Semi-quantitative evaluation method, device and storage medium for bias of tunnel portal section

Abstract

The application provides a semi-quantitative evaluation method and device for tunnel portal segment bias and a storage medium, and relates to the technical field of tunnel bias calculation. The method comprises the following steps: calculating and determining bias coefficients of a plurality of tunnel portal segments; determining a plurality of bias grades based on the numerical values of the plurality of bias coefficients; determining the influence of a plurality of bias influencing factors on the bias coefficients under each bias grade based on numerical simulation, so as to determine one or more bias influencing factors with the greatest influence on the bias coefficients as target influencing factors; obtaining one or more target influencing factors of a target tunnel portal segment, and generating a semi-quantitative evaluation result for the target tunnel portal segment based on the target influencing factors. The method can convert complex mechanical behavior into a quantifiable evaluation benchmark by introducing a bias coefficient method core index, and can greatly improve the evaluation efficiency of the tunnel portal segment bias while ensuring a certain precision.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of tunnel bias calculation, in particular to a semi-quantitative evaluation method, device and storage medium for tunnel portal section bias. BACKGROUND

[0002] In the field of tunnel engineering, accurately evaluating the bias condition of the portal section is a key link to ensure construction and operation safety. The traditional evaluation method usually has the problem of low evaluation efficiency, which is mainly due to its inherent analysis mode.

[0003] The traditional technical method often relies on detailed quantitative calculation and mechanical analysis of all geological and topographic influencing factors. This method attempts to accurately simulate the mechanical response of the tunnel by constructing a complex numerical model, considering the interaction of multiple parameters such as slope gradient, overburden thickness, and rock mass properties. However, this all-in-one analysis approach results in a very complex calculation model that requires a large number of input rock and soil parameters, and the data acquisition and processing process itself is very time-consuming. In addition, due to the concealment and uncertainty of actual engineering geological conditions, it is extremely difficult to obtain accurate values for all parameters, which makes comprehensive quantitative analysis either difficult due to insufficient data or affects the reliability of the results due to model simplification.

[0004] Therefore, in engineering practice, in order to cope with the difficulties of comprehensive analysis, the evaluation work often relies too much on the personal experience of engineers for qualitative judgment. This experience-based mode, although direct, lacks systematicness and unified standards, and the conclusions drawn by different engineers may differ greatly, making it difficult to form objective and reproducible evaluation results, thus having obvious deficiencies in efficiency and objectivity. SUMMARY

[0005] The present application provides a semi-quantitative evaluation method, device and storage medium for tunnel portal section bias, which converts complex mechanical behavior into a quantifiable evaluation benchmark by introducing the core index of bias coefficient method. In actual application, only a few key factors of the target tunnel portal section need to be obtained to generate a semi-quantitative evaluation result, which can greatly improve the evaluation efficiency of the tunnel portal section bias while ensuring a certain accuracy.

[0006] In a first aspect, the present application provides a semi-quantitative evaluation method for bias of a tunnel portal section, comprising: calculating and determining bias coefficients of a plurality of tunnel portal sections; wherein the bias coefficient is obtained based on a ratio of stress difference of the tunnel on both sides to the average stress of the surrounding rock on both sides; determining a plurality of bias levels based on the numerical values of the bias coefficients; determining the influence of a plurality of bias influencing factors on the bias coefficient under each bias level based on numerical simulation, to determine one or more bias influencing factors with the greatest influence on the bias coefficient as target influencing factors; obtaining one or more target influencing factors of a target tunnel portal section, and generating a semi-quantitative evaluation result for the target tunnel portal section based on the target influencing factors.

[0007] According to an embodiment of the present application, determining a plurality of bias levels based on the numerical values of the bias coefficients comprises: obtaining a plurality of engineering critical conditions of the tunnel portal section, and establishing a tunnel model corresponding to each engineering critical condition; performing excavation simulation on each tunnel model based on numerical simulation, and calculating a plurality of critical bias coefficients; taking the critical bias coefficient as a critical value, and determining a plurality of bias levels.

[0008] According to an embodiment of the present application, the tunnel portal section is located in a soil slope or a rock slope; in the case that the tunnel portal section is located in a soil slope, the bias influencing factors include slope body slope, tunnel buried depth and tunnel surrounding rock stiffness; in the case that the tunnel portal section is a rock slope, the bias influencing factors include slope body slope, tunnel buried depth, structural plane inclination, structural plane strength, rock thickness and position of weak structural plane.

[0009] According to an embodiment of the present application, determining the influence of a plurality of bias influencing factors on the bias coefficient under each bias level based on numerical simulation, to determine one or more bias influencing factors with the greatest influence on the bias coefficient as target influencing factors, comprises: in the case that the tunnel portal section is located in a soil slope, performing numerical simulation on the bias influencing factors based on the finite difference method, to determine one or more bias influencing factors with the greatest influence on the bias coefficient as the target influencing factors; in the case that the tunnel portal section is located in a rock slope, performing numerical simulation on the bias influencing factors based on the discrete element method, to determine one or more bias influencing factors with the greatest influence on the bias coefficient as the target influencing factors.

[0010] According to an embodiment of the present application, the target influencing factors include slope body slope and tunnel buried depth.

[0011] According to one embodiment of the present application, the bias level includes a first level, a second level and a third level, the first level represents that the bias coefficient is less than 0.3, the second level represents that the bias coefficient is greater than or equal to 0.3 and less than 0.5, and the third level represents that the bias coefficient is greater than or equal to 0.5.

[0012] According to one embodiment of the present application, the obtaining one or more target influence factors of the target tunnel portal section, and generating a semi-quantitative evaluation result of the target tunnel portal section based on the target influence factors, comprises: generating a semi-quantitative evaluation table of the target tunnel portal section based on the slope gradient and the tunnel buried depth; wherein the semi-quantitative evaluation table includes a first identification mark, a second identification mark and a third identification mark, the first identification mark represents that the bias state of the tunnel is in the first level, the second identification mark represents that the bias state of the tunnel is in the second level, and the third identification mark represents that the bias state of the tunnel is in the third level.

[0013] According to one embodiment of the present application, the bias coefficient is a bias coefficient at a tunnel arch foot.

[0014] In a second aspect, the present application further provides a computer device, which comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the method of the above-mentioned embodiments when executing the computer program.

[0015] In a third aspect, the present application further provides a computer readable storage medium, which stores a computer program, and the computer program implements the method of the above-mentioned embodiments when executed by a processor.

[0016] Compared with the prior art, the present application has the beneficial effects that: by introducing the bias coefficient method core index, the complex mechanical behavior is converted into a quantifiable evaluation benchmark, the bias level is divided according to multiple coefficient values, and a grading system from slight to severe is established, thereby providing a classification basis for different severity of bias. Further, by means of numerical simulation, the action strength of each influence factor on the bias coefficient under different levels is analyzed, thereby screening out key target influence factors, and finally in actual application, only a few key factors of the target tunnel portal section need to be obtained, and a semi-quantitative evaluation result can be generated. This method can avoid tedious full-parameter calculation, and can greatly improve the evaluation efficiency of the tunnel portal section bias while ensuring a certain accuracy. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 The figure shows the steps of the semi-quantitative evaluation method of the tunnel portal section bias provided by the embodiments of the present application.

[0018] Figure 2 Numerical calculation model schematic diagram provided for the embodiment of the present application needs to design the shallow buried bias tunnel.

[0019] Figure 3 Numerical calculation model schematic diagram provided for the embodiment of the present application needs to reinforce the bias tunnel of stratum.

[0020] Figure 4 Schematic diagram of tunnel bias analysis point provided for the embodiment of the present application.

[0021] Figure 5 Moor-Coulomb yield criterion schematic diagram in FLAC3D shown for the embodiment of the present application.

[0022] Figure 6 Numerical calculation model schematic diagram provided for the embodiment of the present application of different slope body gradient.

[0023] Figure 7 Maximum compressive stress nephogram of tunnel surrounding rock under different slope gradient provided for the embodiment of the present application.

[0024] Figure 8 Slope body gradient and bias coefficient change curve schematic diagram provided for the embodiment of the present application.

[0025] Figure 9 Numerical calculation model schematic diagram provided for the embodiment of the present application of different tunnel buried depth.

[0026] Figure 10 Maximum compressive stress nephogram of tunnel surrounding rock under different buried depth provided for the embodiment of the present application.

[0027] Figure 11 Tunnel buried depth and bias coefficient change curve schematic diagram provided for the embodiment of the present application.

[0028] Figure 12 Numerical calculation model schematic diagram provided for the embodiment of the present application of tunnel surrounding rock stiffness.

[0029] Figure 13 Maximum compressive stress nephogram of tunnel surrounding rock under different surrounding rock elastic modulus provided for the embodiment of the present application.

[0030] Figure 14 Tunnel surrounding rock stiffness and bias coefficient change curve schematic diagram provided for the embodiment of the present application.

[0031] Figure 15 Numerical calculation model schematic diagram provided for the embodiment of the present application of different slope body gradient under rock slope.

[0032] Figure 16 Maximum compressive stress nephogram of tunnel surrounding rock under different slope body gradient under rock slope provided for the embodiment of the present application.

[0033] Figure 17 A variation curve diagram of a slope gradient and a bias coefficient of a downhill body of a rock slope is provided for an embodiment of the present application.

[0034] Figure 18 A numerical calculation model diagram of different tunnel depths under a rock slope is provided for an embodiment of the present application.

[0035] Figure 19 A maximum compressive stress nephogram of tunnel surrounding rock of different tunnel depths under a rock slope is provided for an embodiment of the present application.

[0036] Figure 20 A variation curve diagram of a tunnel depth and a bias coefficient under a rock slope is provided for an embodiment of the present application.

[0037] Figure 21 A numerical calculation model diagram of different structural plane inclinations under a rock slope is provided for an embodiment of the present application.

[0038] Figure 22 A maximum compressive stress nephogram of tunnel surrounding rock of different structural plane inclinations under a rock slope is provided for an embodiment of the present application.

[0039] Figure 23 A variation curve diagram of a structural plane inclination and a bias coefficient under a rock slope is provided for an embodiment of the present application.

[0040] Figure 24 A numerical calculation model diagram of a structural plane strength under a rock slope is provided for an embodiment of the present application.

[0041] Figure 25 A maximum compressive stress nephogram of tunnel surrounding rock of different structural plane internal friction angles under a rock slope is provided for an embodiment of the present application.

[0042] Figure 26 A variation curve diagram of a structural plane internal friction angle and a bias coefficient under a rock slope is provided for an embodiment of the present application.

[0043] Figure 27 A numerical calculation model diagram of different rock layer thicknesses under a rock slope is provided for an embodiment of the present application.

[0044] Figure 28 A maximum compressive stress nephogram of tunnel surrounding rock of different rock layer thicknesses under a rock slope is provided for an embodiment of the present application.

[0045] Figure 29 A variation curve diagram of a rock layer thickness and a bias coefficient under a rock slope is provided for an embodiment of the present application.

[0046] Figure 30A numerical calculation model diagram provided by the embodiment of the present application for different positions of soft structural planes under a rock slope.

[0047] Figure 31 A variation curve diagram of a soft structural plane and a biasing coefficient provided by the embodiment of the present application under a rock slope.

[0048] Figure 32 A stress distribution nephogram before tunnel excavation provided by the embodiment of the present application under a rock slope.

[0049] Figure 33 A slope displacement nephogram after tunnel excavation provided by the embodiment of the present application.

[0050] Figure 34 A biasing deformation trend diagram after tunnel excavation provided by the embodiment of the present application.

[0051] Figure 35 A variation curve diagram of a biasing coefficient at an arch spring under different tunnel depths and slopes provided by the embodiment of the present application under a soil slope.

[0052] Figure 36 A qualitative judgment diagram of a biasing degree of a tunnel under different depth and slope combinations provided by the embodiment of the present application under a soil surrounding rock.

[0053] Figure 37 A variation curve diagram of an arch spring biasing coefficient with slope changes under different depth conditions provided by the embodiment of the present application under a rock slope.

[0054] Figure 38 A qualitative judgment diagram of a biasing degree of a tunnel under different depth and slope combinations provided by the embodiment of the present application under a rock slope. DETAILED DESCRIPTION

[0055] The present application will be further described in detail below in combination with test examples and specific embodiments. However, this should not be understood as limiting the scope of the above-mentioned subject matter of the present application to the following examples only, and any technology realized based on the content of the present application falls within the scope of protection of the present application.

[0056] Please refer to Figure 1 , Figure 1 A step diagram of a semi-quantitative evaluation method of biasing of a tunnel portal section provided by the embodiment of the present application. The semi-quantitative evaluation method of biasing of the tunnel portal section can include:

[0057] S1, calculating and determining biasing coefficients of a plurality of tunnel portal sections.

[0058] S2, determining a plurality of biasing grades based on the numerical values of the plurality of biasing coefficients.

[0059] S3, determining the influence of the plurality of bias influence factors on the bias coefficient under each bias level based on numerical simulation to determine one or more bias influence factors with the greatest influence on the bias coefficient as target influence factors.

[0060] S4, obtaining one or more target influence factors of the target tunnel portal section, and generating a semi-quantitative evaluation result of the target tunnel portal section based on the target influence factors.

[0061] In the embodiments of the present application, the bias coefficient refers to a dimensionless index for quantifying the degree of unevenness of the bias load borne by the tunnel structure, i.e., the numerical result obtained through a specific calculation formula, which is obtained based on the ratio of the stress difference of the left and right surrounding rocks of the tunnel to the average stress of the surrounding rocks on both sides. Specifically, the calculation formula of the bias coefficient is:

[0062]

[0063] wherein, C is the bias coefficient, is the deep side pressure stress of the tunnel surrounding rock on the same horizontal line, is the shallow side pressure stress of the tunnel surrounding rock on the same horizontal line. The bias coefficient can describe the unevenness of the stress of the surrounding rocks on both sides of the tunnel on the same horizontal line, and the value range is 0-2. The larger the value, the more serious the bias of the tunnel. When the bias coefficient is 0, at this time, the stress on both sides of the tunnel is uniform, and there is no bias influence; when the bias coefficient is 2, at this time, the tunnel belongs to the limit bias state.

[0064] The bias level refers to a series of discrete bias degree intervals based on a large number of numerical simulation calculation results, i.e., the bias coefficient is divided into different severity levels according to the numerical range, such as "slight bias", "moderate bias" and "serious bias", etc., and each level corresponds to different engineering treatment measures requirements. Specifically, the present application can obtain a large number of typical engineering conditions or specification critical models. Through statistical analysis of the data set and according to the engineering significance, the critical threshold for dividing the bias degree is set, and finally a grading system is established to map the continuous coefficient value to a limited number of discrete severity levels.

[0065] The bias influencing factor refers to various engineering geological and geometric parameters that may affect the numerical value of the bias coefficient in numerical simulation research, that is, a series of variables such as slope gradient, tunnel depth, tunnel surrounding rock stiffness, structural plane inclination, structural plane strength, rock thickness, and position of weak structural plane. The target influencing factor is one or more key parameters that are selected from the numerous bias influencing factors through systematic numerical simulation analysis and have the most significant impact on the bias coefficient. In determining the target influencing factor, the numerical simulation software such as FLAC3D and 3DEC can be used to change one influencing factor (such as the slope gradient from 10 degrees to 50 degrees) while keeping other parameters fixed, and observe and record the change trend and grade of the bias coefficient caused by the factor at different levels. By comparing the sensitivity and change amplitude of all factors at different levels, the most influential parameter or parameters can be identified as the target influencing factor, such as using tunnel depth as the target influencing factor, or using slope gradient and tunnel depth as the target influencing factors.

[0066] After determining the target influencing factor, the key target influencing factor data of a specific tunnel portal project to be evaluated can be investigated or obtained, such as obtaining tunnel depth data or slope gradient and tunnel depth data, and then querying the semi-quantitative evaluation table constructed by the research results in step S3 (the table uses slope and depth as row and column indexes to directly give the corresponding bias grade), to quickly obtain a graded evaluation result of the bias degree of the tunnel portal with clear engineering guidance significance, thereby quickly completing the semi-quantitative evaluation.

[0067] The following is an embodiment of the present application, which determines a plurality of bias grades based on a plurality of bias coefficients.

[0068] The step of determining a plurality of bias grades based on a plurality of bias coefficients can include obtaining a plurality of engineering critical conditions of a tunnel portal section, establishing a tunnel model corresponding to each engineering critical condition; performing excavation simulation on each tunnel model based on numerical simulation, and calculating a plurality of critical bias coefficients; and determining a plurality of bias grades based on the critical bias coefficients as critical values.

[0069] Please refer to Table 1, the values listed in Table 1 are the arch shoulder covering layer thicknesses that need to be designed as shallow bias tunnels. When the ground is inclined and the arch shoulder covering layer thickness is less than the value listed in Table 1, it should be designed as a shallow bias tunnel. Several examples are selected to establish a calculation model, as shown in Figure 2 .

[0070] Table 1 Limit value of arch shoulder covering layer thickness that needs to be designed as a shallow bias tunnel (m)

[0071]

[0072] Figure 2 The numerical calculation model schematic diagram provided by the embodiment of the present application needs to be designed for the shallow buried bias tunnel. Figure 2 The model shown in Table 1 is a set of a series of representative models established for a plurality of critical working conditions, and each model corresponds to a specific condition in Table 1. For example, the three models (a), (b) and (c) simulate the critical state of the arch shoulder covering layer with a thickness of 20, 15 and 10 meters respectively under the slope of 1:0.75, 1:1.25 and 1:2 of the III-grade surrounding rock. Other models also correspond to the critical state of a plurality of slopes under the IV or V-grade surrounding rock grade. From the shape of the model, it can be directly seen that the terrain surface is set as an inclined slope with a constant slope rate, thereby simulating the real bias terrain. The tunnel structure is embedded in the mountain, and the depth of the arch shoulder position is controlled at the critical thickness value specified in Table 1. The model is established by considering the physical and mechanical parameters of the surrounding rock, which strictly correspond to the surrounding rock grade in the table, ensuring the authenticity of the simulation. The purpose of the study is to simulate the tunnel excavation of these models in the critical state of design, to calculate the stress of the key parts such as the tunnel arch foot after excavation, and to finally obtain a series of corresponding critical bias coefficients by substituting the bias coefficient calculation formula. These coefficient values are the core basis for subsequent bias grade demarcation.

[0073] The values listed in Table 2 are the thickness limit values of the stratum above the tunnel vault that needs to be reinforced. When the ground is inclined and the thickness of the stratum above the vault is less than the value listed in Table 1, engineering measures should be taken to reinforce the surface mountain, which provides a clear quantitative standard for determining when engineering reinforcement measures must be taken for the surface mountain under the bias terrain. Several examples are selected to establish a calculation model as shown in Figure 3 .

[0074] Table 2 Thickness limit value of stratum above tunnel vault that needs to be reinforced (m)

[0075]

[0076] Figure 3 The numerical calculation model schematic diagram provided by the embodiment of the present application needs to be designed for the shallow buried bias tunnel. Figure 3The models shown in the table 2 are a set of specific critical working conditions. For example, the two models (a) and (b) simulate the limit state of the III-grade surrounding rock under the slope of 1:1.25 and 1:1.5, and the stratum thickness above the arch crown is 4 meters and 3 meters respectively. The other models are also respectively corresponding to the critical state of the stratum thickness above the arch crown under the IV-grade or V-grade surrounding rock grade. From the construction of the model, it can be clearly seen that the terrain surface is set as an inclined slope with a constant slope rate, thereby simulating the real bias terrain. The tunnel structure is embedded in the mountain, and the thickness of the rock-soil body directly above the arch crown is controlled at the critical thickness value specified in table 2, which is usually much smaller than the arch shoulder covering layer thickness limit value in table 1, indicating that the state of the model is more dangerous.

[0077] Please refer to Figure 4 , Figure 4 The tunnel bias analysis point schematic diagram provided by the embodiment of the application. The applicant found in the research process that under the combination of the ground slope and the buried depth, the arch foot bias coefficient is the largest, indicating that the bias at the arch foot is the most serious, and the bias degree at the arch foot should be given priority in the actual highway bias tunnel. In the calculation of the bias coefficients of the arch foot, the arch waist and the arch shoulder, since the calculation adopts the stratum structure mode and considers the coordinated deformation of the surrounding rock and the lining system, the deformation at the arch foot is the smallest after being subjected to the bias load, the stress release is the least, and the change rule of the bias coefficient at the arch foot is the most representative, which can reflect the bias degree of the whole tunnel. Therefore, the stress at the arch foot is taken for calculation in the calculation. The parameters and results used in the calculation of these models are shown in tables 3 to 5.

[0078] Table 3: Physical and mechanical parameters used in the calculation of each grade of surrounding rock

[0079]

[0080] Table 4: Bias coefficient calculation results of the bias tunnel that needs to be designed

[0081]

[0082] Table 5: Bias coefficient calculation results of the stratum that needs to be reinforced

[0083]

[0084] Through the tunnel excavation simulation of these working conditions in the "must be reinforced" critical state, the stress of the key parts of the tunnel after excavation is calculated, and finally a series of corresponding critical bias coefficients are obtained. As shown in the calculation results in table 5, these coefficient values (such as the minimum value is about 0.56) are generally higher than the values in table 4, so from the engineering safety point of view, the bias coefficient 0.5 is defined as the critical value for judging whether engineering reinforcement measures need to be taken.

[0085] From the analysis of the calculation results listed in Table 3 and Table 4, it can be seen that the bias coefficient is greatly affected by the transverse slope gradient and the buried depth, and the steeper the slope and the shallower the buried depth, the greater the bias coefficient. The minimum bias coefficient listed in Table 3 is about 0.30, and most of the model calculation results are slightly higher than 0.30, so the bias coefficient 0.30 can be considered as the critical value for considering the bias of the tunnel; the minimum bias coefficient listed in Table 4 is 0.56, and for the safety of the project, the bias coefficient 0.50 can be considered as the critical value for the need for engineering reinforcement measures of the stratum. According to the above conclusions, the bias coefficient C <0.3 is the first grade bias coefficient, and the bias degree is "slight bias"; C <0.5 is the second grade bias coefficient, and the bias degree is "moderate bias"; C ≥0.5 is the third grade bias coefficient, and the bias degree is "serious bias".

[0086] The following is an embodiment of the present application, which determines the influence of a plurality of bias influencing factors on the bias coefficient under each bias grade based on numerical simulation, and takes one or more bias influencing factors with the greatest influence on the bias coefficient as the target influencing factor.

[0087] The tunnel portal section can be located in a soil slope or a rock slope. To study the influence law of the soil slope on the bias of the tunnel, the FLAC3D numerical simulation software based on the finite difference method is used to numerically simulate the bias influencing factors, so as to determine one or more bias influencing factors with the greatest influence on the bias coefficient as the target influencing factor. Among them, the calculation model of different transverse slope gradients, tunnel buried depths and surrounding rock modulus is established by the FLAC3D numerical simulation software, and single factor analysis is carried out respectively for the same variable. Then, according to the single factor analysis results, the variable with greater influence is selected for multi-factor analysis, so as to obtain the general law of the overburden soil slope causing bias to the tunnel. Since the surrounding rock of the shallow-buried tunnel portal is mostly broken and loose, it is considered as V-class surrounding rock for analysis, and the calculation parameter values are shown in Table 6.

[0088] Table 6 Physical and mechanical parameters used in FLAC3D calculation

[0089]

[0090] In the embodiment of the present application, considering that the calculation mainly involves the analysis of the mechanical characteristics of the tunnel passing through the soil surrounding rock, the three-dimensional finite difference method program FLAC3D7.0 is used for numerical simulation calculation. In the calculation model, the surrounding rock material is simulated by the Mohr-Coulomb elastic-plastic constitutive model, and the tunnel lining is simulated by the elastic constitutive model.

[0091] The elastic constitutive model in FLAC3D is based on a spatial problem with 15 basic equations and 15 unknown functions. The number of basic equations is equal to the number of unknown functions, and the appropriate boundary conditions can be solved.

[0092] The equilibrium differential equations of spatial problem are:

[0093]

[0094] The equilibrium differential equations of spatial problem describe the static equilibrium conditions that must be satisfied between the stress state and the body force at any point inside the object. Among them, , and represent the three components of the normal stress at that point, i.e. the stress acting perpendicular to the x-axis, y-axis and z-axis. , and other symbols represent shear stress components, the first subscript indicates the normal direction of the stress surface, and the second subscript indicates the direction of the stress. X, Y and Z represent the components of the body force in the x, y and z directions per unit volume of the object.

[0095] The geometric equations of spatial problem are:

[0096]

[0097] The geometric equations of spatial problem establish the geometric relationship between the object before and after deformation, i.e. describe the relationship between strain and displacement. Among them, , and represent the normal strain along the x, y and z directions at that point, i.e. the relative elongation or shortening of length. , , represent the engineering shear strain components, which describe the amount of angle change. u, v and w represent the displacement components of the point in the x, y and z directions. The geometric equations of spatial problem are explicitly expressed by partial derivatives, and the strain is essentially the gradient of the displacement field with respect to space. Therefore, as long as the displacement of each point in the object is known, the strain state can be completely determined by this set of geometric equations.

[0098] The constitutive equations of spatial problem are:

[0099]

[0100] The constitutive equations of spatial problem describe the mechanical properties of the material itself and reveal the physical relationship between stress and strain. Among them, E is the elastic modulus, and the greater the value, the less likely the material is to deform. is the Poisson's ratio, which represents the ratio of the absolute value of the lateral strain to the axial strain when the material is subjected to uniaxial tension or compression. The left side of the equation is the strain component, and the right side is the corresponding stress component combination. represents the shear stress component acting on the plane perpendicular to the y-axis and along the z-axis direction, represents the shear stress component acting on the plane perpendicular to the z-axis and along the x-axis direction, represents the shear stress component acting on the plane perpendicular to the x-axis and along the y-axis direction. For normal strain, it is not only related to the normal stress in the same direction, but also coupled by the normal stress in the perpendicular direction, which is caused by the Poisson's effect. For shear strain, it is only proportional to the corresponding shear stress component.

[0101] Please refer to Figure 5 , Figure 5 is the Mohr-Coulomb yield criterion in FLAC3D shown in the embodiment of the present application. The failure envelope of the Mohr-Coulomb elastoplasticity constitutive model conforms to the Mohr-Coulomb criterion with a tensile intercept (i.e. the shear yield function). The position of the stress point on the envelope is jointly controlled by the non-associated flow rule of shear failure and the associated flow rule of tensile failure. There is a relationship of between the principal stresses, and the yield criterion is defined by and and is established on the stress plane, and the envelope function of the failure is: . is the maximum principal stress, is the intermediate principal stress, is the minimum principal stress.

[0102] The ray starting from the point B and passing through the point A can be defined as the Mohr-Coulomb failure criterion envelope , and the expression is:

[0103]

[0104] The ray starting from the point B and passing through the point C can be defined as the tensile failure criterion envelope , and the expression is:

[0105]

[0106] wherein, , is the cohesion, is the internal friction angle, is the tensile strength.

[0107] The tensile strength of the material cannot exceed the value of the point D, that is, the straight line is parallel to the straight line The maximum of the intersection of the lines of the function f and the function g can be calculated by the following formula:

[0108]

[0109] The potential function is described by two functions: and . Corresponding to the non-associated flow rule, there is the following form:

[0110]

[0111] where, Ψ is the dilatancy angle, consistent with .

[0112] Corresponding to the associated flow rule, there is the following form:

[0113]

[0114] The angle bisector of the straight line and will divide the area above the envelope into two areas, as shown in Figure 5 . When the stress point falls within area 1, shear failure occurs; when the stress point falls within area 2, tensile failure occurs.

[0115] When the tunnel portal section is located in a soil slope, the biasing factors include the slope of the slope body, the tunnel burial depth, and the stiffness of the tunnel surrounding rock.

[0116] Please refer to Figure 6 , Figure 6 for the numerical calculation model schematic diagram provided by the embodiments of the present application under different slope body slopes. Figure 6 It is shown in the embodiments of the present application that the fixed tunnel burial depth is set to 10m, and 9 numerical calculation models are established from 10° to 50° different transverse slope slopes. Figure 7 The maximum compressive stress nephogram of the tunnel surrounding rock under different slopes provided by the embodiments of the present application, Figure 7 each maximum compressive stress nephogram in Figure 6 corresponds to each numerical calculation model in . The color of the maximum compressive stress nephogram is from blue to red, indicating that the compressive stress value gradually increases.

[0117] According to the 9 numerical calculation models, the relationship between the slope of the slope body and the biasing coefficient can be obtained, please refer to Figure 8 , Figure 8This is a schematic diagram illustrating the variation curves of slope gradient and bias coefficient provided in the embodiments of this application. It can be seen that as the cross slope gradient increases, the bias coefficient at the arch foot increases, reaching a maximum value around 45°. When it exceeds 45°, the bias coefficient at the arch foot drops sharply, while the bias coefficient at the arch shoulder increases. This is because when the slope is too steep, the direction of pressure within the slope gradually becomes orthogonal to the tunnel arch shoulder. However, in reality, soil slopes exceeding 45° are rare. Therefore, it can be considered that the bias coefficient is directly proportional to the slope, meaning that the greater the slope, the more severe the tunnel bias.

[0118] Please refer to Figure 9 , Figure 9 A schematic diagram of a numerical calculation model for different tunnel burial depths provided in the embodiments of this application. Figure 9 The image shows 12 calculation models with a fixed cross slope of 25° set in this application, and different tunnel burial depths ranging from 5m to 70m. Figure 10 The maximum compressive stress cloud diagrams of the surrounding rock of tunnels at different burial depths are provided in the embodiments of this application. Figure 10 Each maximum compressive stress contour plot and Figure 9 Each numerical calculation model corresponds one-to-one. The color of the maximum compressive stress contour map changes from blue to red, indicating that the compressive stress value gradually increases.

[0119] Based on 12 numerical calculation models, the influence relationship between tunnel burial depth and bias coefficient can be obtained. Please refer to [the relevant documentation]. Figure 11 , Figure 11 This is a schematic diagram illustrating the relationship between tunnel burial depth and bias coefficient provided in an embodiment of this application. It can be seen that as the tunnel burial depth increases, the bias coefficient at the arch foot and arch waist shows the same decreasing trend, while the bias at the arch shoulder remains insignificant. Within a burial depth of 20m, the rate of change of the bias coefficient is relatively large. When the burial depth exceeds 45m, the bias coefficient is generally less than 0.1 and does not change significantly. At this point, the stress on both sides of the tunnel is relatively balanced, and the tunnel is not affected by bias. This also explains why shallow-buried tunnels are more prone to bias failure at the tunnel entrance.

[0120] Please refer to Figure 12 , Figure 12 This is a schematic diagram of a numerical calculation model for the stiffness of the surrounding rock of a tunnel, provided in an embodiment of this application. Figure 12 The diagram illustrates a calculation model with a fixed cross slope of 25° and a tunnel depth of 10m, as set in this application. The elastic modulus of the surrounding rock is set to 0.1GPa, 0.3GPa, 0.5GPa, 0.7GPa, and 1.0GPa, and the bias coefficient is calculated for each. The specific element division of the calculation model and the calculation results are also presented. Figure 13 As shown. Figure 13 This application provides cloud diagrams of the maximum compressive stress in the surrounding rock of a tunnel under different elastic moduli. Figure 13The maximum compressive stress nephogram with the elastic modulus of surrounding rock set as 0.1 GPa, 0.3 GPa, 0.5 GPa, 0.7 GPa and 1.0 GPa is shown in FIG. 2, and the color of the maximum compressive stress nephogram gradually increases from blue to red, indicating that the compressive stress value gradually increases.

[0121] According to the plurality of maximum compressive stress nephograms, the relationship between the stiffness of the tunnel surrounding rock and the bias coefficient can be obtained, please refer to FIG. 3. Figure 14 Figure 14 FIG. 3 is a schematic diagram of the change curve of the stiffness of the tunnel surrounding rock and the bias coefficient provided by the embodiment of the present application. It can be seen that, as the elastic modulus of the surrounding rock increases, the bias coefficient shows a decreasing trend. When the elastic modulus of the surrounding rock is below 0.5 GPa, the change rate of the bias coefficient is relatively large, and when the elastic modulus of the surrounding rock is above 0.5 GPa, the change rate of the bias coefficient is relatively small or even basically unchanged. This indicates that in the hard rock with high stiffness, the bias coefficient almost does not change with the change of the stiffness, which can also explain the reason why the bias damage of the tunnel usually occurs in the surrounding rock of grade IV, V and below.

[0122] When the tunnel portal section is located in a rock slope, the bias influencing factors include the slope gradient, the tunnel burial depth, the structural plane inclination, the structural plane strength, the rock thickness and the position of the weak structural plane.

[0123] In order to study the influence law of the rock slope on the bias of the tunnel, the 3DEC numerical simulation software based on the discrete element method is used to numerically simulate the bias influencing factors, so as to determine one or more bias influencing factors that have the greatest influence on the bias coefficient as the target influencing factor. Specifically, the calculation models of different horizontal slope gradients, tunnel burial depths, structural plane inclinations, structural plane strengths and rock thicknesses are established by the 3DEC numerical simulation software, and single-factor analysis is performed on the same variable. Then, according to the single-factor analysis results, the variables with greater influence factors are selected for multi-factor analysis, so as to obtain the general law of the rock slope causing the bias of the tunnel. Since the surrounding rock of the shallow-buried tunnel portal is mostly broken and loose, the adverse situation is considered, and the V-grade surrounding rock is analyzed, and the calculation parameter values are shown in Tables 7 and 8.

[0124] Table 7: Physical and mechanical parameters used in 3DEC calculation

[0125]

[0126] Table 8: Physical and mechanical parameters of structural plane used in 3DEC calculation

[0127]

[0128] ​In the embodiments of the present application, considering that the calculation mainly involves mechanical characteristic analysis of tunnel passing through multi-joint rock mass, a three-dimensional discrete element method program 3DEC7.0 is used for numerical simulation calculation. In the calculation model, the surrounding rock material is simulated by using a Mohr-Coulomb elastic-plastic constitutive model, and the tunnel lining is simulated by using an elastic constitutive model.

[0129] Please refer to Figure 15 , Figure 15 The numerical calculation model schematic diagram of different slope body slopes under the rock slope provided in the embodiments of the present application is shown. Figure 15 In the embodiments of the present application, the fixed tunnel buried depth is set to 10 m, the structural plane inclination angle is set to 30°, the rock thickness is set to 5 m, and nine calculation models with different slopes from 10° to 50° are established. Figure 16 The tunnel surrounding rock maximum compressive stress nephogram under different slope body slopes under the rock slope provided in the embodiments of the present application is shown. Figure 16 Each maximum compressive stress nephogram in the embodiments of the present application corresponds to each numerical calculation model in the embodiments of the present application. The color of the maximum compressive stress nephogram is from blue to red, indicating that the compressive stress value gradually increases. Figure 15

[0130] According to the nine numerical calculation models, the influence relationship of the slope body slope under the rock slope on the eccentric compression coefficient can be obtained. Please refer to Figure 17 , Figure 17 The variation curve schematic diagram of the slope body slope and the eccentric compression coefficient under the rock slope provided in the embodiments of the present application is shown. It can be seen that, with the increase of the slope, the eccentric compression coefficient at the arch foot increases, and the maximum value is about 45 degrees. When the slope is greater than 45 degrees, the eccentric compression coefficient at the arch foot decreases. Compared with the soil slope, the bedding rock slope has a fixed eccentric compression direction of the tunnel due to the existence of the structural plane, so the phenomenon of sudden decrease of the eccentric compression coefficient at the arch foot and increase of the eccentric compression coefficient at the arch shoulder under the steep slope does not occur. It can be considered that the eccentric compression coefficient and the slope are in a positive proportional relationship, that is, the greater the slope, the more serious the tunnel eccentric compression.

[0131] Please refer to Figure 18 , Figure 18 The numerical calculation model schematic diagram of different tunnel buried depths under the rock slope provided in the embodiments of the present application is shown. Figure 18 In the embodiments of the present application, the fixed slope is set to 25°, the structural plane inclination angle is set to 30°, the rock thickness is set to 5 m, and twelve calculation models with different slopes from 5 m to 100 m are established. Figure 19 The tunnel surrounding rock maximum compressive stress nephogram under different tunnel buried depths under the rock slope provided in the embodiments of the present application is shown. Figure 19 Each maximum compressive stress nephogram in the embodiments of the present application corresponds to each numerical calculation model in the embodiments of the present application. The color of the maximum compressive stress nephogram is from blue to red, indicating that the compressive stress value gradually increases. Figure 18

[0132] ​​According to 12 numerical calculation models, the relationship between the slope gradient of the rock slope and the bias coefficient can be obtained, please refer to Figure 20 , Figure 20 The figure shows the change curve of the tunnel depth and the bias coefficient under the rock slope provided in the embodiment of the present application. It can be seen that, with the increase of the tunnel depth, the bias coefficients at the arch foot and the side wall show the same downward trend, while the bias at the arch shoulder is not obvious. Within the depth of 20 m, the change rate of the bias coefficient is larger, and when the depth exceeds 45 m, the bias coefficient is basically less than 0.2 and does not change much. At this time, the stress on both sides of the tunnel is balanced, and the tunnel will not be affected by the bias. This also shows that the portal of the shallow tunnel is more prone to bias damage.

[0133] Please refer to Figure 21 , Figure 21 The figure shows the numerical calculation model of different structural plane inclinations under the rock slope provided in the embodiment of the present application. Figure 21 The figure shows the numerical calculation model of different structural plane inclinations under the rock slope provided in the embodiment of the present application. Figure 22 The figure shows the numerical calculation model of different structural plane inclinations under the rock slope provided in the embodiment of the present application. Figure 22 Each maximum compressive stress nephogram in the figure corresponds to each numerical calculation model in the figure. Figure 21 The color of the maximum compressive stress nephogram changes from blue to red, indicating that the compressive stress value gradually increases.

[0134] According to 6 numerical calculation models, the relationship between the structural plane inclination and the bias coefficient under the rock slope can be obtained, please refer to Figure 23 , Figure 23 The figure shows the change curve of the structural plane inclination and the bias coefficient under the rock slope provided in the embodiment of the present application. It can be seen that, when the structural plane inclination is less than 40°, with the increase of the structural plane inclination, the bias coefficient shows a slightly increasing trend. When the structural plane inclination is greater than 40°, with the increase of the structural plane inclination, the bias coefficient shows a slightly decreasing trend. With the change of the structural plane inclination, the overall change of the bias coefficient is not large, and it can be seen that the change of the structural plane inclination has little effect on the bias coefficient.

[0135] Please refer to Figure 24 , Figure 24 The figure shows the numerical calculation model of the structural plane strength under the rock slope provided in the embodiment of the present application. Figure 24 The figure shows the numerical calculation model of the structural plane strength under the rock slope provided in the embodiment of the present application. Figure 25The maximum compressive stress cloud map of tunnel surrounding rock with different internal friction angles under rock slopes provided in this application embodiment is an example of this application. Figure 25 The diagram shows the maximum compressive stress contour plots with the surrounding rock elastic modulus parameter set to an internal friction angle of 10°, 20°, 30°, 40°, and 50°. The colors of the maximum compressive stress contour plots change from blue to red, indicating that the compressive stress value gradually increases.

[0136] Based on multiple maximum compressive stress contour maps, the influence of the internal friction angle of different structural planes on the bias coefficient under rock slopes can be obtained. Please refer to [link / reference needed]. Figure 26 , Figure 26 This is a schematic diagram illustrating the relationship between the internal friction angle and the bias coefficient of a structural surface under a rock slope, as provided in an embodiment of this application. It can be seen that as the internal friction angle increases, the bias coefficient decreases. However, when the internal friction angle increases beyond the slope angle of the structural surface, the decreasing trend of the bias coefficient slows significantly. This is because as the internal friction angle increases, the sliding tendency of the block weakens, and the stress on the deeply buried side of the tunnel decreases, leading to a decrease in the bias coefficient. However, when the internal friction angle is greater than the slope angle, the structural surface strength can be fully utilized, and the bias coefficient will no longer change sensitively with the internal friction angle. Overall, when the structural surface strength is sufficiently high, the bias coefficient does not change with the structural surface strength; when the structural surface strength is too low, the bias coefficient is more sensitive to changes in the structural surface strength.

[0137] Please refer to Figure 27 , Figure 27 This is a schematic diagram of a numerical calculation model for different rock layer thicknesses under a rock slope, provided in an embodiment of this application. Figure 27 The paper shows nine calculation models with a fixed tunnel burial depth of 10m, a structural surface inclination angle of 25°, a cross slope of 25°, and different rock layer thicknesses ranging from 1m to 5m, as set in this application. Figure 28 The maximum compressive stress cloud map of tunnel surrounding rock with different rock layer thicknesses under rock slopes provided in the embodiments of this application. Figure 28 Each maximum compressive stress contour plot and Figure 27 Each numerical calculation model corresponds one-to-one. The color of the maximum compressive stress contour map changes from blue to red, indicating that the compressive stress value gradually increases.

[0138] Based on nine numerical calculation models, the influence of the thickness of the underlying rock layer on the bias coefficient of a rock slope can be obtained. Please refer to [the relevant documentation]. Figure 29 , Figure 29 This is a schematic diagram illustrating the variation curves of rock stratum thickness and bias coefficient under a rock slope provided in an embodiment of this application. It can be seen that the bias coefficient decreases slightly with increasing rock stratum thickness. This is because when the rock stratum thickness is small, there are more structural surfaces passing through the tunnel, which easily leads to stress concentration in the surrounding rock, increasing stress and making bias more likely. However, overall, the bias coefficient does not change significantly with increasing rock stratum thickness; therefore, the influence of rock stratum thickness on bias is relatively small.

[0139] Please refer to Figure 30 , Figure 30 The numerical calculation model diagram of different weak structural plane positions under the rock slope provided by the embodiment of the present application is shown. Figure 30 The six calculation models of different weak structural plane positions with a fixed transverse slope gradient of 25°, a tunnel burial depth of 10 m, and a structural plane inclination of 30° are shown in the table.

[0140] According to the six numerical calculation models, the influence relationship of the weak structural plane under the rock slope on the eccentric compression coefficient can be obtained. Please refer to Figure 31 , Figure 31 The variation curve diagram of the weak structural plane and the eccentric compression coefficient under the rock slope provided by the embodiment of the present application is shown. It can be seen that when the weak structural plane is located above the tunnel vault, the structural plane has almost no influence on the eccentric compression of the tunnel; when the weak structural plane passes through the tunnel, it will cause stress concentration at the passing part and increase the degree of eccentric compression; when the weak structural plane passes from below the tunnel vault, the eccentric compression coefficient begins to slowly decrease. Overall, when the weak structural plane is located above the tunnel, it will not cause the eccentric compression influence on the tunnel, when it passes through the tunnel, the eccentric compression influence is the largest, and when it is located below the tunnel, the eccentric compression influence gradually weakens with the increase of the burial depth.

[0141] Please refer to Figure 32 , Figure 32The stress distribution cloud atlas before tunnel excavation under the rock slope provided by the embodiment of the application is provided. The whole set of cloud atlas represents the size of stress through the cold and warm changes of colors. Generally, the blue color system represents lower compressive stress, the green and yellow colors represent moderate compressive stress, and the red and orange colors represent higher compressive stress. The (a) part and the (b) part of the first set fix the buried depth condition of the tunnel, and mainly study the influence of the slope gradient on the stress distribution. The (a) part shows the stress state when the slope gradient is ten degrees. Because the slope gradient is relatively gentle, the symmetry of the terrain is high, and therefore the stress distribution is relatively uniform and symmetrical. It can be seen that the stress contours in the mountain body are distributed in a horizontal layer, and the stress gradient change around the tunnel body is relatively gentle, and there is no phenomenon of severe stress concentration. This shows that under the condition of a gentle slope, the initial stress field of the slope has little interference on the position of the tunnel. In the (b) part, the slope gradient reaches forty degrees. The steep terrain completely changes the stress mode of the mountain body, resulting in significant redistribution of stress. The stress distribution presents strong asymmetry. On the shallow side of the slope, due to the influence of the free surface, the stress is fully released, which is manifested as a large range of blue low stress area. On the deep side of the burial, due to the great constraint of the mountain rock stratum, the stress cannot be released to the free surface, causing high stress concentration, forming a significant red high stress area. The tunnel axis is no longer located in the symmetrical stress field, and the initial stress level on the right side (deep side) is much higher than that on the left side (shallow side), and this natural stress difference is a direct manifestation of the “unbalanced pressure” effect before excavation.

[0142] The (c) part and the (d) part of the second set fix the slope condition, and mainly study the influence of the tunnel buried depth on the stress distribution. The (c) part shows the stress state when the buried depth is ten meters. Because the tunnel is very close to the slope surface, the thickness of the overburden above the tunnel is very thin, and therefore the overall stress level in the region around the tunnel is low, and a large area presents blue. The stress contours closely surround the tunnel vault and the side wall. The (d) part shows the stress state when the buried depth is thirty meters. With the increase of the buried depth, the thickness of the overburden above the tunnel greatly increases, and the self-weight of the rock mass significantly increases the overall stress level in the whole region, and the area of the warm color region in the figure obviously increases. The tunnel needs to bear greater initial ground stress.

[0143] It can be seen that the initial stress field before tunnel excavation presents a layered distribution parallel to the slope surface, so the stress on the deep buried side is greater than that on the shallow buried side. After tunnel excavation, a new free surface is formed, which leads to a dramatic change in the stress field near the free surface. Since the original stress on the deep buried side is greater than that on the shallow buried side, the stress release is more significant, and the displacement of the lining and surrounding rock is greater. Tunnel structure is prone to eccentric compression failure. With the increase of slope, the stress difference on both sides before tunnel excavation will increase due to the layered distribution of the initial stress field parallel to the slope surface, so the eccentric compression degree will be more serious with the increase of slope. With the increase of burial depth, the initial stress field ratio on both sides before tunnel excavation will decrease, so the influence of eccentric compression caused by terrain will decrease to almost nothing.

[0144] After tunnel excavation, a new free surface is generated, and the active soil pressure on the deep buried side is large, which is easy to cause large deformation of the tunnel structure on the deep buried side, thereby causing eccentric compression deformation. Please refer to Figure 33 and Figure 34 , Figure 33 The tunnel excavation slope displacement cloud chart provided by the embodiment of the present application. Figure 34 The tunnel excavation eccentric compression deformation trend diagram provided by the embodiment of the present application. From Figure 33 It can be seen from (a) part shows the complex deformation mode caused by excavating a tunnel under this adverse terrain condition, and the displacement influence range is extremely wide, not only limited to the tunnel surrounding, but also extended to the entire slope surface. The color transitions from yellow-green in the interior of the slope to red near the slope toe, indicating that the displacement gradually increases from inside to outside. (b) part presents that the deep buried gentle slope shows that the eccentric compression effect caused by terrain is significantly weakened due to the large burial depth and gentle slope. The displacement cloud chart shows that the high displacement area (yellow-green) is closely concentrated in a relatively small range directly above the tunnel crown, and the entire slope almost has no obvious deformation. The displacement vector arrows are almost all perpendicular to the tunnel, and it can be clearly seen that the dominant deformation mechanism under this working condition is the loose failure caused by tunnel excavation, which is mainly vertical settlement, rather than the overall instability of the slope.

[0145] Multi-factor coupling analysis is carried out for the two factors of slope and tunnel burial depth. By comparing the eccentric compression coefficient change curves of the three characteristic points of tunnel haunch, arch waist and arch foot, it can be seen that when considering the coordinated deformation of tunnel and surrounding rock system, the haunch and arch waist will produce larger displacement due to eccentric compression load, which will affect the change law of eccentric compression coefficient. The arch foot usually does not produce large eccentric compression deformation, and the change law of eccentric compression coefficient is relatively clear, so the eccentric compression coefficient of the arch foot can best reflect the degree of influence of eccentric compression on the whole tunnel under different conditions.

[0146] After completing the calculation of all working conditions, all the eccentric compression coefficients of the soil slope can be systematically arranged in a matrix table 9.

[0147] Table 9 Calculation results of bias coefficient of soil slope tunnel

[0148]

[0149] Please refer to Figure 35 , Figure 35 The variation curve of the bias coefficient at the arch spring under the soil slope provided by the embodiment of the present application under different tunnel depths and slope gradients is shown. It can be seen that in the soil slope, the tunnel depth and the slope gradient are the most influential on the bias degree. According to the research results of the bias law of the soil slope, the qualitative evaluation table of the bias of the tunnel portal can be obtained.

[0150] In some embodiments, a semi-quantitative evaluation table of the target tunnel portal section can be generated based on the slope gradient and the tunnel depth; wherein the semi-quantitative evaluation table includes a first identification mark, a second identification mark and a third identification mark, the first identification mark represents that the bias state of the tunnel is in a first grade, the second identification mark represents that the bias state of the tunnel is in a second grade, and the third identification mark represents that the bias state of the tunnel is in a third grade. Specifically, the first identification mark can be a blue mark, the second identification mark can be a yellow mark, and the third identification mark can be a red mark. In the specific application process, the first identification mark, the second identification mark and the third identification mark can also be selected from other colors, patterns or combinations of colors and patterns.

[0151] For example, please refer to Figure 36 , Figure 36 The qualitative judgment diagram of the bias degree of the tunnel under different depth and slope gradient combinations of the soil surrounding rock provided by the embodiment of the present application is shown.

[0152] Under a certain depth and slope gradient combination, when the bias coefficient is less than 0.3, it is displayed in blue in the table, and the bias degree is “slight bias”; when the bias coefficient is greater than or equal to 0.3 and less than 0.5, it is displayed in yellow in the table, indicating that the bias needs to be considered in the tunnel design, and the bias degree is “moderate bias”; when the bias coefficient is greater than or equal to 0.5, it is displayed in red in the table, indicating that the slope needs to be supported against sliding, otherwise the bias damage may occur, and the bias degree is “severe bias”.

[0153] After the calculation of all working conditions is completed, all bias coefficients of the rock slope can be systematically arranged in a matrix table 10.

[0154] Table 10 Calculation results of bias coefficient of rock slope tunnel

[0155]

[0156] Please refer to Figure 37 , Figure 37The rock slope under different buried depth of the arch foot bias coefficient with slope change curve schematic diagram provided by the embodiment of the application. It can be seen that in the rock slope, the tunnel buried depth and the slope body slope are the greatest influence on the bias degree, according to the bias law research result of the rock slope, the qualitative evaluation table of the tunnel portal bias can be obtained. Please refer to Figure 38 , Figure 38 The rock slope under different buried depth and slope combination of the tunnel bias degree qualitative judgment schematic diagram provided by the embodiment of the application. It can be seen that when the tunnel buried depth is more than 45m, no matter how the slope changes, the bias coefficient is less than 0.3, and the growth rate of the bias coefficient is very small with the increase of the slope. The tunnel hole height used in the numerical simulation is 10m, so it can be judged that when the tunnel buried depth is more than about 4.5 times of the tunnel hole height, the influence of the bias can be ignored.

[0157] In the semi-quantitative evaluation method of the tunnel portal section bias provided by the embodiment of the application, by introducing the bias coefficient method core index, the complex mechanical behavior is converted into a quantifiable evaluation benchmark, the bias grade is divided according to multiple coefficient values, and a grading system from slight to severe is established, which provides a classification basis for bias conditions of different severity. Further, by means of numerical simulation, the action strength of each influencing factor on the bias coefficient under different grades is analyzed, so as to screen out the key target influencing factor, and finally in the actual application, only a few key factors of the target tunnel portal section need to be obtained, and the semi-quantitative evaluation result can be generated. This method can avoid the tedious full parameter calculation, greatly improve the evaluation efficiency while ensuring a certain accuracy, and provide strong support for the rapid risk assessment and targeted design of the tunnel engineering.

[0158] Based on the same application concept, the embodiment of the application further provides a computer device, which can include a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the method described in the above description when executing the computer program.

[0159] Based on the same application concept, the embodiment of the application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the method described in the above description.

[0160] The above-described embodiments are only used to illustrate the technical solutions of the application, rather than limit them; although the application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement to some technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the application, and should be included in the protection scope of the application.

Claims

1. A semi-quantitative evaluation method of the bias of a tunnel portal section, characterized in that, The method comprises the following steps: calculating a bias coefficient of a plurality of tunnel portal segments; wherein the bias coefficient is obtained based on a ratio of a stress difference of the tunnel left and right sides to an average stress of the two sides; the tunnel portal segment is located in a soil slope or a rock slope; in the case that the tunnel portal segment is located in a soil slope, the bias influencing factors include slope body slope, tunnel burial depth and tunnel surrounding rock stiffness; in the case that the tunnel portal segment is a rock slope, the bias influencing factors include slope body slope, tunnel burial depth, structural plane inclination, structural plane strength, rock thickness and weak structural plane position; determining a plurality of bias levels based on the numerical values of the plurality of bias coefficients; determining the influence of the plurality of bias influencing factors on the bias coefficient under each bias level based on numerical simulation, so as to determine one or more target influencing factors with the greatest influence on the bias coefficient as target influencing factors; obtaining one or more target influencing factors of a target tunnel portal segment, and generating a semi-quantitative evaluation result of the target tunnel portal segment based on the target influencing factors; wherein determining a plurality of bias levels based on the numerical values of the plurality of bias coefficients comprises: obtaining a plurality of engineering critical conditions of the tunnel portal segment, establishing a tunnel model corresponding to each engineering critical condition, and calculating a plurality of critical bias coefficients based on numerical simulation of each tunnel model; taking the critical bias coefficients as critical values, and determining a plurality of bias levels; determining the influence of the plurality of bias influencing factors on the bias coefficient under each bias level based on numerical simulation, so as to determine one or more target influencing factors with the greatest influence on the bias coefficient as target influencing factors, comprises: in the case that the tunnel portal segment is located in a soil slope, numerically simulating the bias influencing factors based on the finite difference method, so as to determine one or more target influencing factors with the greatest influence on the bias coefficient as the target influencing factors; in the case that the tunnel portal segment is located in a rock slope, numerically simulating the bias influencing factors based on the discrete element method, so as to determine one or more target influencing factors with the greatest influence on the bias coefficient as the target influencing factors.

2. The method of claim 1, wherein, The target influencing factors include slope body slope and tunnel burial depth.

3. The method of claim 1, wherein, The bias levels include a first level, a second level and a third level, the first level represents that the bias coefficient is less than 0.3, the second level represents that the bias coefficient is greater than or equal to 0.3 and less than 0.5, and the third level represents that the bias coefficient is greater than or equal to 0.

5.

4. The method of claim 1, wherein, The method comprises the following steps: generate a semi-quantitative evaluation table for the target tunnel portal section based on the slope of the slope body and the tunnel depth; wherein the semi-quantitative evaluation table comprises a first identification mark, a second identification mark and a third identification mark, the first identification mark representing that the bias state of the tunnel is in a first grade, the second identification mark representing that the bias state of the tunnel is in a second grade, and the third identification mark representing that the bias state of the tunnel is in a third grade.

5. The method according to any one of claims 1 to 4, characterized in that, The bias coefficient is a bias coefficient at an arch spring of the tunnel.

6. A computer device, comprising: The computer device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the method according to any one of claims 1 to 5 when executing the computer program.

7. A computer readable storage medium characterized by The computer readable storage medium stores a computer program, and the computer program is executable by the processor to implement the method according to any one of claims 1 to 5.

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