Method and device for constructing segmented model of mechanical parameter evolution of soft rock under the influence of multiple factors

Abstract

The present disclosure provides a method and device for constructing a segmented model of the evolution of mechanical parameters of soft rock under the influence of multiple factors, belonging to the field of electrical digital data processing, the method comprising: establishing a mapping relationship between the mechanical parameters of soft rock and the confining pressure and plastic deviatoric strain based on the mechanical parameters of soft rock and the plastic deviatoric strain under different confining pressures to obtain a first data set; segmenting the first data set based on the relative size of the critical plastic deviatoric strain of the soft rock and the plastic deviatoric strain to obtain a second data set in the elastic deformation stage, a third data set in the softening deformation stage, and a fourth data set in the residual deformation stage; performing data fitting based on the second data set, the third data set, and the fourth data set, respectively, to obtain a segmented model of the evolution of mechanical parameters of soft rock. The present disclosure can realize the construction of a systematic model for characterizing the evolution of mechanical parameters of soft rock at different deformation stages under the influence of multiple factors, and provides a favorable analysis tool for solving the engineering problem of large deformation of soft rock tunnels with high ground stress.

Description

Technical Field

[0001] The present invention belongs to the field of electronic digital data processing, and more specifically, relates to a method and device for constructing a segmented model of soft rock mechanical parameter evolution under the influence of multiple factors. Background Art

[0002] In recent years, with the increasing scale and number of tunnel construction in high-geo-stress soft rock tunnels, the large deformation problem of high-geo-stress soft rock tunnels has become a major engineering problem that tunnel practitioners and scientific researchers need to solve urgently. Accurately understanding and characterizing the evolution process of soft rock mechanical parameters is the fundamental prerequisite for solving the engineering problem of large deformation of high-geo-stress soft rock tunnels. However, after the excavation of high-geo-stress soft rock tunnels, the stress state of the surrounding rock is adjusted, and the mechanical parameters of the surrounding rock around the tunnel undergo complex evolution under the influence of the coupling of confining pressure and plastic strain. Most of the current studies only focus on the evolution law of soft rock mechanical parameters in a certain stage. There is no systematic mechanical parameter evolution model that characterizes the entire deformation process of soft rock, and the factors considered are relatively simple. Summary of the invention

[0003] The purpose of the present invention is to provide a method and device for constructing a segmented model of the evolution of mechanical parameters of soft rock under the influence of multiple factors, so as to realize the construction of a systematic model for characterizing the evolution of mechanical parameters of soft rock at different deformation stages under the influence of multiple factors, and provide a favorable analysis tool for solving the engineering problem of large deformation of soft rock tunnels with high ground stress.

[0004] A first aspect of the embodiments of the present disclosure provides a method for constructing a segmented model of soft rock mechanical parameter evolution under the influence of multiple factors, comprising:

[0005] Based on the mechanical stress-strain relationship data of soft rock under different confining pressures, the mechanical parameters, plastic deviator strain and critical plastic deviator strain of soft rock under different confining pressures are obtained.

[0006] Based on the mechanical parameters and plastic deviatoric strain of soft rock under different confining pressures, a mapping relationship between the mechanical parameters of soft rock and confining pressure and plastic deviatoric strain is established to obtain a first data set;

[0007] Segmenting the first data set based on the relative size of the critical plastic deviator strain of soft rock and the plastic deviator strain to obtain a second data set in the elastic deformation stage, a third data set in the softening deformation stage, and a fourth data set in the residual deformation stage;

[0008] Data fitting is performed based on the second data set, the third data set and the fourth data set respectively to obtain a segmented model of soft rock mechanical parameter evolution.

[0009] A second aspect of the embodiments of the present disclosure provides a device for constructing a segmented model of soft rock mechanical parameter evolution under the influence of multiple factors, comprising:

[0010] A data calculation module is used to obtain the mechanical parameters, plastic deviatoric strain and critical plastic deviatoric strain of soft rock under different confining pressures based on the mechanical stress-strain relationship data of soft rock under different confining pressures;

[0011] A mapping construction module is used to establish a mapping relationship between the soft rock mechanical parameters and the confining pressure and the plastic deviatoric strain based on the soft rock mechanical parameters and the plastic deviatoric strain under different confining pressures to obtain a first data set;

[0012] A data segmentation module, for segmenting the first data set based on the relative size of the critical plastic deviator strain of soft rock and the plastic deviator strain, to obtain a second data set in the elastic deformation stage, a third data set in the softening deformation stage, and a fourth data set in the residual deformation stage;

[0013] The model building module is used to perform data fitting based on the second data set, the third data set and the fourth data set respectively to obtain a segmented model of soft rock mechanical parameter evolution.

[0014] In a third aspect of an embodiment of the present disclosure, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, the steps of the method for constructing a segmented model of the evolution of soft rock mechanical parameters under the influence of multiple factors are implemented.

[0015] In a fourth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for constructing a segmented model of the evolution of soft rock mechanical parameters under the influence of multiple factors are implemented.

[0016] The beneficial effects of the method and device for constructing a segmented model of soft rock mechanical parameter evolution under the influence of multiple factors provided by the embodiments of the present disclosure are:

[0017] The segmented model for the evolution of mechanical parameters of soft rock proposed in the embodiment of the present disclosure can systematically characterize the evolution process of mechanical parameters of soft rock in different deformation stages (elastic deformation stage, softening deformation stage, residual deformation stage). Moreover, the segmented model for the evolution of mechanical parameters of soft rock proposed in the embodiment of the present disclosure fully considers the coupling effect of confining pressure and plastic strain. In addition, the segmented model for the evolution of mechanical parameters of soft rock proposed in the embodiment of the present disclosure comprehensively characterizes the evolution of deformation parameters and the evolution of strength parameters, including elastic model, Poisson's ratio, cohesion, and friction angle, providing a favorable analysis tool for solving the engineering problem of large deformation of soft rock tunnels with high ground stress. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0019] Figure 1 A schematic flow chart of a method for constructing a segmented model of soft rock mechanical parameter evolution under the influence of multiple factors provided in an embodiment of the present disclosure;

[0020] Figure 2 A schematic diagram of the soft rock stress-strain curve characteristics and the evolution of mechanical parameters and control factors provided in one embodiment of the present disclosure; wherein (a) is the three-stage deformation characteristics of the soft rock stress-strain curve, and (b) is the evolution of mechanical parameters and control factors of the soft rock;

[0021] Figure 3 The following are stress-strain test curves of soft rock under different confining pressure conditions provided by an embodiment of the present disclosure; wherein (a) is the strain-strain cyclic loading and unloading test curve of soft rock under 0 MPa confining pressure, (b) is the strain-strain cyclic loading and unloading test curve of soft rock under 5 MPa confining pressure, (c) is the strain-strain cyclic loading and unloading test curve of soft rock under 10 MPa confining pressure, (d) is the strain-strain cyclic loading and unloading test curve of soft rock under 20 MPa confining pressure, and (e) is the strain-strain cyclic loading and unloading test curve of soft rock under 30 MPa confining pressure;

[0022] Figure 4 A fitting curve of the evolution law of critical plastic deviatoric strain of soft rock provided in an embodiment of the present disclosure;

[0023] Figure 5 The fitting curve of the three-stage evolution model of the elastic modulus of soft rock provided in one embodiment of the present disclosure; wherein (a) is the elastic deformation stage, (b) is the softening deformation stage, and (c) is the residual deformation stage;

[0024] Figure 6 This is a fitting curve of the three-stage evolution model of the Poisson's ratio of soft rock provided in one embodiment of the present disclosure; wherein (a) is the elastic deformation stage, (b) is the softening deformation stage, and (c) is the residual deformation stage;

[0025] Figure 7 This is a fitting curve of the three-stage evolution model of the soft rock friction angle provided in an embodiment of the present disclosure; wherein (a) is the elastic deformation stage, (b) is the softening deformation stage, and (c) is the residual deformation stage;

[0026] Figure 8This is a fitting curve of the three-stage evolution model of soft rock cohesion provided by an embodiment of the present disclosure; wherein (a) is the elastic deformation stage, (b) is the softening deformation stage, and (c) is the residual deformation stage;

[0027] Fig. 9 A structural block diagram of a device for constructing a segmented model of soft rock mechanical parameter evolution under the influence of multiple factors provided in an embodiment of the present disclosure;

[0028] Fig.10 A schematic block diagram of an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0029] In the following description, specific details such as specific system structures and technologies are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present disclosure. However, it should be clear to those skilled in the art that the present disclosure may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obstructing the description of the present disclosure with unnecessary details.

[0030] In order to make the purpose, technical solutions and advantages of the present disclosure more clear, specific embodiments will be described below in conjunction with the accompanying drawings.

[0031] Please refer to Figure 1 , Figure 1 A schematic flow chart of a method for constructing a segmented model of soft rock mechanical parameter evolution under the influence of multiple factors provided in an embodiment of the present disclosure, the method comprising:

[0032] S101: Based on the mechanical stress-strain relationship data of soft rock under different confining pressures, the mechanical parameters, plastic deviatoric strain and critical plastic deviatoric strain of soft rock under different confining pressures are obtained.

[0033] In this embodiment, firstly, it is necessary to obtain the stress-strain relationship data of soft rock mechanics under different confining pressures. The above data can be obtained through experiments, for example, mechanical loading tests are performed on soft rock samples under different confining pressures in the laboratory to record the changes in the stress-strain of the soft rock mechanics.

[0034] Then, based on the above soft rock mechanical stress-strain relationship data, the soft rock mechanical parameters under different confining pressures can be calculated. The soft rock mechanical parameters can include elastic modulus, Poisson's ratio, friction angle and cohesion, which reflect the mechanical properties of soft rock under different confining pressures.

[0035] The elastic modulus is the proportionality coefficient of the material in the elastic deformation stage, when its stress and strain are in direct proportion (i.e., conforming to Hooke's law), which reflects the material's ability to resist elastic deformation. The stress-strain relationship data of soft rock mechanics can be displayed through the stress-strain curve.

[0036] Specifically, the calculation steps of the elastic modulus are as follows:

[0037] First, determine the elastic stage of the stress-strain curve, which can be achieved by observing the change in the slope of the curve. In the elastic stage, the slope of the curve remains basically unchanged, and the material can return to its original shape after unloading in this stage; then, select two data points in the elastic stage and ; Finally, according to the formula Calculate the elastic modulus; where, represents the elastic modulus, All represent stress, Both represent strain.

[0038] Poisson's ratio It is the ratio of the absolute value of the transverse normal strain to the axial normal strain when the material is subjected to unidirectional tension or compression, that is, ,in, represents the axial strain, Represents transverse strain. Poisson's ratio reflects the transverse deformation characteristics of the material.

[0039] The friction angle and cohesion are calculated based on the Mohr-Coulomb criterion. The Mohr-Coulomb criterion is the basic criterion for describing the shear strength of geotechnical materials and is expressed as ,in represents the shear stress, represents the normal stress, Represents cohesion, represents the friction angle.

[0040] Specifically, the calculation steps are as follows:

[0041] First, according to the rock compressive strength and confining pressure under different confining pressure conditions, the shear stress is the vertical axis, normal stress As the horizontal axis, draw multiple Mohr circles; secondly, In the rectangular coordinate system, find the common tangents of the above-mentioned multiple Mohr circles and draw them as the strength envelope, and give the strength envelope expression; finally, find the points on the envelope corresponding to different confining pressures, and make tangents to them respectively, and intersect them with the vertical axis in the opposite direction; then, at this time, the slope of the tangent at each point is , and then by The friction angle under different confining pressures is calculated, and the intersection of each tangent line and the ordinate axis is the cohesion under different confining pressures. .

[0042] At the same time, the plastic deviator strain of soft rock can also be determined by analyzing the stress-strain curve. Plastic deviator strain refers to the degree of irreversible deformation of soft rock during stress. When the stress on soft rock exceeds its elastic limit, plastic deviator strain will occur.

[0043] Specifically, in the stress-strain curve, when the stress exceeds the elastic limit, the strain will not completely return to zero during unloading, but a part of the deformation will remain. The strain corresponding to this residual deformation is the plastic strain.

[0044] The plastic deviator strain can be determined by the incremental method. At each level of loading, the total strain after loading and the amount of elastic strain recovery after unloading are recorded. The plastic strain is equal to the total strain minus the amount of elastic strain recovery. By accumulating the plastic deviator strain generated by each level of loading, the plastic deviator strain during the entire loading process can be obtained.

[0045] In this embodiment, plastic strain is expressed as plastic deviatoric strain. The expression of plastic deviatoric strain is:

[0046]

[0047] in, represents the plastic deviatoric strain, represents the first principal strain produced by plasticity, Represents the third principal strain caused by plasticity.

[0048] In addition, this embodiment also needs to determine the critical plastic deviator strain. The critical plastic deviator strain can be used to determine whether the soft rock has entered a residual state. When the plastic deviator strain of the soft rock reaches a critical value, the mechanical behavior of the soft rock will change significantly. The critical plastic deviator strain adopts the critical plastic deviator strain. To characterize.

[0049] Specifically, the critical plastic deviator strain is a strain limit value at which the mechanical behavior of soft rock changes significantly. During the deformation process of soft rock, when the plastic deviator strain reaches this critical value, the mechanical properties of soft rock, such as strength and stiffness, may change significantly, such as transitioning from the plastic accelerated deformation stage (softening stage) to the residual damage stage (residual stage). By observing the stress-strain curve of soft rock, the point where the slope of the curve changes significantly can be found. In the early stage of soft rock deformation, the stress-strain curve may show the linear characteristics of the elastic stage. As the strain increases, the slope of the curve gradually decreases after entering the plastic stage. When the slope decreases to a certain extent or a point where the slope suddenly changes occurs, the plastic deviator strain corresponding to this point can be used as the critical plastic deviator strain.

[0050] Therefore, through the above process, the mechanical parameters, plastic deviatoric strain and critical plastic deviatoric strain of soft rock under different confining pressures can be obtained.

[0051] S102: Based on the soft rock mechanical parameters and plastic deviatoric strain under different confining pressures, a mapping relationship between the soft rock mechanical parameters and the confining pressure and the plastic deviatoric strain is established to obtain a first data set.

[0052] In this embodiment, the mapping relationship between the mechanical parameters of soft rock and the confining pressure and plastic deviatoric strain can be constructed in the form of a table. Each entry in the table records a set of confining pressure, plastic deviatoric strain and corresponding mechanical parameter values. Multiple sets of data corresponding to multiple sets of confining pressures constitute the first data set.

[0053] S103: segmenting the first data set based on the critical plastic deviator strain of soft rock and the relative size of the plastic deviator strain to obtain a second data set in the elastic deformation stage, a third data set in the softening deformation stage, and a fourth data set in the residual deformation stage.

[0054] In this embodiment, based on the stress-strain test curves of soft rock under different confining pressure conditions, it can be seen that the full stress-strain curve of soft rock can be divided into three stages: elastic deformation stage, softening deformation stage, and residual deformation stage, and the control factors of the evolution of soft rock mechanical parameters in different deformation stages are different, such as Figure 2 As shown. Among them, Figure 2 (a) shows the three-stage deformation characteristics of the soft rock stress-strain curve. Figure 2 (b) represents the evolution of mechanical parameters of soft rock and the controlling factors. In the elastic deformation stage, the deformation of the material is reversible, only elastic strain occurs, no plastic deformation occurs, the plastic deviator strain is 0, and the evolution of mechanical parameters of soft rock is controlled by the confining pressure factor; in the soft rock deformation stage, the material begins to deform plastically but has not yet been completely destroyed. The plastic deviator strain is in a state of increasing from zero but has not yet reached the critical plastic deviator strain, that is, it is between zero and the critical plastic deviator strain. The mechanical parameters are not only affected by the confining pressure, but also change with the change of the degree of plastic deviator strain, that is, the evolution of mechanical parameters of soft rock is affected by the coupling of confining pressure and plastic strain; in the residual deformation stage, the soft rock has undergone complete plastic deformation and reached the limit state it can withstand. At this time, the plastic deviator strain is greater than the critical plastic deviator strain, and the evolution of mechanical parameters of soft rock is controlled by the confining pressure factor.

[0055] Therefore, the first data set can be divided based on the relative size of the critical plastic deviator strain and the plastic deviator strain of the soft rock. Specifically, the data in the first data set whose corresponding plastic deviator strain is equal to 0 is divided into a second data set, and the second data set is used to characterize the elastic deformation stage of the soft rock; the data in the first data set whose corresponding plastic deviator strain is between zero and the critical plastic deviator strain is divided into a third data set, and the third data set is used to characterize the softening deformation stage of the soft rock; the data in the first data set whose corresponding plastic deviator strain is greater than the critical plastic deviator strain is divided into a fourth data set, and the fourth data set is used to characterize the residual deformation stage of the soft rock.

[0056] S104: performing data fitting based on the second data set, the third data set, and the fourth data set respectively to obtain a segmented model of soft rock mechanical parameter evolution.

[0057] In this embodiment, data fitting is performed based on the second data set, the third data set, and the fourth data set to obtain a segmented model of soft rock mechanical parameter evolution, including:

[0058] Based on the soft rock mechanical parameters in the second data set and the corresponding confining pressure, data fitting is performed to obtain a soft rock mechanical parameter evolution model in the elastic deformation stage;

[0059] Based on the soft rock mechanical parameters in the third data set and the corresponding confining pressure and plastic deviatoric strain, data fitting is performed to obtain the soft rock mechanical parameter evolution model in the softening deformation stage;

[0060] Based on the soft rock mechanical parameters in the fourth data set and the corresponding confining pressure, data fitting is performed to obtain the soft rock mechanical parameter evolution model in the residual deformation stage;

[0061] The soft rock mechanical parameter evolution model in the elastic deformation stage, the soft rock mechanical parameter evolution model in the softening deformation stage and the soft rock mechanical parameter evolution model in the residual deformation stage are determined as the soft rock mechanical parameter evolution segmented model.

[0062] In this embodiment, for the mapping relationship between the mechanical parameters of soft rock and the confining pressure and plastic deviatoric strain at different deformation stages, a nonlinear fitting method is used, and based on a general global optimization algorithm, data fitting is performed on the second data set, the third data set and the fourth data set, and an evolution model of the mechanical parameters of soft rock in the elastic deformation stage, the softening deformation stage and the residual deformation stage, that is, a segmented model of the evolution of the mechanical parameters of soft rock, can be obtained.

[0063] Among them, in the elastic deformation stage, the evolution of soft rock mechanical parameters is only controlled by the confining pressure factor. Therefore, data fitting can be performed based on the soft rock mechanical parameters in the second data set and the corresponding confining pressure to obtain the soft rock mechanical parameter evolution model in the elastic deformation stage; in the softening deformation stage, the evolution of soft rock mechanical parameters is affected by the coupling of confining pressure and plastic strain. Therefore, data fitting can be performed based on the soft rock mechanical parameters in the third data set and the corresponding confining pressure and plastic deviatoric strain to obtain the soft rock mechanical parameter evolution model in the softening deformation stage; in the residual deformation stage, the evolution of soft rock mechanical parameters is only controlled by the confining pressure factor. Therefore, data fitting can be performed based on the soft rock mechanical parameters in the fourth data set and the corresponding confining pressure to obtain the soft rock mechanical parameter evolution model in the residual deformation stage.

[0064] From the above, it can be concluded that the segmented model of the evolution of mechanical parameters of soft rock under the influence of the coupling of confining pressure and plastic strain in this embodiment systematically characterizes the evolution process of mechanical parameters of soft rock in different deformation stages (elastic deformation stage, softening deformation stage, residual deformation stage). Moreover, the segmented model of the evolution of mechanical parameters of soft rock proposed in this embodiment fully considers the coupling influence of confining pressure and plastic strain. In addition, the segmented model of the evolution of mechanical parameters of soft rock proposed in this embodiment comprehensively characterizes the evolution of deformation parameters and strength parameters, including elastic model, Poisson's ratio, cohesion, and friction angle, which provides a favorable analysis tool for solving the engineering problem of large deformation of soft rock tunnels with high ground stress.

[0065] For example, during tunnel excavation, the soft rock mechanical evolution model of this embodiment can predict the deformation, stress changes and development of the plastic zone of soft rock at different construction stages, providing a basis for tunnel support design. By analyzing the changes in soft rock mechanical parameters with stress state, the risks of excessive deformation around the tunnel and instability and collapse of the cavern that may occur during tunnel construction can be evaluated, and corresponding emergency plans can be formulated based on the risk assessment results to improve construction safety.

[0066] In one embodiment of the present disclosure, the method for constructing a segmented model of soft rock mechanical parameter evolution under the influence of multiple factors further includes:

[0067] Making soft rock sample specimens;

[0068] Conventional triaxial compression tests and cyclic loading and unloading triaxial compression tests were carried out on soft rock specimens to determine the mechanical stress-strain relationship data of soft rock under different confining pressures.

[0069] In this embodiment, the soft rock sample specimens can be processed into standard cylindrical specimens with a height of 10 cm and a diameter of 5 cm through on-site sampling, core drilling, grinding and other processes. The specimens are divided into 10 groups, each with 3 rock sample specimens, for a total of 30 rock sample specimens.

[0070] Conventional triaxial compression tests and cyclic loading and unloading triaxial compression tests were carried out on 10 groups of rock specimens under 5 different confining pressure conditions. The specific test conditions are shown in Table 1.

[0071] Before the cyclic loading and unloading triaxial compression test under each confining pressure condition, conventional triaxial compression tests under different confining pressure conditions are first carried out to determine the peak strength and maximum plastic deviatoric strain value of the soft rock under each confining pressure condition as reference data for the cyclic loading and unloading triaxial compression test under different confining pressure conditions. Based on this reference data, cyclic loading and unloading triaxial compression tests of soft rock under different confining pressure conditions are carried out; in the test, cyclic loading and unloading are carried out in a gradient loading manner with a loading and unloading rate of 1kN / min until the soft rock reaches its residual strength. Finally, the full stress-strain curve test data of cyclic loading and unloading of soft rock under different confining pressure conditions are obtained, as shown in the figure. Figure 3 As shown. Among them, Figure 3 (a) shows the stress-strain cyclic loading and unloading test curve of soft rock under 0MPa confining pressure. Figure 3 (b) shows the stress-strain cyclic loading and unloading test curve of soft rock under 5MPa confining pressure. Figure 3 (c) shows the stress-strain cyclic loading and unloading test curve of soft rock under 10MPa confining pressure. Figure 3 (d) shows the stress-strain cyclic loading and unloading test curve of soft rock under 20MPa confining pressure. Figure 3 (e) shows the stress-strain cyclic loading and unloading test curve of soft rock under 30MPa confining pressure.

[0072] Table 1. Conventional triaxial compression test and cyclic loading and unloading triaxial compression test conditions for soft rock

[0073]

[0074] It can be concluded from the above that this embodiment can accurately capture the mechanical response characteristics of soft rock under different confining pressure conditions by preparing soft rock sample specimens and implementing comprehensive triaxial compression and cyclic loading and unloading tests.

[0075] In one embodiment of the present disclosure, data fitting is performed based on the second data set, the third data set, and the fourth data set, respectively, including:

[0076] The ratios of the soft rock mechanical parameters, confining pressure, and plastic deviator strain in the second data set, the third data set, and the fourth data set to the corresponding reference values ​​are calculated respectively to obtain the dimensionless values ​​of the soft rock mechanical parameters, the dimensionless values ​​of the confining pressure, and the dimensionless values ​​of the plastic deviator strain;

[0077] Data fitting is performed based on the dimensionless values ​​of soft rock mechanical parameters, confining pressure, and plastic deviatoric strain.

[0078] In this embodiment, considering the different units of soft rock mechanical parameters, confining pressure, plastic deviator strain and other data,

[0079] If the corresponding soft rock mechanical parameter evolution model is established by directly taking the confining pressure or plastic deviator strain as the dependent variable and the mechanical parameters as the independent variables, there will be defects such as unclear interpretation of the dimensional physical meaning and excessively large undetermined coefficients. To solve the above problems, this embodiment performs dimensionless processing on the soft rock mechanical parameters, confining pressure and plastic deviator strain.

[0080] Specifically, the dimensionless processing method can be as follows:

[0081] (1) Definition is the strength stress ratio:

[0082]

[0083] in, represents the confining pressure, represents the uniaxial compressive strength of rock, It represents the ratio of confining pressure to the uniaxial compressive strength of rock sample and is used to describe the influence of confining pressure on the evolution of mechanical parameters of soft rock.

[0084] (2) Definition is the plastic deviator strain ratio, is the ratio of plastic deviator strain to critical plastic deviator strain, and is used to describe the influence of plastic strain factors on the evolution of mechanical parameters of soft rock.

[0085] Specifically, the critical plastic deviator strain under different confining pressures can be obtained by fitting the critical plastic deviator strain evolution model of soft rock, such as Figure 4 As shown in the figure, it is the fitting curve of the evolution law of critical plastic deviatoric strain of soft rock, and the expression of the evolution model of critical plastic deviatoric strain of soft rock is:

[0086]

[0087] in, represents the critical plastic deviatoric strain, Expressed as a natural constant The exponential function with base , represents the strength-stress ratio, , represents the confining pressure, represents the uniaxial compressive strength of rock, They are all proportional parameters, and their specific values ​​are obtained through data fitting.

[0088] At the same time, the fitting results and the values ​​of the undetermined parameters are shown in Table 2. The fitting results are expressed in terms of root mean square error (RMSE), sum of squares due to error (SSE), correlation coefficient R, R-squared (R 2 ) and determination coefficient (DC) were used for evaluation.

[0089] Table 2 Fitting results of critical plastic deviatoric strain evolution model of soft rock and values ​​of undetermined parameters

[0090]

[0091] (3) Taking elastic modulus as an example, define the mechanical parameter ratio of soft rock: It is the ratio of mechanical parameters to the mechanical parameters of soft rock in elastic stage under uniaxial conditions.

[0092] It can be concluded from the above that this embodiment performs dimensionless processing on the soft rock mechanical parameters, confining pressure, and plastic deviatoric strain in the second data set, the third data set, and the fourth data set based on the corresponding benchmark values, which is beneficial to improving the applicability of the fitting data and makes up for the defect that the dimensional physical meaning of the current evolution model cannot be explained.

[0093] In one embodiment of the present disclosure, the segmented model of soft rock mechanical parameter evolution includes a three-stage evolution model of soft rock elastic modulus;

[0094] The expression of the three-stage evolution model of soft rock elastic modulus is:

[0095]

[0096] in, represents the elastic modulus, represents the elastic modulus under uniaxial conditions, represents the strength-stress ratio, , represents the confining pressure, represents the uniaxial compressive strength of rock, represents the plastic deviatoric strain, represents the critical plastic deviatoric strain, , Indicated by natural constant The exponential function with base , They are all proportional parameters, and their specific values ​​are obtained through data fitting.

[0097] In this embodiment, according to the three-stage deformation characteristics of the soft rock stress-strain curve, mechanical parameter evolution models of the soft rock elastic deformation stage, softening deformation stage and residual deformation stage are fitted respectively.

[0098] Table 3 Fitting results of the three-stage evolution model of soft rock elastic modulus

[0099]

[0100] Table 4 Parameters of the three-stage evolution model of soft rock elastic modulus

[0101]

[0102] The fitting curve of the three-stage evolution model of soft rock elastic modulus is as follows: Figure 5 As shown. Among them, Figure 5 (a) represents the elastic deformation stage, Figure 5 (b) represents the softening deformation stage, Figure 5 (c) represents the residual deformation stage. At the same time, the fitting results and parameter values ​​are shown in Table 3 and Table 4, respectively.

[0103] The expression of the three-stage evolution model of soft rock elastic modulus is:

[0104]

[0105] in, represents the elastic modulus, represents the elastic modulus under uniaxial conditions, represents the strength-stress ratio, , represents the confining pressure, represents the uniaxial compressive strength of rock, represents the plastic deviatoric strain, represents the critical plastic deviatoric strain, , Indicated by natural constant The exponential function with base , They are all proportional parameters, and their specific values ​​are obtained through data fitting.

[0106] In one embodiment of the present disclosure, the segmented model of soft rock mechanical parameter evolution includes a three-stage evolution model of soft rock Poisson's ratio;

[0107] The expression of the three-stage evolution model of Poisson's ratio of soft rock is:

[0108]

[0109] in, represents Poisson's ratio, represents the Poisson's ratio under uniaxial conditions, represents the strength-stress ratio, , represents the confining pressure, represents the uniaxial compressive strength of rock, represents the plastic deviatoric strain, represents the critical plastic deviatoric strain, , Indicated by natural constant The exponential function with base , They are all proportional parameters, and their specific values ​​are obtained through data fitting.

[0110] In this embodiment, according to the three-stage deformation characteristics of the soft rock stress-strain curve, the mechanical parameter evolution models of the soft rock elastic deformation stage, softening deformation stage and residual deformation stage are fitted respectively. The fitting curve of the three-stage evolution model of the soft rock Poisson's ratio is as follows: Figure 6 As shown. Among them, Figure 6 (a) represents the elastic deformation stage, Figure 6 (b) represents the softening deformation stage, Figure 6 (c) represents the residual deformation stage. At the same time, the fitting results and parameter values ​​are shown in Table 5 and Table 6, respectively.

[0111] Table 5 Fitting results of the three-stage evolution model of Poisson's ratio of soft rock

[0112]

[0113] Table 6 Parameters of the three-stage evolution model of Poisson's ratio of soft rock

[0114]

[0115] The expression of the three-stage evolution model of Poisson's ratio of soft rock is:

[0116]

[0117] in, represents Poisson's ratio, represents the Poisson's ratio under uniaxial conditions, represents the strength-stress ratio, , represents the confining pressure, represents the uniaxial compressive strength of rock, represents the plastic deviatoric strain, represents the critical plastic deviatoric strain, , Expressed as a natural constant The exponential function with base , They are all proportional parameters, and their specific values ​​are obtained through data fitting.

[0118] In one embodiment of the present disclosure, the segmented model of soft rock mechanical parameter evolution includes a three-stage evolution model of soft rock friction angle;

[0119] The expression of the three-stage evolution model of soft rock friction angle is:

[0120]

[0121] in, represents the friction angle, represents the friction angle under uniaxial conditions, represents the strength-stress ratio, , represents the confining pressure, represents the uniaxial compressive strength of rock, represents the plastic deviatoric strain, represents the critical plastic deviatoric strain, , Expressed as a natural constant The exponential function with base , They are all proportional parameters, and their specific values ​​are obtained through data fitting.

[0122] In this embodiment, according to the three-stage deformation characteristics of the soft rock stress-strain curve, mechanical parameter evolution models of the soft rock elastic deformation stage, softening deformation stage and residual deformation stage are fitted respectively.

[0123] The fitting curve of the three-stage evolution model of soft rock friction angle is as follows: Figure 7 As shown. Among them, Figure 7 (a) represents the elastic deformation stage, Figure 7 (b) represents the softening deformation stage, Figure 7 (c) represents the residual deformation stage. At the same time, the fitting results and parameter values ​​are shown in Table 7 and Table 8, respectively.

[0124] The expression of the three-stage evolution model of soft rock friction angle is:

[0125]

[0126] in, represents the friction angle, represents the friction angle under uniaxial conditions, represents the strength-stress ratio, , represents the confining pressure, represents the uniaxial compressive strength of rock, represents the plastic deviatoric strain, represents the critical plastic deviatoric strain, , Indicated by natural constant The exponential function with base , They are all proportional parameters, and their specific values ​​are obtained through data fitting.

[0127] Table 7 Fitting results of the three-stage evolution model of soft rock friction angle

[0128]

[0129] Table 8 Parameters of the three-stage evolution model of soft rock friction angle

[0130]

[0131] In one embodiment of the present disclosure, the segmented model of soft rock mechanical parameter evolution includes a three-stage evolution model of soft rock cohesion;

[0132] The expression of the three-stage evolution model of soft rock cohesion is:

[0133]

[0134] in, Represents cohesion, represents the cohesion under uniaxial conditions, represents the strength-stress ratio, , represents the confining pressure, represents the uniaxial compressive strength of rock, represents the plastic deviatoric strain, represents the critical plastic deviatoric strain, , Indicated by natural constant The exponential function with base , They are all proportional parameters, and their specific values ​​are obtained through data fitting.

[0135] In this embodiment, according to the three-stage deformation characteristics of the soft rock stress-strain curve, the mechanical parameter evolution models of the soft rock elastic deformation stage, softening deformation stage and residual deformation stage are fitted respectively. The fitting curve of the three-stage evolution model of the soft rock friction angle is as follows: Figure 8 As shown. Among them, Figure 8 (a) represents the elastic deformation stage, Figure 8 (b) represents the softening deformation stage, Figure 8 (c) represents the residual deformation stage. At the same time, the fitting results and parameter values ​​are shown in Table 9 and Table 10, respectively.

[0136] Table 9 Fitting results of the three-stage evolution model of soft rock cohesion

[0137]

[0138] Table 10 Parameters of the three-stage evolution model of soft rock cohesion

[0139]

[0140] The expression of the three-stage evolution model of soft rock cohesion is:

[0141]

[0142] in, Represents cohesion, represents the cohesion under uniaxial conditions, represents the strength-stress ratio, , represents the confining pressure, represents the uniaxial compressive strength of rock, represents the plastic deviatoric strain, represents the critical plastic deviatoric strain, , Indicated by natural constant The exponential function with base , They are all proportional parameters, and their specific values ​​are obtained through data fitting.

[0143] It can be concluded from the above that the segmented models of soft rock mechanical parameter evolution proposed in this embodiment are all dimensionless models, which make up for the defect that the physical meaning of the dimension of the current evolution model cannot be explained. At the same time, the soft rock mechanical parameter evolution model under the influence of the coupling of confining pressure and plastic strain in this embodiment can systematically characterize the evolution process of mechanical parameters of soft rock in different deformation stages (elastic deformation stage, softening deformation stage, residual deformation stage).

[0144] Corresponding to the method for constructing a segmented model of the evolution of soft rock mechanical parameters under the influence of multiple factors in the above embodiment, Fig. 9 This is a structural block diagram of a device for constructing a segmented model of soft rock mechanical parameter evolution under the influence of multiple factors provided by an embodiment of the present disclosure. For ease of explanation, only the parts related to the embodiment of the present disclosure are shown. Fig. 9 The device 20 for constructing a segmented model of the evolution of mechanical parameters of soft rock under the influence of multiple factors includes: a data calculation module 21, a mapping construction module 22, a data segmentation module 23 and a model construction module 24.

[0145] The data calculation module 21 is used to obtain the soft rock mechanical parameters, plastic deviator strain and critical plastic deviator strain under different confining pressures based on the soft rock mechanical stress-strain relationship data under different confining pressures;

[0146] A mapping construction module 22 is used to establish a mapping relationship between soft rock mechanical parameters and confining pressure and plastic deviatoric strain based on the soft rock mechanical parameters and plastic deviatoric strain under different confining pressures to obtain a first data set;

[0147] A data segmentation module 23 is used to segment the first data set based on the relative size of the critical plastic deviator strain of the soft rock and the plastic deviator strain to obtain a second data set in the elastic deformation stage, a third data set in the softening deformation stage, and a fourth data set in the residual deformation stage;

[0148] The model building module 24 is used to perform data fitting based on the second data set, the third data set and the fourth data set to obtain a segmented model of the evolution of soft rock mechanical parameters.

[0149] In one embodiment of the present disclosure, the model building module 24 is specifically used to:

[0150] Based on the soft rock mechanical parameters in the second data set and the corresponding confining pressure, data fitting is performed to obtain a soft rock mechanical parameter evolution model in the elastic deformation stage;

[0151] Based on the soft rock mechanical parameters in the third data set and the corresponding confining pressure and plastic deviatoric strain, data fitting is performed to obtain the soft rock mechanical parameter evolution model in the softening deformation stage;

[0152] Based on the soft rock mechanical parameters in the fourth data set and the corresponding confining pressure, data fitting is performed to obtain the soft rock mechanical parameter evolution model in the residual deformation stage;

[0153] The soft rock mechanical parameter evolution model in the elastic deformation stage, the soft rock mechanical parameter evolution model in the softening deformation stage and the soft rock mechanical parameter evolution model in the residual deformation stage are determined as the soft rock mechanical parameter evolution segmented model.

[0154] In one embodiment of the present disclosure, the device 20 for constructing a segmented model of soft rock mechanical parameter evolution under the influence of multiple factors further includes: a data determination module;

[0155] A data determination module is used to prepare soft rock sample specimens;

[0156] Conventional triaxial compression tests and cyclic loading and unloading triaxial compression tests were carried out on soft rock specimens to determine the mechanical stress-strain relationship data of soft rock under different confining pressures.

[0157] In one embodiment of the present disclosure, the model building module 24 is specifically used to:

[0158] The ratios of the soft rock mechanical parameters, confining pressure, and plastic deviator strain in the second data set, the third data set, and the fourth data set to the corresponding reference values ​​are calculated respectively to obtain the dimensionless values ​​of the soft rock mechanical parameters, the dimensionless values ​​of the confining pressure, and the dimensionless values ​​of the plastic deviator strain;

[0159] Data fitting is performed based on the second data set, the third data set and the fourth data set respectively, including: data fitting is performed based on dimensionless values ​​of soft rock mechanical parameters, dimensionless values ​​of confining pressure and dimensionless values ​​of plastic deviatoric strain.

[0160] In one embodiment of the present disclosure, the model building module 24 is specifically used to build a three-stage evolution model of the elastic modulus of soft rock. The expression of the three-stage evolution model of the elastic modulus of soft rock is:

[0161]

[0162] in, represents the elastic modulus, represents the elastic modulus under uniaxial conditions, represents the strength-stress ratio, , represents the confining pressure, represents the uniaxial compressive strength of rock, represents the plastic deviatoric strain, represents the critical plastic deviatoric strain, , Expressed as a natural constant The exponential function with base , They are all proportional parameters, and their specific values ​​are obtained through data fitting.

[0163] In one embodiment of the present disclosure, the model building module 24 is specifically used to build a three-stage evolution model of the Poisson's ratio of soft rock. The expression of the three-stage evolution model of the Poisson's ratio of soft rock is:

[0164]

[0165] in, represents Poisson's ratio, represents the Poisson's ratio under uniaxial conditions, represents the strength-stress ratio, , represents the confining pressure, represents the uniaxial compressive strength of rock, represents the plastic deviatoric strain, represents the critical plastic deviatoric strain, , Expressed as a natural constant The exponential function with base , They are all proportional parameters, and their specific values ​​are obtained through data fitting.

[0166] In one embodiment of the present disclosure, the model building module 24 is specifically used to build a three-stage evolution model of the soft rock friction angle. The expression of the three-stage evolution model of the soft rock friction angle is:

[0167]

[0168] in, represents the friction angle, represents the friction angle under uniaxial conditions, represents the strength-stress ratio, , represents the confining pressure, represents the uniaxial compressive strength of rock, represents the plastic deviatoric strain, represents the critical plastic deviatoric strain, , Expressed as a natural constant The exponential function with base , They are all proportional parameters, and their specific values ​​are obtained through data fitting.

[0169] In one embodiment of the present disclosure, the model building module 24 is specifically used to build a three-stage evolution model of soft rock cohesion. The expression of the three-stage evolution model of soft rock cohesion is:

[0170]

[0171] in, Represents cohesion, represents the cohesion under uniaxial conditions, represents the strength-stress ratio, , represents the confining pressure, represents the uniaxial compressive strength of rock, represents the plastic deviatoric strain, represents the critical plastic deviatoric strain, , Expressed as a natural constant The exponential function with base , They are all proportional parameters, and their specific values ​​are obtained through data fitting.

[0172] See also Fig.10 , Fig.10 A schematic block diagram of an electronic device provided by an embodiment of the present disclosure. Fig.10 The electronic device 300 in the embodiment shown may include: one or more processors 301, one or more input devices 302, one or more output devices 303 and one or more memories 304. The processors 301, input devices 302, output devices 303 and memories 304 communicate with each other via a communication bus 305. The memory 304 is used to store computer programs, which include program instructions. The processor 301 is used to execute the program instructions stored in the memory 304. The processor 301 is configured to call the program instructions to execute the functions of each module / unit in the above-mentioned device embodiments, such as Fig. 9 The functions of modules 21 to 24 are shown.

[0173] It should be understood that in the embodiments of the present disclosure, the processor 301 may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0174] The input device 302 may include a touch panel, a fingerprint collection sensor (for collecting the user's fingerprint information and fingerprint direction information), a microphone, etc., and the output device 303 may include a display (LCD, etc.), a speaker, etc.

[0175] The memory 304 may include a read-only memory and a random access memory, and provide instructions and data to the processor 301. A portion of the memory 304 may also include a non-volatile random access memory. For example, the memory 304 may also store information about the device type.

[0176] In a specific implementation, the processor 301, input device 302, and output device 303 described in the embodiments of the present disclosure can execute the implementation methods described in the first and second embodiments of the method for constructing a segmented model of the evolution of soft rock mechanical parameters under the influence of multiple factors provided in the embodiments of the present disclosure, and can also execute the implementation methods of the electronic device described in the embodiments of the present disclosure, which will not be repeated here.

[0177] In another embodiment of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by the processor, all or part of the processes in the above-mentioned embodiment method are implemented, and the computer program can also be completed by instructing the relevant hardware through the computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor, the steps of each of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0178] The computer-readable storage medium may be an internal storage unit of the electronic device of any of the aforementioned embodiments, such as a hard disk or memory of the electronic device. The computer-readable storage medium may also be an external storage device of the electronic device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device. Furthermore, the computer-readable storage medium may also include both an internal storage unit of the electronic device and an external storage device. The computer-readable storage medium is used to store computer programs and other programs and data required by the electronic device. The computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.

[0179] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this disclosure.

[0180] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the electronic devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0181] In the several embodiments provided in the present application, it should be understood that the disclosed electronic devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces or units, or it can be an electrical, mechanical or other form of connection.

[0182] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present disclosure.

[0183] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0184] The above are only specific embodiments of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present disclosure, and these modifications or replacements should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

[0185] The above are only specific embodiments of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present disclosure, and these modifications or replacements should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A method for constructing a segmented model of soft rock mechanical parameter evolution under the influence of multiple factors, characterized in that: include: Based on the mechanical stress-strain relationship data of soft rock under different confining pressures, the mechanical parameters, plastic deviator strain and critical plastic deviator strain of soft rock under different confining pressures are obtained. Based on the mechanical parameters and plastic deviatoric strain of soft rock under different confining pressures, a mapping relationship between the mechanical parameters of soft rock and confining pressure and plastic deviatoric strain is established to obtain a first data set; Segmenting the first data set based on the relative size of the critical plastic deviator strain of soft rock and the plastic deviator strain to obtain a second data set in the elastic deformation stage, a third data set in the softening deformation stage, and a fourth data set in the residual deformation stage; Performing data fitting based on the second data set, the third data set, and the fourth data set respectively to obtain a segmented model of soft rock mechanical parameter evolution; The soft rock mechanical parameter evolution segmented model includes a soft rock elastic modulus three-stage evolution model; The expression of the three-stage evolution model of the soft rock elastic modulus is: in, represents the elastic modulus, represents the elastic modulus under uniaxial conditions, represents the strength-stress ratio, , represents the confining pressure, represents the uniaxial compressive strength of rock, represents the plastic deviatoric strain, represents the critical plastic deviatoric strain, , Indicated by natural constant The exponential function with base , They are all proportional parameters, and their specific values ​​are obtained through data fitting.

2. The method for constructing a segmented model of soft rock mechanical parameter evolution under the influence of multiple factors as claimed in claim 1, characterized in that: The step of performing data fitting based on the second data set, the third data set and the fourth data set to obtain a segmented model of soft rock mechanical parameter evolution includes: Performing data fitting based on the soft rock mechanical parameters in the second data set and the corresponding confining pressure to obtain a soft rock mechanical parameter evolution model in the elastic deformation stage; Performing data fitting based on the soft rock mechanical parameters in the third data set and the corresponding confining pressure and plastic deviatoric strain to obtain a soft rock mechanical parameter evolution model in the softening deformation stage; Performing data fitting based on the soft rock mechanical parameters in the fourth data set and the corresponding confining pressure to obtain a soft rock mechanical parameter evolution model in the residual deformation stage; The soft rock mechanical parameter evolution model in the elastic deformation stage, the soft rock mechanical parameter evolution model in the softening deformation stage and the soft rock mechanical parameter evolution model in the residual deformation stage are determined as a soft rock mechanical parameter evolution segmented model.

3. The method for constructing a segmented model of soft rock mechanical parameter evolution under the influence of multiple factors as claimed in claim 1, characterized in that: Also includes: Making soft rock sample specimens; Conventional triaxial compression tests and cyclic loading and unloading triaxial compression tests are carried out on the soft rock sample specimens to determine the mechanical stress-strain relationship data of the soft rock under different confining pressures.

4. The method for constructing a segmented model of soft rock mechanical parameter evolution under the influence of multiple factors as claimed in claim 1, characterized in that: The performing data fitting based on the second data set, the third data set and the fourth data set respectively comprises: Respectively calculating the ratios of the soft rock mechanical parameters, confining pressure, and plastic deviator strain in the second data set, the third data set, and the fourth data set to the corresponding reference values ​​to obtain dimensionless values ​​of the soft rock mechanical parameters, the dimensionless value of the confining pressure, and the dimensionless value of the plastic deviator strain; Data fitting is performed based on the dimensionless values ​​of the soft rock mechanical parameters, the dimensionless value of the confining pressure, and the dimensionless value of the plastic deviatoric strain.

5. The method for constructing a segmented model of soft rock mechanical parameter evolution under the influence of multiple factors as claimed in claim 1, characterized in that: The soft rock mechanical parameter evolution segmented model includes a soft rock Poisson's ratio three-stage evolution model; The expression of the three-stage evolution model of the soft rock Poisson's ratio is: in, represents Poisson's ratio, represents the Poisson's ratio under uniaxial conditions, represents the strength-stress ratio, , represents the confining pressure, represents the uniaxial compressive strength of rock, represents the plastic deviatoric strain, represents the critical plastic deviatoric strain, , Indicated by natural constant The exponential function with base , They are all proportional parameters, and their specific values ​​are obtained through data fitting.

6. The method for constructing a segmented model of soft rock mechanical parameter evolution under the influence of multiple factors as claimed in claim 1, characterized in that: The segmented model for the evolution of soft rock mechanical parameters includes a three-stage evolution model for soft rock friction angle; The expression of the three-stage evolution model of soft rock friction angle is: in, represents the friction angle, represents the friction angle under uniaxial conditions, represents the strength-stress ratio, , represents the confining pressure, represents the uniaxial compressive strength of rock, represents the plastic deviatoric strain, represents the critical plastic deviatoric strain, , Indicated by natural constant The exponential function with base , They are all proportional parameters, and their specific values ​​are obtained through data fitting.

7. The method for constructing a segmented model of soft rock mechanical parameter evolution under the influence of multiple factors as claimed in claim 1, characterized in that: The segmented model of soft rock mechanical parameter evolution includes a three-stage evolution model of soft rock cohesion; The expression of the three-stage evolution model of soft rock cohesion is: in, Represents cohesion, represents the cohesion under uniaxial conditions, represents the strength-stress ratio, , represents the confining pressure, represents the uniaxial compressive strength of rock, represents the plastic deviatoric strain, represents the critical plastic deviatoric strain, , Indicated by natural constant The exponential function with base , They are all proportional parameters, and their specific values ​​are obtained through data fitting.

8. A device for constructing a segmented model of soft rock mechanical parameter evolution under the influence of multiple factors, characterized in that: include: A data calculation module is used to obtain the mechanical parameters, plastic deviatoric strain and critical plastic deviatoric strain of soft rock under different confining pressures based on the mechanical stress-strain relationship data of soft rock under different confining pressures; A mapping construction module is used to establish a mapping relationship between the soft rock mechanical parameters and the confining pressure and the plastic deviatoric strain based on the soft rock mechanical parameters and the plastic deviatoric strain under different confining pressures to obtain a first data set; A data segmentation module, for segmenting the first data set based on the relative size of the critical plastic deviator strain of soft rock and the plastic deviator strain, to obtain a second data set in the elastic deformation stage, a third data set in the softening deformation stage, and a fourth data set in the residual deformation stage; A model building module, used for performing data fitting based on the second data set, the third data set and the fourth data set respectively, to obtain a segmented model of soft rock mechanical parameter evolution; The model building module is specifically used to build a three-stage evolution model of the elastic modulus of soft rock. The expression of the three-stage evolution model of the elastic modulus of soft rock is: in, represents the elastic modulus, represents the elastic modulus under uniaxial conditions, represents the strength-stress ratio, , represents the confining pressure, represents the uniaxial compressive strength of rock, represents the plastic deviatoric strain, represents the critical plastic deviatoric strain, , Indicated by natural constant The exponential function with base , They are all proportional parameters, and their specific values ​​are obtained through data fitting.

9. The device for constructing a segmented model of soft rock mechanical parameter evolution under the influence of multiple factors as claimed in claim 8, characterized in that: The model building module is specifically used for: Performing data fitting based on the soft rock mechanical parameters in the second data set and the corresponding confining pressure to obtain a soft rock mechanical parameter evolution model in the elastic deformation stage; Performing data fitting based on the soft rock mechanical parameters in the third data set and the corresponding confining pressure and plastic deviatoric strain to obtain a soft rock mechanical parameter evolution model in the softening deformation stage; Performing data fitting based on the soft rock mechanical parameters in the fourth data set and the corresponding confining pressure to obtain a soft rock mechanical parameter evolution model in the residual deformation stage; The soft rock mechanical parameter evolution model in the elastic deformation stage, the soft rock mechanical parameter evolution model in the softening deformation stage and the soft rock mechanical parameter evolution model in the residual deformation stage are determined as a soft rock mechanical parameter evolution segmented model.

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