Method for testing rheological mechanical properties of soft rock based on vibration-seepage pressure coupling

Abstract

This invention discloses a method for testing the rheological mechanical properties of soft rock based on vibration-seepage pressure coupling. The method includes: selecting and processing soft rock samples; constructing a testing system containing modules for vibration loading, seepage pressure application, and data acquisition; applying seepage pressure to the soft rock samples and acquiring pore water pressure data; after stabilization, applying periodic vibration loads and simultaneously acquiring strain and stress data; importing the data into the ZSoil three-dimensional finite element analysis platform; using the strain softening-aging viscoelastic-plastic algorithm to establish a mechanical response analysis model; and then introducing a fluid-structure-thermal coupling fractional-order rheological model and a vibration-seepage pressure dynamic fully coupled model to simulate long-term rheological properties. This method, through multi-model collaboration and an integrated testing process, solves the problems of insufficient model coupling, coarse characteristic characterization, and low efficiency, accurately obtaining soft rock rheological parameters, and providing reliable support for the design optimization and safety assurance of water conservancy, hydropower, and mining projects.

Description

Technical Field

[0001] This invention relates to the field of soft rock rheological testing technology, and in particular to a method for testing the rheological properties of soft rock based on vibration-seepage pressure coupling. Background Technology

[0002] In engineering activities such as water conservancy and hydropower, mining, and transportation tunnels, soft rock is a common engineering medium. During its long-term service, it often faces the coupled effects of vibration loads and seepage pressure, such as blasting vibrations in mining and groundwater seepage during tunnel construction. These effects can cause rheological deformation in soft rock, leading to structural instability, support failure, and other problems, seriously threatening the safety and service life of the project. Therefore, accurately obtaining the rheological mechanical properties of soft rock under vibration-seepage pressure coupling conditions is crucial for guiding engineering design optimization, risk assessment, and stability control. Current engineering practice has an increasingly urgent need for testing the rheological properties of soft rock. A testing method is needed that can realistically simulate complex service environments and accurately capture mechanical response patterns to address the problem that traditional tests cannot reflect the long-term rheological behavior of soft rock under multi-field coupling effects, providing reliable mechanical parameter support for engineering construction.

[0003] Existing technologies for testing the rheological mechanical properties of soft rock have two significant drawbacks: First, the models used in existing testing methods are mostly limited to a single physical field or simple coupling, failing to fully consider the dynamic full coupling relationship between vibration, seepage, and soft rock rheology. This makes it impossible to accurately characterize the influence of the interaction of various factors on the rheological properties of soft rock, resulting in a large deviation between the test results and the mechanical behavior of soft rock in actual engineering, making it difficult to meet the requirements of engineering design for accurate parameters. Second, in the data processing and simulation analysis stages, existing tests lack a deep integration of field test data with advanced numerical analysis platforms and complex algorithms. The characterization of key properties such as strain softening and aging viscoelastic-plastic properties of soft rock is not detailed enough, and the coordination between the modules of the testing system is insufficient, making it impossible to achieve an integrated process from parameter application and data acquisition to simulation analysis, thus reducing testing efficiency and the reliability of results. Summary of the Invention

[0004] In order to overcome the shortcomings and deficiencies of the existing technology, this invention provides a method for testing the rheological mechanical properties of soft rock based on vibration-seepage pressure coupling.

[0005] The technical solution adopted in this invention is a method for testing the rheological mechanical properties of soft rock based on vibration-seepage pressure coupling, comprising the following steps: S1, selecting a soft rock sample, obtaining a soft rock sample that meets the test size requirements through a special sampling device, smoothing the surface of the soft rock sample, and obtaining the initial physical parameters of the soft rock sample using a high-precision measuring instrument; S2, constructing a test system including a vibration loading module, a seepage pressure application module, and a data acquisition module, fixing the processed soft rock sample in the sample clamping device of the test system, ensuring close contact between the soft rock sample and the vibration loading module and the seepage pressure application module; S3, activating the seepage pressure application module, applying seepage pressure to the interior of the soft rock sample according to a preset seepage pressure gradient, and simultaneously activating the data acquisition module to collect the pore water pressure distribution data of the soft rock sample under different seepage pressures in real time. According to the following steps: S4. After the seepage pressure stabilizes, the vibration loading module is activated, and periodic vibration loads are applied to the soft rock sample according to the set vibration frequency and amplitude parameters. The data acquisition module simultaneously collects the strain and stress change data of the soft rock sample under the coupled action of vibration and seepage pressure. S5. The collected strain, stress, and pore water pressure data are imported into the ZSoil three-dimensional finite element analysis platform. The strain softening aging viscoelastic-plastic algorithm is called to perform preliminary data processing and establish a mechanical response analysis model for the soft rock sample. S6. Based on the mechanical response analysis model, a fluid-solid-thermal coupling fractional-order rheological model and a vibration-seepage pressure dynamic full coupling model are introduced respectively. The long-term rheological mechanical properties of the soft rock sample under the coupled action of vibration and seepage pressure are simulated and analyzed through the ZSoil three-dimensional finite element analysis platform to obtain the rheological mechanical property parameters of the soft rock sample.

[0006] Furthermore, the expression for the fluid-structure-thermal coupling fractional-order rheological model is as follows: ,in, For the stress of the soft rock sample, For the strain of the soft rock sample, For time, For integration variables, The order of the fractional derivative For viscoelastic parameters, For soft rock elastic modulus, The viscosity coefficient of soft rock. The viscoelastic coupling coefficient is... Thermo-mechanical coupling coefficient, The seepage-mechanical coupling coefficient is... Temperature of the soft rock sample. This refers to the pore water pressure.

[0007] Furthermore, the expression for the vibration-seepage pressure dynamic fully coupled model is as follows: ,in, For soft rock permeability, Porosity of soft rock (varying with pore water pressure) and strain change), The density of pore water, The pore water seepage velocity, The frequency of vibration. It represents the vibration phase angle.

[0008] Furthermore, the expression for the strain-softening aging viscoelastic-plastic algorithm is as follows:

[0009]

[0010]

[0011]

[0012]

[0013] in, For total strain, For elastic strain, For viscoelastic strain, For plastic strain, For the elastic stage, the elastic modulus. Poisson's ratio, The symbol for Kronecker. For stress tensor, This refers to the elastic modulus in the viscoelastic stage. The viscosity coefficient is the viscosity coefficient in the viscoelastic stage. For timeliness parameters, For relaxation time, For yield stress, For the enhancement coefficient, This is the softening coefficient over time. For reference only.

[0014] Furthermore, when simulating the rheological mechanical properties of soft rock in the ZSoil three-dimensional finite element analysis platform, the expression of the mesh generation control model is as follows: ,in, The finite element mesh size is... For the basic size factor of the grid, The stress influence coefficient is... The strain rate influence coefficient is... For maximum stress, For the maximum strain rate, The coefficient representing the influence of seepage pressure is denoted as . For reference pore water pressure, This is the vibration influence coefficient.

[0015] Furthermore, the model expression for modifying the rheological mechanical property parameters of soft rock is as follows: ,in, These are the corrected rheological and mechanical property parameters for soft rock. These are the initial rheological properties parameters. This is the stress cumulative effect coefficient. The cumulative influence coefficient of seepage-vibration coupling. This is the fractional strain rate influence coefficient.

[0016] Further, S3 specifically includes the following sub-steps: S31, connecting the pressure output end of the seepage pressure application module to the pore channels of the soft rock sample, and adjusting the opening state of the seepage path through the valve control device to ensure that the seepage pressure can be uniformly transmitted to the interior of the soft rock sample; S32, setting the initial value, termination value, and pressure gradient of the seepage pressure application, and starting the pressure control unit to gradually increase the seepage pressure according to the set gradient, avoiding pressure sudden changes that could damage the soft rock sample structure; S33, during the seepage pressure increase process, the data acquisition module collects pressure data through pore water pressure sensors arranged at different locations on the soft rock sample, and the acquisition interval is adjusted according to the pressure change rate; S34, performing preliminary screening on the collected pore water pressure data to remove obviously abnormal data points, providing accurate basic data for subsequent model analysis.

[0017] Further, S4 specifically includes the following sub-steps: S41, preset the frequency range and amplitude range of vibration loading according to the mechanical properties of the soft rock sample, input the vibration parameters into the control unit of the vibration loading module, and ensure that the output of the vibration load meets the test requirements; S42, after the seepage pressure stabilizes at the set value, start the vibration loading module so that the vibration load acts on the soft rock sample in the form of a sine wave, and record the start time of vibration loading at the same time; S43, the data acquisition module collects the strain and stress data of the soft rock sample under the vibration load in real time through strain sensors and stress sensors, and the acquisition frequency is higher than 5 times the vibration frequency to ensure the integrity of the data; S44, during the vibration loading process, monitor the appearance of the soft rock sample in real time. If obvious cracks or damage are found in the sample, stop the vibration loading immediately and record the test parameters at this time.

[0018] Further, S5 specifically includes the following sub-steps: S51, organizing the strain, stress, and pore water pressure data stored in the data acquisition module according to the time series and converting them into a data format recognizable by the ZSoil 3D finite element analysis platform; S52, establishing a geometric model consistent with the actual size of the soft rock sample in the ZSoil 3D finite element analysis platform, and setting the material properties of the model according to the initial physical parameters of the soft rock sample; S53, calling the strain softening aging viscoelastic-plastic algorithm, importing the organized test data into the model, setting the boundary conditions of the model, and simulating the constraint state during the test process; S54, running the finite element analysis to obtain the mechanical response distribution cloud map of the soft rock sample at different test stages, providing an analytical basis for the subsequent introduction of the coupled model.

[0019] A method for testing the rheological mechanical properties of soft rock based on vibration-seepage pressure coupling is implemented through different units, including: a soft rock sample pretreatment and fixation unit, a multi-parameter loading control unit, a high-precision data acquisition unit, a ZSoil finite element analysis and simulation unit, a coupled model calculation unit, and a test result output and storage unit. The soft rock sample pretreatment and fixation unit is connected to the multi-parameter loading control unit to process and fix the soft rock sample, and then transfers the processed sample to the multi-parameter loading control unit. The multi-parameter loading control unit is connected to both the soft rock sample pretreatment and fixation unit and the high-precision data acquisition unit, and applies seepage pressure and vibration load to the soft rock sample, transferring the loading parameters to the high-precision data acquisition unit. The high-precision data acquisition unit is connected to both the multi-parameter loading control unit and the ZSoil finite element analysis and simulation unit, and is used to collect data on the soft rock sample's rheological properties. The mechanical and seepage data of the rock sample are transmitted to the ZSoil finite element analysis and simulation unit. The ZSoil finite element analysis and simulation unit is connected to the high-precision data acquisition unit and the coupled model calculation unit, respectively, for preliminary processing and finite element simulation of the acquired data, and the processing results are transmitted to the coupled model calculation unit. The coupled model calculation unit is connected to the ZSoil finite element analysis and simulation unit and the test result output and storage unit, respectively, for calling the fluid-solid-thermal coupling fractional-order rheological model, the vibration-seepage-pressure dynamic fully coupled model, and the strain softening aging viscoelastic-plastic algorithm to perform coupled analysis on the simulation results, and the analysis results are transmitted to the test result output and storage unit. The test result output and storage unit is connected to the coupled model calculation unit for storing the soft rock rheological mechanical property parameters obtained from the coupled analysis and outputting the test report in a specified format.

[0020] Beneficial effects: This invention proposes a test method for the rheological mechanical properties of soft rock based on vibration-seepage pressure coupling. By building an integrated test system including vibration loading, seepage pressure application and data acquisition, and combining a multi-field coupling model with an advanced numerical analysis platform, it not only solves the problem of insufficient coupling of existing technology models, but also achieves efficient coordination of the test process. In terms of model application, a fractional-order rheological model coupled with fluid-structure-thermal coupling and a dynamic fully coupled model of vibration-seepage-pressure are introduced to fully characterize the dynamic interaction between vibration, seepage, and soft rock rheology. This accurately reflects the mechanical behavior of soft rock under multi-field coupling in actual engineering, significantly reducing the deviation between test results and actual conditions, and meeting the requirements of engineering design for accurate parameters. At the same time, by using the strain softening aging viscoelastic-plastic algorithm and the ZSoil three-dimensional finite element analysis platform, the strain, stress, and pore water pressure data collected on-site are deeply combined with numerical simulation to meticulously characterize key properties such as strain softening and aging viscoelastic-plastic properties of soft rock. Furthermore, by optimizing the testing and analysis process step by step, the integration of parameter application, data acquisition, and simulation analysis is achieved, improving testing efficiency and result reliability. This provides more reliable mechanical parameter support for structural design optimization, risk assessment, and stability control in water conservancy, hydropower, and mining projects, effectively ensuring project safety and service life. Attached Figure Description

[0021] Figure 1 This is a flowchart of the method steps of the present invention;

[0022] Figure 2 This is a diagram showing the unit composition for implementing the method of the present invention. Detailed Implementation

[0023] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0024] like Figure 1 As shown, the method for testing the rheological mechanical properties of soft rock based on vibration-seepage pressure coupling includes the following steps:

[0025] S1. Select soft rock samples, obtain soft rock samples that meet the test size requirements through a special sampling device, perform flatness treatment on the surface of the soft rock samples, and use high-precision measuring instruments to obtain the initial physical parameters of the soft rock samples.

[0026] Specifically, step S1 involves selecting, processing, and measuring the initial parameters of soft rock samples. First, soft rock samples are obtained from the area to be studied at the engineering site. A standard sampler with a diameter of 50-100 mm and a height of 100-200 mm is used to ensure the sample axis is perpendicular to the original structural surface of the rock strata, preventing additional stress from the sampling process from damaging the sample structure. After sampling, the two ends of the sample are treated with a grinding wheel to control the flatness error of the end face to ≤0.05 mm. Loose debris and crack fillers are removed from the surface to ensure the sample is free of obvious defects. Next, high-precision instruments are used to measure the initial physical parameters: an electronic balance (accuracy 0.01 g) measures the mass; a vernier caliper (accuracy 0.02 mm) measures the diameter and height to calculate the volume and density; an acoustic wave detector (detection frequency 20-50 kHz) measures the longitudinal wave velocity to determine internal integrity; and a porosity meter (test pressure 0.1-0.3 MPa) measures the porosity. This step, by strictly controlling the sample size and flatness, avoids the impact of geometric errors on subsequent loading and data acquisition. The initial parameters obtained provide basic data for test system construction, model parameter setting, and result analysis, ensuring the accuracy and repeatability of the test.

[0027] S2. Construct a test system including a vibration loading module, a seepage pressure application module, and a data acquisition module. Fix the treated soft rock sample in the sample clamping device of the test system to ensure that the soft rock sample is in close contact with the vibration loading module and the seepage pressure application module.

[0028] Specifically, in step S2, the test system is built and the soft rock sample is fixed. The vibration loading module uses an electromagnetic vibration table with a vibration frequency adjustment range of 0.1-50 Hz, an amplitude adjustment range of 0.01-5 mm, and a maximum excitation force ≥5 kN. A rigid loading head matching the sample diameter is installed at the output end, and the surface of the loading head is chrome-plated to reduce friction loss. The seepage pressure application module uses a high-pressure constant pressure pump with a pressure adjustment range of 0-10 MPa and a stability accuracy of ±0.01 MPa. The outlet is connected to the seepage channel of the sample clamping device through a high-pressure hose with a pressure resistance rating ≥15 MPa. The data acquisition module uses a multi-channel data acquisition instrument with a sampling frequency of 1-1000 Hz, an analog input accuracy of 0.1% of full scale, and is equipped with a pore water pressure sensor (measurement range 0-10 MPa, accuracy 0.2%FS), a resistance strain gauge (sensitivity coefficient 2.0±0.1), and a stress sensor (measurement range 0-20 MPa, accuracy 0.1%FS). When fixing the sample, the processed sample is placed in a cylindrical clamping device with a 2-5 mm thick rubber sealing gasket on the inner wall. The clamping force is adjusted by bolts to ensure that the sample fits tightly against the inner wall of the device. At the same time, it ensures that the vibration loading head is in close contact with the upper surface of the sample and the seepage channel is in close contact with the side pores of the sample, without leakage or loosening. This provides equipment and structural support for subsequent accurate loading and stable data acquisition.

[0029] S3. Start the seepage pressure application module to apply seepage pressure to the interior of the soft rock sample according to the preset seepage pressure gradient. At the same time, start the data acquisition module to collect the pore water pressure distribution data of the soft rock sample under different seepage pressures in real time.

[0030] Specifically, step S3 is responsible for applying seepage pressure and collecting pore water pressure data. During implementation, the outlet valve of the seepage pressure application module is first closed, and the pressure of the high-pressure constant-pressure pump is set to an initial value of 0.5 MPa. After the pump pressure stabilizes, the valve is slowly opened, allowing the seepage pressure to be transmitted to the seepage channel of the sample clamping device at a rate of 0.1 MPa / min, avoiding a sudden pressure increase that could damage the internal pore structure of the sample. The seepage pressure gradient is set to 0.5 MPa / level, and each pressure level is maintained for 30-60 minutes until the fluctuation range of the pore water pressure sensor data is <0.02 MPa, indicating that the seepage pressure is stable. During data acquisition, the pore water pressure sensor is installed at different heights on the sample clamping device via a threaded interface, with 3-5 measurement points (located at 1 / 4, 1 / 2, 3 / 4 of the sample height and near both end faces, respectively). The sampling frequency of the data acquisition instrument is set to 1 Hz, and 300-600 sets of data are continuously collected during each pressure stabilization stage, automatically stored to the computer terminal (Excel format, including acquisition time, sensor number, and pressure value). During the process, the sealing of the device should be monitored in real time. If leakage is found, the valve should be closed immediately and the sealing gasket adjusted or replaced. If the data fluctuates abnormally, the sensor circuit should be checked to ensure continuous and accurate data acquisition, so as to provide direct data for analyzing the impact of seepage on the rheological properties of soft rock.

[0031] S4. After the seepage pressure stabilizes, start the vibration loading module and apply periodic vibration load to the soft rock sample according to the set vibration frequency and amplitude parameters. The data acquisition module simultaneously collects the strain and stress change data of the soft rock sample under the vibration-seepage pressure coupling action.

[0032] Specifically, in step S4, a vibration load is applied and strain and stress data are collected simultaneously. After the seepage pressure stabilizes at 2-5 MPa (set according to project requirements), the vibration loading module is activated. The vibration frequency is set to 5-20 Hz according to common engineering vibration sources, the amplitude is 0.1-1 mm, and the waveform is selected as a sine wave to conform to the actual engineering vibration characteristics. The vibration loading lasts for 60-120 minutes. During this period, the pressure is monitored and adjusted in real time through the high-pressure constant pressure pump pressure feedback system to ensure that the fluctuation is ≤±0.01 MPa. During data acquisition, strain gauges are pasted to the side of the sample with special adhesive. 3-4 measuring points are evenly set along the circumference. Two gauges are pasted along the axial direction at each measuring point to measure axial and circumferential strain. Before pasting, the sample surface is polished, cleaned, and degreased to ensure firm adhesion. The strain data is converted into electrical signals and stored by the data acquisition instrument. The stress sensor is installed between the vibration loading head and the upper end face of the sample to directly measure the axial stress. Stress and strain data are collected simultaneously at a sampling frequency of 50-100 Hz (5-10 times the vibration frequency) to ensure complete capture of stress and strain changes in each vibration cycle. During the process, a high-definition camera (1920×1080 pixels resolution, 25 frames / second) was used to observe the appearance of the sample in real time. If new cracks or crack propagation occurred, relevant parameters were recorded. If the sample broke, loading was stopped immediately and the data was saved to provide support for analyzing the dynamic rheological properties of soft rock and determining the critical failure conditions.

[0033] S5. Import the collected strain, stress, and pore water pressure data into the ZSoil three-dimensional finite element analysis platform, call the strain softening aging viscoelastic-plastic algorithm to perform preliminary data processing, and establish a mechanical response analysis model for soft rock samples.

[0034] Specifically, in step S5, data is imported and a mechanical response analysis model is established. First, the collected strain, stress, and pore water pressure data are preprocessed. Abnormal data that deviates from the average value by more than three times the standard deviation is deleted using data processing software. Missing data is supplemented using linear interpolation to ensure completeness. Then, the preprocessed data is organized according to the time series and converted into a text format supported by the ZSoil 3D finite element analysis platform, containing parameters such as time, stress value, axial strain value, circumferential strain value, and pore water pressure value at each measuring point. Each parameter corresponds to a unique data column for easy identification by the platform. When establishing the geometric model in ZSoil, create a three-dimensional cylindrical model according to the actual dimensions of the sample (diameter 50-100 mm, height 100-200 mm). Use tetrahedral elements for meshing, with an element size of 5-10 mm. Refine the mesh to 2-3 mm near the sample surface and loading surface to ensure calculation accuracy. When setting material properties, input the initial parameters such as density, porosity, and P-wave velocity obtained in step S1. Set the initial elastic modulus (1-5 GPa) and Poisson's ratio (0.25-0.45) according to the soft rock type (e.g., mudstone, shale). When calling the strain softening aging viscoelastic-plastic algorithm, select the corresponding module from the platform's material constitutive model library, input the initial values ​​of viscosity coefficient, aging parameters, yield stress, etc. (set according to similar experimental data), and set the boundary conditions: fixed constraint on the lower end face (limiting axial and radial displacement), free loading on the upper end face (matching the displacement of the vibration loading head), and seepage boundary on the side (set according to the stable pore water pressure value in step S3). When running finite element analysis, the step size is 0.1-1 seconds, and the total time is consistent with the actual test (60-120 minutes). Convergence is monitored in real time. If convergence is not achieved, the mesh or parameters are adjusted. Finally, stress, strain, and pore water pressure cloud maps at different time points are output, laying the foundation for subsequent coupled model simulation.

[0035] S6. Based on the mechanical response analysis model, a fractional-order rheological model of fluid-structure-thermal coupling and a dynamic fully coupled model of vibration-seepage pressure are introduced respectively. The long-term rheological mechanical properties of soft rock samples under the coupled action of vibration-seepage pressure are simulated and analyzed through the ZSoil three-dimensional finite element analysis platform to obtain the rheological mechanical property parameters of soft rock samples.

[0036] Specifically, step S6 introduces a coupled model and simulates long-term rheological characteristics. Based on the mechanical response analysis model in step S5, a fluid-structure-thermal coupling fractional-order rheological model is added to the constitutive model module of the ZSoil platform. The parameters (fractional derivative order, viscoelastic parameters, thermo-mechanical coupling coefficient, and seepage-mechanical coupling coefficient) are determined according to the physical and mechanical data collected in steps S1-S4 and previous empirical values, and are input according to the platform format to ensure compatibility. Then, a vibration-seepage pressure dynamic fully coupled model is added. Vibration parameters (frequency, amplitude) and seepage parameters (pressure value, permeability coefficient) are associated through the platform's multi-field coupling interface to realize the simulation of the synergistic effect of multiple fields and vibration loads. When simulating long-term rheology, the time frame is set to 1000-10000 hours, with the step size adjusted in stages: 1 hour for short-term (0-100 hours) and 10-100 hours for long-term (100-10000 hours), balancing efficiency and accuracy. During the simulation, the platform automatically calls the strain-softening-aging viscoelastic-plastic algorithm to calculate and store strain, stress, pore water pressure, and displacement data at different time points in real time, outputting rheological curves (strain-time, stress-strain) and long-term stability results. In post-simulation processing, long-term rheological parameters (long-term strength, creep modulus, viscosity coefficient, and rheological failure time) are extracted and compared with the short-term data from step S4 to verify accuracy. If the error is greater than 5%, the permeability coefficient, viscoelastic parameters, etc., are corrected, and the simulation is repeated. Finally, a PDF analysis report containing simulation parameters, rheological curves, and parameter comparison results is generated, providing reliable parameters for long-term stability design and life assessment of engineering projects.

[0037] Preferably, the expression for the fluid-structure-thermal coupling fractional-order rheological model is: ,in, For the stress of the soft rock sample, For the strain of the soft rock sample, For time, For integration variables, The order of the fractional derivative For viscoelastic parameters, For soft rock elastic modulus, The viscosity coefficient of soft rock. The viscoelastic coupling coefficient is... Thermo-mechanical coupling coefficient, The seepage-mechanical coupling coefficient is... Temperature of the soft rock sample. This refers to the pore water pressure.

[0038] Specifically, the fluid-structure-thermal coupling fractional-order rheological model is used to accurately characterize the rheological response of soft rock under the combined effects of temperature, seepage, and mechanical forces. When implementing this model, the value ranges of key parameters must first be determined: the fractional derivative order is set to 0.1-0.9 based on the type of soft rock (e.g., mudstone, shale); the viscoelastic parameter is set to 0.2-0.8; the elastic modulus is set to 1-5 GPa based on the initial physical parameter test results of the soft rock; and the viscosity coefficient is set to 1×10⁻⁶ based on rheological test data of similar soft rocks. 9 -1×10 11 The viscoelastic coupling coefficient, calibrated to 0.5-2.5 through preliminary experiments, and the thermo-mechanical coupling coefficient, set to 1×10⁻⁶ based on the engineering environment temperature range (-10-60℃), are also considered. -5 -5×10 -4 The seepage-mechanical coupling coefficient is adjusted to 0.1-0.8 based on the porosity of soft rock (5%-25%). When applying the model, the initial soft rock temperature value obtained in step S1 (consistent with the ambient temperature, typically 20-25℃) and the pore water pressure data collected in step S3 are first substituted into the model. Then, the aforementioned coefficients are entered one by one through the parameter input interface of the ZSoil 3D finite element analysis platform to ensure that the model matches the actual physical and mechanical properties of the soft rock. This model breaks through the limitations of traditional single mechanical models, simultaneously considering the influence of temperature changes on the viscoelasticity of soft rock and the effect of seepage pressure on the pore structure. It accurately describes the memory and non-integer order characteristics of soft rock rheology through fractional derivatives, making the simulation results more consistent with the complex environment of soft rock in long-term service in engineering. This provides more realistic constitutive relation support for subsequent long-term rheological characteristic analysis, avoiding parameter calculation deviations caused by neglecting thermal and fluid coupling effects.

[0039] Preferably, the expression for the vibration-seepage pressure dynamic fully coupled model is: ,in, For soft rock permeability, Porosity of soft rock (varying with pore water pressure) and strain change), The density of pore water, The pore water seepage velocity, The frequency of vibration. It represents the vibration phase angle.

[0040] Specifically, the vibration-seepage pressure dynamic fully coupled model is used to capture the flow law of pore water inside soft rock under the interaction of vibration load and seepage pressure. During implementation, the dynamic values ​​of the model parameters need to be determined first: permeability varies with pore water pressure (0-10 MPa) and strain (0-0.05). When the pore water pressure increases, the permeability value ranges from 1×10⁻⁶. -15 -1×10 -13Permeability can increase to 1×10⁻⁶ square meters when strain increases. -14 -5×10 -13 The porosity varies with pore water pressure and strain. The initial porosity is 5%-25%, decreasing by 0.5%-2% for every 1 MPa increase in pore water pressure and increasing by 1%-3% for every 0.01 MPa increase in strain. The pore water density is taken as a constant of 1000 kg / m³. The pore water seepage velocity is calculated as 1 × 10⁻¹⁰ m³ based on the seepage pressure gradient (0.1-1 MPa / m). -7 -1×10 -5 The vibration frequency is measured in meters per second (m / s); the vibration angular frequency is converted to 31.4-125.6 radians per second based on the vibration frequency (5-20 Hz) set in step S4, and the vibration phase angle is set to 0-π to cover different initial vibration states. When applying the model, real-time changing pore water pressure and strain values ​​are extracted from the vibration parameters collected in step S4 and the seepage data collected in step S3. The permeability and porosity parameters are dynamically adjusted, and the real-time interactive calculation of vibration load and seepage field is achieved through the multi-field coupling calculation module of the ZSoil platform. This model solves the problem of independent calculation of vibration and seepage in traditional models, accurately reflecting the impact of vibration-induced changes in the pore structure of soft rock on seepage, as well as the reaction effect of seepage pressure changes on the vibration response of soft rock. It provides accurate model support for analyzing the evolution of the internal hydraulic state of soft rock under coupled action, ensuring the dynamic accuracy of hydraulic parameters in subsequent rheological characteristic simulations.

[0041] Preferably, the expression for the strain softening aging viscoelastic-plastic algorithm is:

[0042]

[0043]

[0044]

[0045]

[0046] in, For total strain, For elastic strain, For viscoelastic strain, For plastic strain, For the elastic stage, the elastic modulus. Poisson's ratio, The symbol for Kronecker. For stress tensor, This refers to the elastic modulus in the viscoelastic stage. The viscosity coefficient is the viscosity coefficient in the viscoelastic stage. For timeliness parameters, For relaxation time, For yield stress, For the enhancement coefficient, This is the softening coefficient over time. For reference only.

[0047] Specifically, the strain-softening aging viscoelastic-plastic algorithm is used to analyze the superposition effect of elastic, viscoelastic, and plastic deformation of soft rock under load. During implementation, parameters need to be determined in stages: in the elastic stage, the elastic modulus is set to 1-5 GPa based on the acoustic detection results in step S1, and the Poisson's ratio is set to 0.25-0.45; in the viscoelastic stage, the elastic modulus is 10%-30% lower than that in the elastic stage, ranging from 0.7-4.5 GPa, and the viscosity coefficient is set to 5 × 10⁻⁶. 8 -5×10 10 Pa·second, aging parameters are set to 0.3-0.9 to reflect the effect of time on viscoelasticity, and relaxation time is set to 1×10 based on the creep characteristics of soft rock. 3 -1×10 5 The yield stress in the plastic stage is referenced in step S4. Short-term strength test results are set at 0.5-3 MPa, and the hardening factor is set at 10-50 MPa to describe the strength change after plastic deformation. The aging softening factor is set at 0.01-0.1, indicating that the plastic deformation capacity gradually increases over time; the reference time is set to 1 × 10⁻⁶ seconds. 3 The second is used as the time-dependent calculation benchmark. When applying the algorithm, the corresponding constitutive module is called in the ZSoil platform. The stress and strain data preprocessed in step S5 are input as a time series. The algorithm automatically identifies the deformation stage: when the stress is less than the yield stress, elastic and viscoelastic deformation predominates; when the stress exceeds the yield stress, plastic deformation calculation is initiated, and a time-dependent factor is introduced, increasing over time to adjust the softening coefficient, thus achieving simultaneous calculation of strain softening and time-dependent effects. This algorithm comprehensively characterizes the multi-stage characteristics of soft rock deformation, avoiding the limitations of traditional algorithms that only consider a single deformation type. It accurately reflects the entire process of soft rock under long-term loads, from elastic to plastic and from hardening to softening, providing precise deformation calculation logic for subsequent mechanical response model establishment and ensuring a high degree of consistency between simulation results and the actual mechanical behavior of soft rock.

[0048] Preferably, when simulating the rheological mechanical properties of soft rock in the ZSoil three-dimensional finite element analysis platform, the expression of the mesh generation control model is as follows: ,in, The finite element mesh size is... For the basic size factor of the grid, The stress influence coefficient is... The strain rate influence coefficient is... For maximum stress, For the maximum strain rate, The coefficient representing the influence of seepage pressure is denoted as . For reference pore water pressure, This is the vibration influence coefficient.

[0049] Specifically, the mesh generation control model of the ZSoil platform is used to optimize the mesh size for finite element calculations, balancing computational accuracy and efficiency. During implementation, parameters need to be dynamically adjusted based on soft rock mechanical parameters: the mesh foundation size factor is set to 5-10 mm based on the sample size (diameter 50-100 mm, height 100-200 mm); the stress influence factor is set to 0.01-0.05 based on the maximum stress in step S4 (0.5-3 MPa), with a larger coefficient and smaller mesh size for higher maximum stress; the strain rate influence factor is set based on the maximum strain rate in step S4 (1×10⁻⁶). -5 -1×10 -3 Second -1 The coefficient is set to 0.02-0.1, with higher strain rates resulting in larger coefficients and more pronounced mesh refinement. The reference pore water pressure is the stable seepage pressure (2-5 MPa) from step S3. The vibration influence coefficient is set to 0.1-0.5 based on the vibration frequency (5-20 Hz) from step S4, with higher frequencies resulting in larger coefficients to accommodate high-frequency changes in vibration loads. During model application, real-time maximum stress, maximum strain rate, pore water pressure, and vibration parameters are extracted from the data collected in steps S3-S4 and substituted into the mesh generation control model. The ZSoil platform automatically calculates the mesh size for different regions: the mesh size on the sample surface and in stress concentration areas (such as the loading surface and areas with drastic changes in pore water pressure) is reduced to 2-3 mm, while the mesh size in areas with uniform internal stress remains at 5-10 mm. Simultaneously, the mesh density is finely adjusted in real-time according to changes in vibration load. This model addresses the issues of insufficient computational accuracy or low efficiency caused by traditional fixed mesh sizes. By dynamically adjusting the mesh, it achieves accurate calculations in regions where key parameters such as stress, strain, seepage, and vibration change drastically, while ensuring computational efficiency in other regions. This ensures that the entire finite element analysis process is both accurate and efficient, providing a reasonable mesh foundation for subsequent coupled model calculations.

[0050] The preferred model expression for modifying the rheological mechanical properties of soft rock is as follows: ,in, These are the corrected rheological and mechanical property parameters for soft rock. These are the initial rheological properties parameters. This is the stress cumulative effect coefficient. The cumulative influence coefficient of seepage-vibration coupling. This is the fractional strain rate influence coefficient.

[0051] Specifically, the soft rock rheological mechanical property parameter correction model is used to calibrate the deviation between simulated parameters and actual test data. During implementation, the values ​​of the correction parameters need to be determined: initial rheological mechanical property parameters (such as long-term strength and creep modulus) are extracted from the mechanical response model in step S5, with initial values ​​for long-term strength of 0.3-2.5 MPa and creep modulus of 0.5-4 GPa; the stress accumulation influence coefficient is set to 1×10 based on the stress loading history in step S4. -4 -5×10 -4 The longer the stress accumulation time, the more significant the effect of the coefficient; the cumulative influence coefficient of seepage-vibration coupling is set to 5×10 based on the seepage pressure (2-5 MPa) and vibration frequency (5-20 Hz) in steps S3-S4. -5 -2×10 -4 The influence of the coefficient increases by 1%-5% for every hour increase in coupling time; the influence coefficient of fractional strain rate is set to 0.05-0.3, with higher fractional derivatives resulting in larger coefficients and stronger parameter correction. When applying the model, the cumulative stress and coupling values ​​are calculated from the stress-time data and seepage pressure-vibration coupling time data collected in step S4. The fractional strain rate is extracted from the preliminary simulation results in step S6 and substituted into the correction model to adjust the initial rheological parameters: when the cumulative stress increases, the long-term strength decreases by 5%-20% after correction, and the creep modulus decreases by 3%-15% after correction; when the cumulative coupling value increases, the long-term strength further decreases by 2%-10%; when the fractional strain rate increases, the rheological parameter correction range expands by 1%-5%. This model compensates for the deviations caused by neglecting the cumulative effect in the initial model parameters. By introducing the cumulative effects of stress, coupling, and fractional strain rate, the corrected rheological parameters are made to better fit the actual characteristics of soft rock in long-term service. This ensures that the final output rheological parameters (such as long-term strength and creep modulus) have engineering application value and avoids engineering design deviations caused by inaccurate parameters.

[0052] Preferably, step S3 specifically includes the following sub-steps: S31, connecting the pressure output end of the seepage pressure application module to the pore channel of the soft rock sample, and adjusting the opening state of the seepage path through the valve control device to ensure that the seepage pressure can be uniformly transmitted to the interior of the soft rock sample; S32, setting the initial value, termination value, and pressure gradient of the seepage pressure application, and starting the pressure control unit to gradually increase the seepage pressure according to the set gradient, avoiding pressure sudden changes that could damage the soft rock sample structure; S33, during the increase of the seepage pressure, the data acquisition module collects pressure data through pore water pressure sensors arranged at different locations on the soft rock sample, and the acquisition interval is adjusted according to the pressure change rate; S34, performing preliminary screening on the collected pore water pressure data to remove obviously abnormal data points, providing accurate basic data for subsequent model analysis.

[0053] Specifically, step S3, applying seepage pressure and collecting pore water pressure data, is implemented in steps S31-S34: S31: Connect the pressure output end of the seepage pressure application module to the seepage channel of the soft rock sample clamping device via a high-pressure connector with a pressure rating ≥15 MPa. The diameter of the seepage channel is set to 2-5 mm, ensuring alignment with the pores on the side of the sample. Simultaneously, close the shut-off valves on both sides of the channel. Then, lay a 2-3 mm thick nitrile rubber sealing gasket on the inner wall of the clamping device where it contacts the sample. Tighten the clamping bolts with a torque wrench to a torque of 5-10 N·m to ensure no leakage during the seepage pressure transmission process. S32: Set the initial seepage pressure to 0.5 MPa and the final pressure to 5 MPa, with a pressure gradient of 0.5 MPa / stage. Input the parameters into the control interface of the high-pressure constant-pressure pump, start the pump preheating program, and preheat for 10-15 minutes. After the pump pressure stabilizes, proceed with the pump... The outlet valve is opened via the control panel, and the valve opening is adjusted to control the pressure rise rate at 0.1 MPa / min, avoiding sudden pressure increases that could damage the sample's pore structure. During each pressure application stage, pore water pressure data is collected in real-time using a data acquisition instrument at a frequency of 1 Hz. Pore water pressure sensors are positioned at 1 / 4, 1 / 2, and 3 / 4 of the sample height, with a sensor accuracy of 0.2%FS. The collected data is transmitted to the computer in real-time. When the data fluctuation is less than 0.02 MPa for 30 consecutive minutes, the seepage pressure is considered to have reached a stable state, and the stable data for that pressure level is recorded. The collected pressure data for each stage is then filtered, removing outliers exceeding three standard deviations from the average value. Linear interpolation is used to supplement missing data points, generating a pore water pressure-time curve to provide continuous and accurate basic data for subsequent model analysis. This step, through standardized seepage pressure application and data acquisition procedures, ensures that the soft rock sample is fully hydraulically balanced. Data from multiple measurement points can comprehensively reflect the distribution pattern of pore water pressure inside the sample, avoiding analytical biases caused by improper pressure application or abnormal data.

[0054] Preferably, step S4 specifically includes the following sub-steps: S41. Preset the frequency range and amplitude range of vibration loading according to the mechanical properties of the soft rock sample, and input the vibration parameters into the control unit of the vibration loading module to ensure that the output of the vibration load meets the test requirements; S42. After the seepage pressure stabilizes at the set value, start the vibration loading module so that the vibration load acts on the soft rock sample in the form of a sine wave, and record the start time of vibration loading at the same time; S43. The data acquisition module collects the strain and stress data of the soft rock sample under the vibration load in real time through strain sensors and stress sensors, and the acquisition frequency is higher than 5 times the vibration frequency to ensure the integrity of the data; S44. During the vibration loading process, monitor the appearance of the soft rock sample in real time. If obvious cracks or damage are found in the sample, stop the vibration loading immediately and record the test parameters at this time.

[0055] Specifically, step S4, the application of vibration load and acquisition of stress-strain data, is implemented in steps S41-S44: S41: Based on the estimated strength (1-3 MPa) of the soft rock sample, set the vibration frequency range to 5-20 Hz and the amplitude range to 0.1-1 mm. Input the parameters into the control software of the electromagnetic vibration table, setting the software sampling frequency to 1000 Hz. Perform no-load debugging for 5-10 minutes to confirm that the frequency and amplitude errors output by the vibration table are <5%. Simultaneously check the contact between the vibration loading head and the upper surface of the sample; the surface flatness error of the loading head should be ≤0.05 mm. If necessary, ensure tight contact through grinding. S42: After the seepage pressure stabilizes at the target value (2-5 MPa), start the loading program through the vibration table control software. Select a sine wave for the vibration waveform and set the loading duration to 60-120 minutes. Simultaneously, monitor the seepage pressure in real time through the pressure feedback system of the high-pressure constant-pressure pump. When the pressure fluctuation exceeds ±0.01 MPa, the pump automatically starts the pressure replenishment program to maintain pressure stability. S43: Start the data... According to the data acquisition instrument, the strain sensor uses a BFH120-3AA type resistance strain gauge with a sensitivity coefficient of 2.0±0.1. Three measuring points are evenly distributed along the circumference of the sample side, with one gauge attached to each measuring point along the axial and circumferential directions. The strain data acquisition frequency is set to 100 Hz. The stress sensor is installed between the vibration loading head and the sample, with a range of 0-5 MPa and an accuracy of 0.1%FS. Stress data and strain data are acquired synchronously to ensure complete capture of the mechanical response of each vibration cycle. During the vibration loading process, the S44 monitors the appearance of the sample in real time through a high-definition camera with a resolution of 1920×1080 pixels. The distance between the camera and the sample is maintained at 30-50 cm, and the frame rate is set to 25 frames / second. When a crack with a length > 2 mm is observed on the sample surface, the vibration time, frequency, amplitude, and corresponding stress and strain data are recorded. If the sample is obviously broken (broken area > 10% of the sample surface area), the vibration table and seepage system are immediately shut down via the emergency stop button, all acquired data are saved, and the sample test is terminated. This step, through precise vibration parameter control and synchronous data acquisition, can realistically simulate the vibration-seepage coupling environment faced by soft rock in engineering. Real-time visual monitoring can promptly grasp the sample failure process, providing complete data support for analyzing the dynamic rheological characteristics and critical failure conditions of soft rock.

[0056] Preferably, step S5 specifically includes the following sub-steps: S51, organizing the strain, stress, and pore water pressure data stored in the data acquisition module according to the time series and converting them into a data format recognizable by the ZSoil 3D finite element analysis platform; S52, establishing a geometric model consistent with the actual size of the soft rock sample in the ZSoil 3D finite element analysis platform, and setting the material properties of the model according to the initial physical parameters of the soft rock sample; S53, calling the strain softening aging viscoelastic-plastic algorithm, importing the organized test data into the model, setting the boundary conditions of the model, and simulating the constraint state during the test process; S54, running the finite element analysis to obtain the mechanical response distribution cloud map of the soft rock sample at different test stages, providing an analytical basis for the subsequent introduction of a coupled model.

[0057] Specifically, step S5 involves data processing and mechanical response analysis model establishment, implemented in steps S51-S54: S51: Export the stress and strain data collected in step S4 and the pore water pressure data collected in step S3 to Excel format. Preprocess the data using MATLAB software, first smoothing the data and then eliminating high-frequency noise using a 5-point moving average method. Sort the data by time series with a uniform time interval of 1 second. Convert the processed data to TXT format supported by the ZSoil 3D finite element analysis platform. The data columns include time, axial stress, axial strain, circumferential strain, and pore water pressure at three measuring points, totaling seven columns. S52: In ZSoil… A three-dimensional cylindrical model with the same dimensions as the soft rock sample was created in the platform. The sample diameter was set to 50 mm and the height to 100 mm. Tetrahedral elements were used for meshing, with the total number of elements controlled between 5000 and 8000. The mesh was refined within 5 mm of the top and bottom surfaces of the sample, with an element size of 2 mm, while the element size in other areas was 5 mm to ensure calculation accuracy near the loading surface. In step S53, the sample parameters obtained in step S1 were entered into the platform's material properties interface: density 2500-2700 kg / m³, porosity 10%-20%, and P-wave velocity 2000-3000 m / s. The "strain softening aged viscoelastic-plastic" constitutive model was selected, and the viscosity coefficient was entered as 1 × 10⁻⁶. 9 -1×10 10 The parameters are set as follows: Pa·s, aging parameter 0.5-0.8, yield stress 0.8-1.5 MPa. Boundary conditions are set: the lower end face constrains displacement in the X, Y, and Z directions, the upper end face only constrains displacement in the X and Y directions, and allows displacement in the Z direction. The side is set as a permeable boundary, and the pore water pressure boundary value is taken as the stable pressure value in step S3. The finite element analysis task is submitted in step S54, with an analysis step size of 0.1 seconds. The total analysis time is consistent with the actual test time (60-120 minutes). During the analysis, the convergence curve is monitored in real time. When the residual is less than 1×10⁻⁶, the convergence curve is considered complete. -6Convergence is determined upon completion of the analysis. Stress contour maps, strain contour maps, and pore water pressure contour maps at different time points are output. The stress-strain curve at the sample center point is extracted and compared with the actual test curve. If the error is less than 5%, the mechanical response analysis model is considered complete, laying the foundation for subsequent coupling model introduction. This step, through standardized data processing and refined model establishment, effectively connects test data with finite element simulation, ensuring that the model accurately reflects the mechanical state of soft rock under coupling effects, providing a reliable model foundation for subsequent long-term rheological property simulation.

[0058] The fluid-structure-thermal coupling fractional-order rheological model in this invention is a constitutive model capable of simultaneously characterizing the long-term rheological properties of soft rock under the influence of fluid (seepage), solid (mechanical), and thermal fields. It describes the memory properties and non-integer-order mechanical responses of soft rock rheology through fractional derivatives. In implementation, the key parameters of the model are first determined based on the initial physical parameters of the soft rock sample (such as elastic modulus and viscosity coefficient) and the temperature range of the engineering environment. The fractional derivative order is set to 0.1-0.9, the viscoelastic parameters to 0.2-0.8, and the thermo-mechanical coupling coefficient to 1×10⁻⁶. -5 -5×10 -4 The seepage-mechanical coupling coefficient was set to 0.1-0.8. Then, the pore water pressure data collected in step S3 and the initial temperature value obtained in step S1 were substituted into the model. Parameters were entered through the constitutive model interface of the ZSoil 3D finite element analysis platform to complete the association between the model and the test data. The purpose of this model is to overcome the limitations of traditional single mechanical models, simultaneously considering the influence of seepage pressure on the pore structure of soft rock and the effect of temperature changes on viscoelasticity, accurately calculating the stress-strain-time relationship of soft rock under multi-field coupling. This provides a realistic constitutive basis for simulating the long-term rheological properties of soft rock, avoiding parameter deviations caused by neglecting thermal and fluid coupling effects, ensuring that the simulation results reflect the actual service state of soft rock in engineering projects, and providing a reliable basis for the long-term stability assessment of engineering structures.

[0059] The vibration-seepage pressure dynamic fully coupled model in this invention is used to capture the evolution of the hydraulic state inside soft rock under the interaction of vibration load and seepage pressure, and can reflect the dynamic feedback relationship between the two. In implementation, the vibration angular frequency (31.4-125.6 radians / second) is first converted according to the vibration parameters (frequency 5-20 Hz, amplitude 0.1-1 mm) set in step S4. Combined with the pore water pressure data collected in step S3, the permeability (1×10⁻⁶) in the model is determined. -15 -5×10 -13The dynamic values ​​of permeability (per square meter) and porosity (5%-25%) are determined—permeability increases with increasing strain, while porosity decreases with increasing seepage pressure. The ZSoil platform's multi-field coupling calculation module then interacts with the vibration load parameters and seepage data in real time, enabling dynamic coupling calculation of vibration and seepage. This model addresses the problem of independent calculation of vibration and seepage in traditional models, accurately reflecting the impact of vibration-induced changes in the pore structure of soft rock on seepage, as well as the reaction of seepage pressure changes to the vibration response of soft rock, and dynamically updating the pore water seepage velocity (1×10⁻⁶ m²) within the soft rock. -7 -1×10 -5 (m / s). This provides dynamic model support for the calculation of hydraulic parameters of soft rock under coupled effects, ensuring that the hydraulic conditions in subsequent rheological characteristic simulations are consistent with reality, and avoiding deviations in hydraulic state analysis caused by ignoring the coupling effect between the two.

[0060] The strain-softening time-dependent viscoelastic-plastic algorithm in this invention is a calculation method used to analyze the superimposed effects of elastic, viscoelastic, and plastic deformation of soft rock under load, and to consider the influence of time on softening characteristics. In implementation, parameters are first determined according to the deformation stages of the soft rock: elastic stage: elastic modulus 1-5 GPa, Poisson's ratio 0.25-0.45; viscoelastic stage: elastic modulus 0.7-4.5 GPa, viscosity coefficient 5 × 10⁻⁶. 8 -5×10 10 Pa·s; yield stress in the plastic stage is 0.5-3 MPa, and the aging softening coefficient is 0.01-0.1; then the stress-strain data preprocessed in step S5 is input into the corresponding constitutive module of the ZSoil platform according to the time series. The algorithm automatically identifies the deformation stage—when the stress is less than the yield stress, elastic-viscoelastic deformation is dominant; when it exceeds the yield stress, plastic calculation is initiated, and an aging factor is introduced to adjust the softening coefficient over time. The purpose of this algorithm is to comprehensively characterize the entire deformation process of soft rock from elastic to plastic and from hardening to softening, and accurately calculate the total strain (elastic + viscoelastic + plastic strain) at different time points. It overcomes the shortcomings of traditional algorithms that only consider a single deformation type, accurately reflects the aging softening characteristics of soft rock under long-term load, provides accurate deformation calculation logic for mechanical response analysis models, and ensures that the simulation results are highly consistent with the actual mechanical behavior of soft rock.

[0061] The ZSoil three-dimensional finite element analysis platform of this invention is a numerical calculation platform for simulating the mechanical response of soft rock, performing coupled model calculations, and analyzing long-term rheological properties. In implementation, firstly, S51 converts the preprocessed stress, strain, and pore water pressure data into the TXT format supported by the platform; S52 establishes a three-dimensional cylindrical model according to the actual sample size (diameter 50-100 mm, height 100-200 mm), and meshes it using tetrahedral elements (element size 2-10 mm, with finer meshing near the loading surface); S53 inputs the sample's physical parameters and constitutive model (such as a strain-softening aging viscoelastic-plastic algorithm), and sets boundary conditions (fixed lower end face, free loading of the upper end face, and water permeability on the sides); S54 submits the analysis task, with a step size of 0.1-1 seconds and a total time of 60-120 minutes, while simultaneously associating a fluid-structure-thermal coupled fractional-order rheological model and a vibration-seepage pressure dynamic fully coupled model to complete multi-field coupled simulation. The platform integrates test data with various models to enable visualized analysis of internal stress, strain, and pore water pressure in soft rock (outputting contour maps and rheological curves), and supports long-term rheological simulation (1000-10000 hours). It provides an integrated numerical computing environment, resolving the connection between test data and model calculations, improving simulation efficiency and accuracy, and offering technical support for extracting rheological mechanical property parameters of soft rock (such as long-term strength and creep modulus), thus assisting in engineering design optimization and risk assessment.

[0062] like Figure 2As shown, a method for testing the rheological mechanical properties of soft rock based on vibration-seepage pressure coupling is implemented through different units, including: a soft rock sample pretreatment and fixation unit, a multi-parameter loading control unit, a high-precision data acquisition unit, a ZSoil finite element analysis and simulation unit, a coupled model calculation unit, and a test result output and storage unit. The soft rock sample pretreatment and fixation unit is connected to the multi-parameter loading control unit to complete the processing and fixation of the soft rock sample and transfer the processed sample to the multi-parameter loading control unit. The multi-parameter loading control unit is connected to both the soft rock sample pretreatment and fixation unit and the high-precision data acquisition unit to apply seepage pressure and vibration load to the soft rock sample and transfer the loading parameters to the high-precision data acquisition unit. The high-precision data acquisition unit is connected to both the multi-parameter loading control unit and the ZSoil finite element analysis and simulation unit to collect data. The system collects mechanical and seepage data from soft rock samples and transmits the data to the ZSoil finite element analysis and simulation unit. The ZSoil finite element analysis and simulation unit is connected to the high-precision data acquisition unit and the coupled model calculation unit, respectively, for preliminary processing and finite element simulation of the acquired data, and transmits the processing results to the coupled model calculation unit. The coupled model calculation unit is connected to the ZSoil finite element analysis and simulation unit and the test result output and storage unit, respectively, for calling the fluid-solid-thermal coupling fractional-order rheological model, the vibration-seepage-pressure dynamic fully coupled model, and the strain softening aging viscoelastic-plastic algorithm to perform coupled analysis of the simulation results, and transmits the analysis results to the test result output and storage unit. The test result output and storage unit is connected to the coupled model calculation unit, for storing the soft rock rheological and mechanical property parameters obtained from the coupled analysis, and outputting a test report in a specified format.

[0063] The vibration-seepage-pressure coupling-based testing method for the rheological mechanical properties of soft rock utilizes a fluid-structure-thermal coupling fractional-order rheological model and a vibration-seepage-pressure dynamic fully coupled model. This method is no longer limited to a single physical field or simple coupling, but can fully characterize the dynamic interaction between vibration, seepage, and soft rock rheology. It accurately reflects the mechanical behavior of soft rock under multi-field coupling in actual engineering, significantly reducing the deviation between test results and actual conditions, and meeting the requirements of engineering design for accurate parameters. Simultaneously, by employing a strain-softening-aging viscoelastic-plastic algorithm combined with the ZSoil three-dimensional finite element analysis platform, the method deeply integrates the collected strain, stress, and pore water pressure data with numerical simulations, meticulously characterizing key properties of soft rock such as strain softening and aging viscoelastic-plastic properties. This solves the problem of coarse characterization of key mechanical properties of soft rock in existing technologies, providing more accurate basic data for subsequent engineering analysis.

[0064] This testing method, with its advantages in process design and system collaboration, effectively overcomes the shortcomings of existing technologies, such as low testing efficiency and poor reliability. It optimizes the testing process step-by-step, standardizing operations from soft rock sample preparation, seepage pressure application, vibration loading to data acquisition and simulation analysis. Furthermore, it establishes an integrated testing system encompassing vibration loading, seepage pressure application, and data acquisition, enabling collaborative work among modules. During testing, the data acquisition module can synchronously collect multiple parameters in real time. The acquisition frequency and filtering methods are optimized to ensure data integrity and accuracy. Subsequently, after importing the data into the analysis platform, model building, boundary setting, and finite element analysis can be quickly completed, achieving integration from parameter application and data acquisition to simulation analysis. This improves testing efficiency, reduces human error, enhances the reliability of test results, and provides stronger technical support for engineering applications.

[0065] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," "link," and "fix" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0066] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various equivalent changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for testing the rheological mechanical properties of soft rock based on vibration-seepage pressure coupling, characterized in that, Includes the following steps: S1. Select a soft rock sample and obtain a sample that meets the test size requirements using a dedicated sampling device. Perform surface smoothing treatment on the soft rock sample and use a high-precision measuring instrument to obtain the initial physical parameters of the sample. S2. Construct a test system including a vibration loading module, a seepage pressure application module, and a data acquisition module. Fix the treated soft rock sample in the sample clamping device of the test system, ensuring close contact between the soft rock sample and the vibration loading module and seepage pressure application module. S3. Activate the seepage pressure application module to apply seepage pressure to the interior of the soft rock sample according to a preset seepage pressure gradient. Simultaneously, activate the data acquisition module to collect real-time data on the pore water pressure distribution of the soft rock sample under different seepage pressures. S4. After the seepage pressure stabilizes, activate the vibration loading module to apply a periodic vibration load to the soft rock sample according to the set vibration frequency and amplitude parameters. The data acquisition module simultaneously collects the strain and stress change data of the soft rock sample under the vibration-seepage pressure coupling effect. S5. Import the collected strain, stress, and pore water pressure data into the ZSoil three-dimensional finite element analysis platform, and use the strain softening aging viscoelastic-plastic algorithm to perform preliminary data processing and establish a mechanical response analysis model for the soft rock sample; S6. Based on the mechanical response analysis model, introduce the fluid-structure-thermal coupling fractional-order rheological model and the vibration-seepage pressure dynamic full coupling model respectively, and use the ZSoil three-dimensional finite element analysis platform to simulate and analyze the long-term rheological mechanical properties of the soft rock sample under the coupled action of vibration-seepage pressure, and obtain the rheological mechanical property parameters of the soft rock sample; The expression for the fluid-structure-thermal coupling fractional-order rheological model is as follows: ,in, For the stress of the soft rock sample, For the strain of the soft rock sample, For time, For integration variables, The order of the fractional derivative For viscoelastic parameters, For soft rock elastic modulus, The viscosity coefficient of soft rock. The viscoelastic coupling coefficient is... Thermo-mechanical coupling coefficient, The seepage-mechanical coupling coefficient is... Temperature of the soft rock sample. Pore ​​water pressure; The dynamic fully coupled model expression for vibration-seepage pressure is as follows: ,in, For soft rock permeability, For soft rock porosity, it varies with pore water pressure. and strain change, The density of pore water, The pore water seepage velocity, The frequency of vibration. The vibration phase angle; The expression for the strain-softening aging viscoelastic-plastic algorithm is as follows: ； ； ； ； in, For total strain, For elastic strain, For viscoelastic strain, For plastic strain, For the elastic stage, the elastic modulus. Poisson's ratio, The symbol for Kronecker. For stress tensor, This refers to the elastic modulus in the viscoelastic stage. The viscosity coefficient is the viscosity coefficient in the viscoelastic stage. For timeliness parameters, For relaxation time, For yield stress, For the enhancement coefficient, This is the softening coefficient over time. For reference only.

2. The method for testing the rheological mechanical properties of soft rock based on vibration-seepage pressure coupling according to claim 1, characterized in that, When simulating the rheological mechanical properties of soft rock using the ZSoil 3D finite element analysis platform, the expression for the mesh generation control model is as follows: ,in, The finite element mesh size is... For the basic size factor of the grid, The stress influence coefficient is... The strain rate influence coefficient is... For maximum stress, For the maximum strain rate, The coefficient representing the influence of seepage pressure is denoted as . For reference pore water pressure, This is the vibration influence coefficient.

3. The method for testing the rheological mechanical properties of soft rock based on vibration-seepage pressure coupling according to claim 1, characterized in that, The model expression for correcting the rheological and mechanical properties of soft rock is as follows: ,in, These are the corrected rheological and mechanical property parameters for soft rock. These are the initial rheological properties parameters. This is the stress cumulative effect coefficient. This represents the cumulative influence coefficient of the seepage-vibration coupling. This is the fractional strain rate influence coefficient.

4. The method for testing the rheological mechanical properties of soft rock based on vibration-seepage pressure coupling according to claim 1, characterized in that, S3 specifically includes the following steps: S31, connecting the pressure output terminal of the seepage pressure application module to the pore channels of the soft rock sample, and adjusting the opening state of the seepage path through the valve control device to ensure that the seepage pressure can be uniformly transmitted to the interior of the soft rock sample; S32, setting the initial value, termination value, and pressure gradient of the seepage pressure application, and starting the pressure control unit to gradually increase the seepage pressure according to the set gradient, avoiding sudden pressure changes that could damage the soft rock sample structure; S33, during the increase of seepage pressure, the data acquisition module collects pressure data through pore water pressure sensors placed at different locations on the soft rock sample, and the acquisition interval is adjusted according to the rate of pressure change; S34, performing preliminary screening of the collected pore water pressure data to remove obviously abnormal data points, providing accurate basic data for subsequent model analysis.

5. The method for testing the rheological mechanical properties of soft rock based on vibration-seepage pressure coupling according to claim 1, characterized in that, S4 specifically includes the following steps: S41, preset the frequency range and amplitude range of vibration loading according to the mechanical properties of the soft rock sample, input the vibration parameters into the control unit of the vibration loading module, and ensure that the output of the vibration load meets the test requirements; S42, after the seepage pressure stabilizes at the set value, start the vibration loading module so that the vibration load acts on the soft rock sample in the form of a sine wave, and record the start time of vibration loading at the same time. S43. The data acquisition module collects strain and stress data of soft rock samples under vibration load in real time through strain sensors and stress sensors. The acquisition frequency is more than 5 times the vibration frequency to ensure data integrity. S44. During vibration loading, the appearance of the soft rock sample is monitored in real time. If obvious cracks or damage are found in the sample, vibration loading is stopped immediately and the test parameters at this time are recorded.

6. The method for testing the rheological mechanical properties of soft rock based on vibration-seepage pressure coupling according to claim 1, characterized in that, S5 specifically includes the following steps: S51, organizing the strain, stress, and pore water pressure data stored in the data acquisition module according to the time series and converting them into a data format recognizable by the ZSoil 3D finite element analysis platform; S52, establishing a geometric model consistent with the actual size of the soft rock sample in the ZSoil 3D finite element analysis platform, and setting the material properties of the model according to the initial physical parameters of the soft rock sample; S53, calling the strain softening aging viscoelastic-plastic algorithm, importing the organized test data into the model, setting the boundary conditions of the model, and simulating the constraint state during the test process; S54, running the finite element analysis to obtain the mechanical response distribution cloud map of the soft rock sample at different test stages, providing an analytical basis for the subsequent introduction of a coupled model.

7. The method for testing the rheological mechanical properties of soft rock based on vibration-seepage pressure coupling according to any one of claims 1-6, characterized in that, This method is implemented through different units, including: a soft rock sample pretreatment and fixation unit, a multi-parameter loading control unit, a high-precision data acquisition unit, a ZSoil finite element analysis and simulation unit, a coupled model calculation unit, and a test result output and storage unit. The soft rock sample pretreatment and fixation unit is connected to the multi-parameter loading control unit to process and fix the soft rock sample, and then transfers the processed sample to the multi-parameter loading control unit. The multi-parameter loading control unit is connected to both the soft rock sample pretreatment and fixation unit and the high-precision data acquisition unit, and applies seepage pressure and vibration load to the soft rock sample, transferring the loading parameters to the high-precision data acquisition unit. The high-precision data acquisition unit is connected to both the multi-parameter loading control unit and the ZSoil finite element analysis and simulation unit, and acquires the mechanical and seepage data of the soft rock sample. The data is then transmitted to the ZSoil finite element analysis and simulation unit. The ZSoil finite element analysis and simulation unit is connected to the high-precision data acquisition unit and the coupled model calculation unit, respectively, for preliminary processing and finite element simulation of the acquired data, and the processing results are transmitted to the coupled model calculation unit. The coupled model calculation unit is connected to the ZSoil finite element analysis and simulation unit and the test result output and storage unit, respectively, for calling the fluid-solid-thermal coupling fractional-order rheological model, the vibration-seepage-pressure dynamic fully coupled model, and the strain softening aging viscoelastic-plastic algorithm to perform coupled analysis of the simulation results, and the analysis results are transmitted to the test result output and storage unit. The test result output and storage unit is connected to the coupled model calculation unit, for storing the soft rock rheological mechanical property parameters obtained from the coupled analysis, and outputting the test report in a specified format.

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