10th freeze-thaw cycles, representative rock samples were removed from the freeze-thaw cycle chamber and CT scanned using a Phoenix v|tome|xL300 micro-nano CT scanning system. The scanning parameters were set as follows: X-ray tube voltage: 180kV.

[0064] X-ray tube current: 120μA.

[0065] Scan resolution: 4.5μm / pixel (meets the requirement of not less than 5μm / pixel).

[0066] Scanning angle: 360° rotation, 2000 projections.

[0067] Reconstruction matrix: 2000×2000×1500 voxels.

[0068] Each CT scan acquires a set of representative rock sample 3D CT volume data in 16-bit grayscale TIFF stack format. During the scanning process, the location of the representative rock sample and the scanning parameters are kept completely consistent to ensure the spatial correspondence of the 3D CT volume data under different freeze-thaw cycles.

[0069] Next, two sets of 3D CT volume data obtained from adjacent freeze-thaw cycles were analyzed using a 3D digital volume image correlation analysis algorithm based on local sub-voxel matching. The specific implementation process is as follows: The 3D CT volume data after the 0th freeze-thaw cycle was used as the reference volume data, and the 3D CT volume data after the 1st freeze-thaw cycle was used as the deformable volume data. A grid of nodes was divided in the reference volume data with a node spacing of 32 voxels. A cube sub-block with a side length of 64 voxels was defined centered on each node. The corresponding sub-block position with the highest grayscale correlation to the reference sub-block was searched in the deformable volume data, and a zero-mean normalized cross-correlation function was used as the similarity criterion. The 3D displacement vector of the sub-block center point was obtained through sub-voxel interpolation, and then the 3D displacement field inside the representative rock sample was calculated. Spatial gradient calculation was performed on this 3D displacement field to obtain the 3D strain field inside the representative rock sample, which includes three normal strain components and three shear strain components. Repeat the above operations to calculate the three-dimensional displacement field and three-dimensional strain field between the 1st and 3rd times, the 3rd and 5th times, the 5th and 7th times, and the 7th and 10th times in sequence.

[0070] Then, an image segmentation algorithm was used to process the three-dimensional strain field to extract the pore-fracture network inside the rock. The specific steps are as follows: the equivalent plastic strain at each voxel was calculated, and an equivalent plastic strain threshold of 0.5% was set. Voxels with equivalent plastic strain greater than this threshold were marked as pore-fracture regions, and voxels with equivalent plastic strain less than this threshold were marked as intact rock regions. A connected component analysis algorithm was used to process the marked binary three-dimensional image to extract the three-dimensional spatial distribution of the pore-fracture network. Taking the results after the 5th freeze-thaw cycle test as an example, the extracted pore-fracture network showed that freeze-thaw damage mainly initiated along the interface between quartz grains and calcite cement, and gradually extended into the interior of feldspar grains, forming a microfracture network that penetrates multiple mineral grains.

[0071] Finally, based on the extracted pore-fracture network, the pore connectivity, fracture fractal dimension, and local strain concentration coefficient are calculated as non-uniform evolution characteristic parameters.

[0072] Pore ​​connectivity is defined as the ratio of the number of voxels in the largest connected cluster to the total number of voxels in the pore-fracture network after freeze-thaw cycles. Specifically, firstly, each voxel in the binarized 3D image of the pore-fracture network is assigned a binary label, with voxels labeled as pores / fractures having a value of one and voxels labeled as intact rock having a value of zero. Secondly, connected component analysis is performed on the binarized 3D image using the 26-neighborhood connectivity criterion, which states that if two voxels labeled as pores / fractures are adjacent on faces, edges, or vertices in 3D space, they are considered to belong to the same connected cluster. The connected component analysis algorithm traverses all pore / fracture voxels, merging interconnected pore / fracture voxels into the same cluster and assigning a unique identifier to each cluster, while also counting the number of voxels contained in each cluster. Then, among all identified connected clusters, the cluster with the largest number of voxels is selected, and its voxel count is recorded as the largest connected cluster voxel count. Finally, the ratio obtained by dividing the number of voxels of the largest connected cluster by the total number of all pore and fracture voxels is the pore connectivity after the m-th freeze-thaw cycle. This ratio ranges from 0 to 1. The closer the ratio is to 1, the higher the degree of connectivity of the pore and fracture network. The initially isolated and dispersed micropores and microcracks have been interconnected through the cumulative effect of freeze-thaw damage to form a through fracture channel.

[0073] The fractal dimension of the fracture was calculated using box counting to quantitatively characterize the complexity and filling capacity of the spatial distribution of the pore-fracture network under freeze-thaw cycles. Specifically, the binarized 3D image of the pore-fracture network was divided into cubic boxes with side length δ, and the number B(δ) of boxes containing at least one pore-fracture voxel was counted. The side length δ of the boxes was varied from 1 voxel to 256 voxels to obtain a series of data points. Linear fitting was then performed on the data points in a double logarithmic coordinate system. Where d is a constant; the slope of the linearly fitted line. This is the fractal dimension of the crack, which can be obtained by the least squares method.

[0074] The local strain concentration factor is defined as the ratio of the average equivalent strain of the largest equivalent strain element in the three-dimensional strain field after a freeze-thaw cycle test to the average equivalent strain of the entire field. Specifically, firstly, the three-dimensional strain field inside a representative rock sample is used as the basic data. This three-dimensional strain field contains six strain components at each voxel location, namely three normal strain components and three shear strain components. Secondly, the equivalent strain value at each voxel is calculated based on the above six strain components. The calculation of equivalent strain follows the definition in classical plasticity mechanics, combining the normal strain components and shear strain components with appropriate weights into a scalar index to comprehensively reflect the deformation intensity at that voxel location. Then, the equivalent strain values ​​of all voxels in the entire field are counted, and the sum of the equivalent strain values ​​of all voxels is divided by the total number of voxels to obtain the average equivalent strain of the entire field. At the same time, all voxels in the entire field are sorted in descending order according to their respective equivalent strain values, and a subset of voxels in the top 5% of the sorted results is selected. The arithmetic mean of the equivalent strain values ​​of all voxels in this subset is calculated to obtain the average equivalent strain of the top 5%. Finally, the ratio obtained by dividing the first 5% average equivalent strain by the overall average equivalent strain is the local strain concentration factor after the m-th freeze-thaw cycle test. The larger the ratio, the more significant the localization of strain caused by freeze-thaw damage, that is, the deformation is highly concentrated in a few weak areas rather than being uniformly distributed throughout the entire rock sample. This indicates that a clear damage concentration zone has been formed inside the rock, which is a precursor microscopic indicator of the overall mechanical properties of the rock and its eventual failure.

[0075] In this embodiment of the invention, by obtaining the non-uniform evolution characteristic parameters of the pore-fracture network inside the rock under freeze-thaw cycles, the quantitative characterization of pore connectivity, fracture fractal dimension and local strain concentration coefficient during the freeze-thaw process is realized. This reveals the non-uniform damage accumulation law of the rock microstructure evolving from isolated pores to a through-fracture network, and provides reliable microscopic experimental basis for the calculation of freeze-thaw damage variables and the construction of subsequent variable parameter creep damage constitutive models.

[0076] In a preferred embodiment of the present invention, the step of establishing a mapping relationship between the freeze-thaw damage variable and the thermal expansion heterogeneity index of mineral particles based on the non-uniform evolution characteristic parameters specifically includes: firstly, calculating the freeze-thaw damage variable after each freeze-thaw cycle test based on the pore connectivity and fracture fractal dimension; specifically, the freeze-thaw damage variable F m The calculation formula is as follows: ; In the formula, C m D represents the pore connectivity after the m-th freeze-thaw cycle test. m Em is the fractal dimension of the fracture after the m-th freeze-thaw cycle test; E0 is the initial elastic modulus of the unfrozen rock sample; Em mdenoted as the equivalent elastic modulus after the m-th freeze-thaw cycle test; k is a material constant, characterizing the sensitivity of the rock's microstructure damage to the decay of the macroscopic elastic modulus, which can be obtained by nonlinear regression fitting of systematic test data of unfrozen rock samples and rock samples with different freeze-thaw cycle numbers.

[0077] Then, regression analysis is performed on the freeze-thaw damage variable and the thermal expansion heterogeneity index of mineral particles to establish a mapping relationship between the freeze-thaw damage variable and the thermal expansion heterogeneity index of mineral particles; specifically, the specific functional form of the above mapping relationship can be determined by nonlinear least squares fitting method: In the formula, a, b, and c are fitting parameters.

[0078] like Figure 3 As shown, in a preferred embodiment of the present invention, the step of constructing the acoustic signature-creep coupling response relationship based on the graded loading and unloading creep test, namely step S400, specifically includes: S410, performing a graded loading and unloading creep test on a representative rock sample after multiple freeze-thaw cycles, and simultaneously collecting acoustic emission signals during the graded loading and unloading creep test.

[0079] Specifically, the confining pressure and axial pressure are first increased synchronously to the specified confining pressure value. Then, the deviatoric stress is applied to a set value and kept constant. After a preset creep time, elastic unloading is performed, and the elastic recovery deformation during the unloading stage is recorded. The stress is then increased to the next level, and the above operation is repeated until the representative rock sample undergoes creep failure. In addition, acoustic emission signals are collected through acoustic emission sensors, which are placed on the surface of the representative rock sample, with a sampling frequency of not less than 500 kHz.

[0080] S420. Perform waveform analysis and parameter extraction on the acoustic emission signal to obtain acoustic signature feature parameters; the acoustic signature feature parameters include acoustic emission count rate, acoustic emission energy rate, b-value, RA-AF value distribution, and peak frequency-amplitude spectrum characteristics;

[0081] Specifically, the acoustic emission count rate refers to the number of acoustic emission events exceeding a preset threshold per unit time; the acoustic emission energy rate refers to the cumulative value of the envelope area of ​​the acoustic emission signal waveform per unit time; the b-value is calculated based on the maximum amplitude distribution of the acoustic emission events; in the RA-AF value distribution, RA is the ratio of rise time to maximum amplitude, and AF is the ratio of ring count to duration (average frequency). Tensile cracks and shear cracks can be distinguished based on the distribution characteristics of RA-AF values; the method for obtaining peak frequency-amplitude spectrum characteristics is as follows: perform a fast Fourier transform on the acoustic emission waveform signal to obtain the peak frequency and corresponding amplitude spectral density of the signal.

[0082] S430. Divide the creep process of the graded loading and unloading creep test into a decay creep stage, a steady-state creep stage, and an accelerated creep stage, and extract the creep mechanical parameters of each creep stage; the creep mechanical parameters include instantaneous elastic strain, viscoelastic strain, viscoplastic strain, steady-state creep rate, and accelerated creep initiation time.

[0083] Specifically, creep mechanical parameters can be extracted based on the creep curves and unloading recovery curves at various stress levels; the creep mechanical parameters include instantaneous elastic strain, viscoelastic strain, viscoplastic strain, steady-state creep rate, and accelerated creep initiation time.

[0084] S440. Perform time-domain alignment and correlation analysis between the voiceprint feature parameters and creep mechanical parameters to construct the voiceprint-creep coupled response relationship.

[0085] Specifically, the average acoustic emission count rate within the steady-state creep stage at the same stress level is correlated with the steady-state creep rate to establish a first coupling relationship. This first coupling relationship indicates that the acoustic emission count rate and the steady-state creep rate are positively correlated by a power law, and the acoustic emission activity can quantitatively reflect the creep rate level. The rate of change of the b value is correlated with the acceleration creep initiation time to establish a second coupling relationship. Based on the first and second coupling relationships, a complete acoustic signature-creep coupling response relationship can be constructed. This coupling response relationship enables a quantitative description of creep stage identification, creep rate prediction, and acceleration creep early warning through real-time acoustic emission monitoring signals.

[0086] like Figure 4 As shown, in a preferred embodiment of the present invention, the step of constructing a variable parameter creep damage constitutive model based on the mapping relationship between the freeze-thaw damage variable and the thermal expansion heterogeneity index of mineral particles, and the acoustic signature-creep coupling response relationship, namely step S500, specifically includes: S510, establishing a damage evolution function of creep mechanical parameters, expressing the elastic modulus, viscosity coefficient and long-term strength as functions of the thermal expansion heterogeneity index of mineral particles, the number of freeze-thaw cycles and the deviatoric stress.

[0087] Specifically, the damaged elastic modulus is calculated by multiplying the initial elastic modulus of the unfrozen rock sample by a reduction factor jointly determined by the freeze-thaw damage variable and the deviatoric stress level. This reduction factor decays as a quadratic function based on the ratio of the current deviatoric stress to the peak strength of the rock sample. The viscosity coefficient is calculated by multiplying the initial viscosity coefficient of the unfrozen rock sample by a decay term exponentially related to the freeze-thaw damage variable and a stress acceleration factor with the deviatoric stress ratio as the independent variable, reflecting the combined weakening effect of freeze-thaw damage and stress level on viscous flow resistance. The long-term strength is calculated by multiplying the initial long-term strength of the unfrozen rock sample by a coefficient linearly reduced by the freeze-thaw damage variable, characterizing the degree to which freeze-thaw damage weakens the long-term bearing capacity of the rock.

[0088] S520. Based on the damage evolution function of creep mechanical parameters, a variable parameter creep damage constitutive model considering the thermal expansion heterogeneity of mineral particles is constructed.

[0089] Specifically, the variable-parameter creep damage constitutive model decomposes the total strain into three components: the first part is the instantaneous elastic strain term, which is directly obtained by dividing the current deviatoric stress by the damage elastic modulus; the second part is the viscoelastic creep strain term, which is described by convolving a creep compliance function in fractional integral form with the stress history. The viscosity coefficient in the creep compliance function is taken from the viscosity coefficient after damage, and the fractional order is determined by fitting experimental data; the third part is the viscoplastic strain term, which is activated only when the deviatoric stress exceeds the long-term strength after damage. Its magnitude is obtained by multiplying the excess deviatoric stress difference by the viscoplastic viscosity coefficient and then by the cumulative time. This variable-parameter creep damage constitutive model embeds the influence of freeze-thaw damage into various creep mechanical parameters, which in turn explicitly depend on the thermal expansion heterogeneity index of mineral particles, the number of freeze-thaw cycles, and the deviatoric stress, thus realizing a cross-scale correlation from microscopic thermophysical properties to macroscopic creep mechanical response.

[0090] S530. The accelerated creep initiation time predicted based on the rate of change of b value in the acoustic signature-creep coupling response relationship is used as the triggering criterion for the viscoplastic strain term in the variable parameter creep damage constitutive model.

[0091] Specifically, within each time step of the numerical calculation, the rate of change of the acoustic emission b-value is continuously monitored. When the rate of change of the b-value is detected to be less than or equal to a preset critical negative threshold for the first time, it is determined that the accelerated creep stage is about to begin. After experiencing a warning lead time determined by a second coupling relationship, the accelerated creep mode in the viscoplastic strain term is activated. In the accelerated creep stage, the viscoplastic strain no longer accumulates linearly over time, but rather its rapid growth is described by an exponential function. The coefficients and exponential factors of the exponential function are calibrated using experimental data from the accelerated creep stage. The introduction of this criterion enables the variable-parameter creep damage constitutive model to dynamically adjust the creep evolution path based on real-time acoustic emission monitoring signals, significantly enhancing its ability to capture precursors of freeze-thaw damaged rock instability.

[0092] In a preferred embodiment of the present invention, the steps of selecting a typical cross-section of a tunnel in a cold region and calculating the creep analysis results of the surrounding rock of the tunnel in a cold region based on the variable parameter creep damage constitutive model specifically include: first, selecting a typical cross-section of a tunnel in a cold region and establishing a numerical calculation model; then, embedding the variable parameter creep damage constitutive model into finite difference numerical software for secondary development; and then, inputting the thermal expansion heterogeneity index of mineral particles and the number of freeze-thaw cycles in the tunnel site to calculate the displacement field, stress field, and plastic yield zone distribution of the surrounding rock of the typical cross-section of the tunnel in a cold region, which are used as the creep analysis results of the surrounding rock of the tunnel in a cold region.

[0093] In practical applications, a representative cross-section of a tunnel in a cold region is selected. Based on tunnel design drawings and geological survey data, a numerical calculation model is established that includes the surrounding rock, lining structure, and anchor support structure. The numerical calculation model needs to be large enough to eliminate boundary effects. The surrounding rock area is discretized using continuous medium elements, the lining is simulated using linear elastic elements, and the anchors are simulated using dedicated structural elements to simulate their axial pull-out and grouting anchoring effects.

[0094] Using the secondary development interface and built-in scripting language provided by the finite difference software, the aforementioned variable-parameter creep damage constitutive model was written as a user-defined constitutive subroutine and embedded into the software kernel. Within each calculation step, this subroutine reads the stress state of the current element, the number of freeze-thaw cycles already experienced, and the user-input thermal expansion heterogeneity index of the mineral particles. Based on this, it updates the element's elastic modulus, viscosity coefficient, and long-term strength values, and determines whether to switch to accelerated creep calculation mode based on the acoustic signature-creep coupling response criterion.

[0095] Two key analytical parameters, the mineral particle thermal expansion heterogeneity index and the number of freeze-thaw cycles in the tunnel, were input into the numerical calculation model, which had already undergone secondary development of the constitutive model. The mineral particle thermal expansion heterogeneity index was calculated based on borehole rock samples obtained from the above method, and the number of freeze-thaw cycles was obtained from local temperature records during the tunnel's operational years. After setting the calculation time step, total simulation duration, and boundary constraints to match the actual engineering project, the numerical solution process was initiated to calculate the stress and deformation evolution of the surrounding rock after tunnel excavation disturbance under long-term freeze-thaw environment and creep.

[0096] After numerical calculation convergence, the displacement field, stress field, and plastic yield zone distribution data of typical cross-sections of tunnels in cold regions are extracted from the calculation results. The displacement field includes key deformation indicators such as crown settlement, horizontal convergence of the arch waist, and invert heave, along with their evolution curves over time. The stress field includes the spatial distribution characteristics of the maximum principal stress, minimum principal stress, and tangential stress, as well as the range of stress release areas. The distribution of the plastic yield zone uses yield proximity or plastic zone indicator variables to show the depth and contour of irreversible deformation of the surrounding rock. These three outputs together constitute the results of the freeze-thaw damage creep analysis of the surrounding rock in tunnels in cold regions, which can be directly used for long-term stability assessment and support scheme optimization design of tunnels.

[0097] like Figure 5 As shown, in another embodiment of the present invention, a system for analyzing the freeze-thaw damage creep of surrounding rock in cold-region tunnels is also provided to implement the above-mentioned method for analyzing the freeze-thaw damage creep of surrounding rock in cold-region tunnels. Specifically, it includes: a heterogeneity index construction module 10, used to construct a thermal expansion heterogeneity index of mineral particles.

[0098] The evolution feature extraction module 20 is used to obtain the non-uniform evolution feature parameters of the rock microstructure under freeze-thaw cycles.

[0099] The mapping relationship establishment module 30 is used to establish a mapping relationship between freeze-thaw damage variables and the thermal expansion heterogeneity index of mineral particles based on the non-uniform evolution characteristic parameters.

[0100] The coupling relationship construction module 40 is used to construct the acoustic signature-creep coupling response relationship based on the graded loading and unloading creep test.

[0101] Constitutive model construction module 50 is used to construct a variable parameter creep damage constitutive model based on the mapping relationship between the freeze-thaw damage variable and the thermal expansion heterogeneity index of mineral particles, as well as the acoustic signature-creep coupling response relationship.

[0102] The analysis result output module 60 is used to select a typical cross-section of a tunnel in a cold region based on the variable parameter creep damage constitutive model, and calculate the creep analysis results of the freeze-thaw damage of the surrounding rock of the tunnel in a cold region.

[0103] It should be noted that each of the above modules can be implemented as a computer program, which can run on a computer device. The computer device's memory can store the computer program that makes up each module, enabling the processor to execute each step of the above method.

[0104] It should be understood that although the steps in the flowcharts of the embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in each embodiment may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0105] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods.

[0106] The above embodiments merely illustrate several implementation methods of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this patent should be determined by the appended claims.

Claims

1. A method for analyzing freeze-thaw damage and creep in the surrounding rock of tunnels in cold regions, characterized in that, Includes the following steps: A mineral particle thermal expansion heterogeneity index is constructed; the mineral particle thermal expansion heterogeneity index is used to quantitatively characterize the level of non-uniform thermal mismatch stress caused by the difference in thermal expansion coefficients between different mineral components inside the rock. To obtain the non-uniform evolution characteristic parameters of rock microstructure under freeze-thaw cycles; Based on the aforementioned non-uniform evolution characteristic parameters, a mapping relationship between freeze-thaw damage variables and the thermal expansion heterogeneity index of mineral particles is established. Based on graded loading and unloading creep tests, a voiceprint-creep coupling response relationship is constructed. Based on the mapping relationship between the freeze-thaw damage variables and the thermal expansion heterogeneity index of mineral particles, and the acoustic signature-creep coupling response relationship, a variable parameter creep damage constitutive model is constructed. Based on the aforementioned variable parameter creep damage constitutive model, a typical cross-section of a tunnel in a cold region was selected, and the results of the freeze-thaw damage creep analysis of the surrounding rock of the tunnel in a cold region were calculated.

2. The method for analyzing freeze-thaw damage and creep in surrounding rock of tunnels in cold regions according to claim 1, characterized in that, The steps for constructing the thermal expansion heterogeneity index of mineral grains specifically include: Representative rock samples of the surrounding rock of tunnels in cold regions were selected; Obtain the volume fraction of each mineral component, the average particle size of minerals, and the coefficient of linear thermal expansion in representative rock samples; A mineral particle thermal expansion heterogeneity index is constructed based on the volume fraction of each mineral component, the average particle size of the mineral particles, and the linear thermal expansion coefficient.

3. The method for analyzing freeze-thaw damage and creep in surrounding rock of tunnels in cold regions according to claim 2, characterized in that, The formula for calculating the thermal expansion heterogeneity index of the mineral particles is as follows: ； In the formula, H is the thermal expansion heterogeneity index of mineral particles; V i V j These are the volume fractions of the i-th and j-th mineral components, respectively; , The linear thermal expansion coefficients of the i-th and j-th mineral components are respectively; d i d j , respectively, are the average particle sizes of the mineral particles of the i-th and j-th mineral components; The particle contact probability factors for the i-th and j-th mineral components are determined by the spatial correlation function method based on backscattered electron images.

4. The method for analyzing freeze-thaw damage and creep in surrounding rock of tunnels in cold regions according to claim 3, characterized in that, The spatial correlation function method based on backscattered electron images includes the following steps: First, after polishing the surface of representative rock samples, high-resolution mineral distribution images were acquired using a scanning electron microscope in backscattered electron mode. Different mineral components exhibit different gray levels due to their varying average atomic numbers. Next, energy dispersive spectroscopy (EDS) was used to calibrate the mineral component categories corresponding to each gray level region, and a mineral phase distribution map was generated using an image segmentation algorithm, assigning a mineral component category label to each pixel. Then, a large number of pixel pairs were randomly selected from the mineral phase distribution map, and the probabilities of two pixels at a distance r belonging to the i-th and j-th mineral components, respectively, were calculated to determine the correlation function between the two points. Extrapolating the correlation function between these two points to the limit value as r→0 is taken as the particle contact probability factor for the i-th and j-th mineral components, i.e. .

5. The method for analyzing freeze-thaw damage and creep in surrounding rock of tunnels in cold regions according to claim 2, characterized in that, The steps for obtaining the non-uniform evolution characteristic parameters of rock microstructure under freeze-thaw cycles specifically include: First, representative rock samples were subjected to multiple freeze-thaw cycles. Three-dimensional CT volumetric data of the representative rock samples were acquired before and after each freeze-thaw cycle. Then, digital volumetric image correlation analysis was performed on the three-dimensional CT volumetric data to extract the non-uniform evolution characteristic parameters of the pore-fracture network inside the rock under different freeze-thaw cycles. The non-uniform evolution characteristic parameters include pore connectivity, fracture fractal dimension, and local strain concentration coefficient.

6. The method for analyzing freeze-thaw damage and creep in surrounding rock of tunnels in cold regions according to claim 5, characterized in that, The pore connectivity is defined as the ratio of the number of voxels with the largest connected clusters in the pore-fracture network to the total number of all pore-fracture voxels after the freeze-thaw cycle test; the fracture fractal dimension is calculated using the box counting method to quantitatively characterize the complexity and filling capacity of the spatial distribution of the pore-fracture network under freeze-thaw cycles; the local strain concentration factor is defined as the ratio of the average equivalent strain of the voxels with the largest pre-set percentage in the three-dimensional strain field after the freeze-thaw cycle test to the average equivalent strain of the entire field.

7. The method for analyzing freeze-thaw damage and creep in surrounding rock of tunnels in cold regions according to claim 5, characterized in that, The step of establishing a mapping relationship between freeze-thaw damage variables and the thermal expansion heterogeneity index of mineral grains based on the aforementioned non-uniform evolution characteristic parameters specifically includes: First, based on the pore connectivity and fracture fractal dimension, the freeze-thaw damage variable after each freeze-thaw cycle test is calculated; then, regression analysis is performed on the freeze-thaw damage variable and the thermal expansion heterogeneity index of mineral particles to establish a mapping relationship between the freeze-thaw damage variable and the thermal expansion heterogeneity index of mineral particles.

8. The method for analyzing freeze-thaw damage and creep in surrounding rock of tunnels in cold regions according to claim 5, characterized in that, The steps for constructing the acoustic signature-creep coupling response relationship based on graded loading and unloading creep tests specifically include: A graded loading and unloading creep test was conducted on representative rock samples after multiple freeze-thaw cycles, and acoustic emission signals were collected simultaneously during the graded loading and unloading creep test. Waveform analysis and parameter extraction are performed on the acoustic emission signal to obtain acoustic signature feature parameters; the acoustic signature feature parameters include acoustic emission count rate, acoustic emission energy rate, b-value, RA-AF value distribution, and peak-frequency-amplitude spectrum characteristics; The creep process of the staged loading and unloading creep test is divided into a decay creep stage, a steady-state creep stage, and an accelerated creep stage, and the creep mechanical parameters of each creep stage are extracted. The creep mechanical parameters include instantaneous elastic strain, viscoelastic strain, viscoplastic strain, steady-state creep rate, and accelerated creep initiation time. The acoustic signature feature parameters and creep mechanical parameters are aligned and correlated in the time domain to construct the acoustic signature-creep coupling response relationship.

9. The method for analyzing freeze-thaw damage and creep in surrounding rock of tunnels in cold regions according to claim 8, characterized in that, Based on the mapping relationship between the freeze-thaw damage variables and the thermal expansion heterogeneity index of mineral particles, and the acoustic signature-creep coupling response relationship, the steps for constructing a variable-parameter creep damage constitutive model specifically include: A damage evolution function for creep mechanical parameters is established, expressing the elastic modulus, viscosity coefficient, and long-term strength as functions of the thermal expansion heterogeneity index of mineral particles, the number of freeze-thaw cycles, and deviatoric stress. Based on the damage evolution function of creep mechanical parameters, a variable parameter creep damage constitutive model considering the thermal expansion heterogeneity of mineral particles is constructed; the variable parameter creep damage constitutive model includes three parts: instantaneous elastic strain term, viscoelastic creep strain term, and viscoplastic strain term; The accelerated creep initiation time, predicted based on the rate of change of b value in the acoustic signature-creep coupling response relationship, is used as the triggering criterion for the viscoplastic strain term in the variable parameter creep damage constitutive model.

10. A system for analyzing the creep of frozen-thaw damage in surrounding rock of tunnels in cold regions, used to implement the method for analyzing the creep of frozen-thaw damage in surrounding rock of tunnels in cold regions as described in any one of claims 1-9, characterized in that, include: The heterogeneity index construction module is used to construct the thermal expansion heterogeneity index of mineral particles; The evolution feature extraction module is used to obtain the non-uniform evolution feature parameters of rock microstructure under freeze-thaw cycles; The mapping relationship establishment module is used to establish a mapping relationship between freeze-thaw damage variables and the thermal expansion heterogeneity index of mineral particles based on the non-uniform evolution characteristic parameters. The coupling relationship construction module is used to construct the acoustic signature-creep coupling response relationship based on the graded loading and unloading creep test; The constitutive model construction module is used to construct a variable parameter creep damage constitutive model based on the mapping relationship between the freeze-thaw damage variables and the thermal expansion heterogeneity index of mineral particles, as well as the acoustic signature-creep coupling response relationship. The analysis results output module is used to select typical cross-sections of tunnels in cold regions based on the variable parameter creep damage constitutive model, and calculate the creep analysis results of the surrounding rock freeze-thaw damage of tunnels in cold regions.

Images