Small clear distance tunnel shearing mechanical property inversion method

Abstract

The present application provides a kind of small clear spacing tunnel shearing mechanical property inversion method, it is related to tunnel mechanics performance analysis technical field, the present application is by combining with three-dimensional model to each parameter actually collected, by the way of manually configuring initial stress environment, in simulation analysis stage, it can quantify the biasing action that rock wall is subjected to, make it more conform to the actual environment where tunnel is located;Again in combination with different types of displacement gradient and optimization algorithm, the parameter inversion of shearing mechanical property can be realized, ensure that three-dimensional model is highly consistent with actual working condition;Again by the identification and stress projection to rock wall slip surface, the stress condition of rock wall can be reflected, so that the risk cloud map finally generated, can convert complex mechanical state into intuitive spatial distribution information, so as to realize early warning to tunnel safety.

Description

Technical Field

[0001] This invention relates to the field of tunnel mechanical performance analysis technology, specifically a method for inverting the shear mechanical performance of tunnels with small clearance. Background Technology

[0002] In the construction of transportation infrastructure in mountainous areas, due to terrain constraints, small-clearance tunnels have become a common engineering form. Traditionally, small-clearance tunnels are excavated in the middle of the mountain, with the top of the tunnel walls relatively uniform on both sides. However, in special cases such as those requiring vegetation protection or bridge-tunnel connections, the tunnel may be biased towards one side of the mountain, resulting in uneven distribution of the top of the middle rock wall on both sides. This causes the tunnel to be subjected not only to vertical self-weight stress but also to lateral shear caused by biased pressure.

[0003] In the prior art, CN115370418A discloses a data processing method and apparatus for judging the stability of rock walls in tunnels. The method includes: acquiring tunnel data to be processed, representing relevant data of the target construction tunnel; performing model construction processing on the tunnel data to obtain tunnel model data; extracting stability features from the tunnel model data to obtain stability feature data, which represents the stability characteristics of the rock walls in the target construction tunnel; and judging the stability feature data to obtain the judgment result of the stability of the rock walls in the target construction tunnel. Although this scheme can simulate the stability of the rock walls by constructing a tunnel model, it still analyzes under ordinary uniform stress conditions. When the tunnel excavation area is not located in the middle of the mountain, the bias pressure on the rock walls is ignored, resulting in a large discrepancy with the actual tunnel environment and reduced accuracy of the analysis results.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a method for inverting the shear mechanical properties of tunnels with small clearances, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: A method for inverting the shear mechanical properties of tunnels with small clearances, comprising the following steps: S1: Several detection points are symmetrically set on both sides of the middle rock wall of the tunnel to collect displacement parameters at different heights on both sides of the middle rock wall, and the slope angle of the tunnel mountain, the natural unit weight of the rock mass and the actual burial depth of each detection point are collected simultaneously. S2: The actual burial depth and slope angle are combined to correct the lateral pressure coefficient of the tunnel, and the asymmetric lateral pressure coefficient of each detection point is obtained. At the same time, a three-dimensional model of the tunnel is constructed, and the stress tensor is set according to the asymmetric lateral pressure coefficient of each detection point to configure the initial stress environment of the three-dimensional model. S3: The three-dimensional model is simulated and analyzed based on the finite difference method to generate a simulated displacement gradient that reflects the degree of shear deformation of the middle rock wall. Then, the actual displacement gradient of the middle rock wall is calculated based on the displacement parameters. Combined with the optimization algorithm, the equivalent values ​​of cohesion and internal friction angle are generated respectively. S4: Based on the equivalent value of the internal friction angle and the slope angle, the azimuth angle of the slip surface of the middle rock wall is generated. Then, by combining the equivalent value of the cohesion and the internal friction angle, the azimuth angle and the stress tensor of each detection point, the projected shear stress and projected stress of each detection point on the slip surface are calculated. S5: Generate asymmetric risk factors for each detection point based on the projected shear stress and projected stress on the slip surface. Then, compare the asymmetric risk factors of each detection point with several preset judgment intervals in sequence, and generate a risk cloud map of the tunnel based on the comparison results.

[0007] Preferably, based on the excavation location of the tunnel, the two sides of the rock wall in the tunnel are defined as the deep buried side and the shallow buried side, respectively, with the side closer to the tunnel mountain being the deep buried side and the side farther away from the tunnel mountain being the shallow buried side; The displacement parameters include vertical displacement and horizontal displacement. When collecting displacement parameters, several detection sections are uniformly set along the tunnel axis, and for each detection section, the detection points are uniformly and symmetrically set on both sides of the middle rock wall.

[0008] Preferably, the lateral pressure coefficient is obtained from an empirical formula in the theory of earth pressure at rest, specifically the difference between a preset empirical constant and the sine of the initial value of the internal friction angle; The asymmetric lateral pressure coefficient is the product of the lateral pressure coefficient and the correction factor, plus the lateral pressure coefficient. The correction factor is constructed based on Coulomb's earth pressure theory and the equivalent burial depth theory, and includes three multiplied sub-terms. The first sub-term is a preset terrain correction constant, the second sub-term is the ratio between the difference in actual burial depth of the detection points on both sides of the rock wall at the same height and the axial distance between the tunnel's first and second tunnels, and the third sub-term is the sine value of twice the slope angle.

[0009] Preferably, when configuring the initial stress environment of the 3D model, an initial value of the stress tensor needs to be set for each detection point. The stress tensor includes horizontal stress, vertical self-weight stress, and shear stress, wherein: The initial value of the vertical self-weight stress is the product of the natural unit weight of the rock mass and the actual burial depth of the detection point; The initial value of the horizontal stress is the product of the asymmetric lateral pressure coefficient and the vertical self-weight stress; The initial value of the shear stress is the product of the tangent of the slope angle and the vertical self-weight stress.

[0010] Preferably, the simulated displacement gradient and the actual displacement gradient are both displacement gradients, which are calculated from the simulated and measured values ​​of the displacement parameters of the detection points, respectively. The displacement gradient is positively correlated with the difference in displacement parameters of the detection points on both sides of the middle rock wall and negatively correlated with the net thickness of the middle rock wall.

[0011] Preferably, when generating equivalent values ​​of cohesion and internal friction angle, the optimization objective is to minimize the error between the simulated displacement gradient and the actual displacement gradient, and the cohesion and internal friction angle of the rock mass are used as optimization variables for optimization.

[0012] Preferably, the azimuth angle of the slip surface of the middle rock wall is obtained based on the Mohr-Coulomb criterion and the Rankine active pressure theory. Specifically, it is 45° plus the equivalent value of half the internal friction angle, and then minus half the slope angle. The azimuth angle is used to reflect the degree to which the slip surface of the middle rock wall deviates from the deep buried side to the shallow buried side under the lateral pressure of the tunnel mountain. The projected shear stress and projected stress of each detection point on the slip surface are calculated by stress transformation formula and are used to represent the projection of the stress tensor of the detection point on the slip surface.

[0013] Preferably, the asymmetric risk factors at each detection point are expressed in fractional form, where the numerator is the absolute value of the projected shear stress at the detection point, and the denominator is the product of the projected stress and the tangent of the equivalent value of the internal friction angle at the detection point, plus the equivalent value of the cohesion.

[0014] Preferably, the logic for generating a risk cloud map of the tunnel based on the comparison results is as follows: The judgment intervals are arranged in ascending order, and are continuous and non-overlapping with each other. Each group of judgment intervals corresponds to a risk level. Sequentially identify the judgment interval of the asymmetric risk factor at each detection point, and assign the risk level of the judgment interval to the corresponding detection point; Each risk level is assigned a color, and in the 3D model of the tunnel, the color is rendered with the detection point as the center and the preset grid length as the radius, thereby generating a risk cloud map of the entire tunnel.

[0015] Compared with the prior art, the beneficial effects of the present invention are: This invention combines actual collected parameters with a 3D model and manually configures the initial stress environment to quantify the biasing effect on the rock wall during the simulation analysis stage, making it more consistent with the actual environment of the tunnel. By combining different types of displacement gradients and optimization algorithms, it can achieve parameter inversion of shear mechanical properties, ensuring that the 3D model closely matches the actual working conditions. Furthermore, by identifying the slip surface of the rock wall and projecting stress, it can reflect the stress state of the rock wall. The resulting risk cloud map can transform the complex mechanical state into intuitive spatial distribution information, thereby enabling early warning of tunnel safety. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the overall method flow of the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0018] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0019] Example: Please see Figure 1 The present invention provides a technical solution: A method for inverting the shear mechanical properties of tunnels with small clearances, comprising the following steps: S1: Several detection points are symmetrically set on both sides of the middle rock wall of the tunnel to collect displacement parameters at different heights on both sides of the middle rock wall, and the slope angle of the tunnel mountain, the natural unit weight of the rock mass, and the actual burial depth of each detection point (i.e., the vertical distance between the detection point and the upper surface of the tunnel mountain) are collected simultaneously.

[0020] Based on the tunnel's excavation location, the two sides of the tunnel wall are defined as the deep-buried side and the shallow-buried side, with the side closer to the tunnel's mountain body being the deep-buried side and the side farther away being the shallow-buried side. Simply put, when the tunnel is located on a steep slope, the difference in overburden thickness between the two sides of the central rock wall is significant, and correspondingly, the actual burial depth of the monitoring points on both sides also differs considerably. The central rock wall is not only subjected to compression but also to enormous lateral shear thrust, meaning it experiences biased pressure from the deep-buried side to the shallow-buried side.

[0021] Displacement parameters include vertical and horizontal displacement. When collecting these parameters, several detection sections are uniformly set along the tunnel direction, and for each section, detection points are evenly and symmetrically placed on both sides of the central rock wall. Taking a 150m long tunnel with a small clearance as an example, detection sections can be set at 10m intervals, and the central rock wall in 15 detection sections can be analyzed sequentially. Detection points on both sides of the central rock wall at the same height can be grouped together for subsequent calculations. The more detection sections and points, the slower the simulation analysis, but the higher the accuracy. This can be adjusted according to actual engineering needs. This method allows for the analysis of the tunnel from a local to a global perspective, thereby improving the inversion effect of the shear force on the central rock wall under eccentric pressure.

[0022] S2: The actual burial depth and slope angle are combined to correct the lateral pressure coefficient of the tunnel, and the asymmetric lateral pressure coefficient of each detection point is obtained. At the same time, a three-dimensional model of the tunnel is constructed, and the stress tensor is set according to the asymmetric lateral pressure coefficient of each detection point to configure the initial stress environment of the three-dimensional model.

[0023] In geotechnical mechanics, the lateral pressure coefficient is the ratio of horizontal compressive stress to vertical compressive stress, representing the natural lateral pressure exerted on the rock mass due to the Poisson effect when there is no slope. This value can be obtained either through experimental methods, such as axial displacement control tests using a triaxial apparatus, or through empirical formulas in the theory of earth pressure at rest. In this embodiment, an empirical formula is used, specifically the difference between a preset empirical constant and the sine of the initial value of the internal friction angle, expressed as: In the formula , These represent the initial values ​​of the lateral pressure coefficient and the internal friction angle, respectively. This represents a preset empirical constant. The initial value of the internal friction angle corresponds to the internal friction angle of the rock mass under no bias pressure, which can be obtained through laboratory measurement. Specifically, rock samples are collected from the tunnel shaft, and triaxial compression tests are conducted in the laboratory. Multiple sets of tests under different confining pressures are performed, and the value is obtained using the Mohr's circle envelope. The specific method will not be elaborated here. The preset empirical parameter is typically set to 1.

[0024] Asymmetric lateral pressure coefficient Lateral pressure coefficient and correction factor The product of these factors, plus the lateral pressure coefficient, combined with like terms, gives the following expression: The correction factor is constructed based on Coulomb's earth pressure theory and equivalent burial depth theory, and includes three multiplied sub-terms. The first sub-term is a preset terrain correction constant; the second sub-term is the ratio between the actual burial depth difference between the detection points on both sides of the rock wall at the same height and the axial distance between the tunnel's lead tunnel and follow tunnel; and the third sub-term is the sine of twice the slope angle. The specific expression is as follows: In the formula This represents the preset terrain correction constant, typically ranging from 0.85 to 1.15, which is fine-tuned based on the integrity of the rock mass. This represents the difference in actual burial depth between the detection points on both sides of the rock wall at the same height. It can be understood that the height here refers to the distance between the detection point and the tunnel surface. This indicates the axial spacing between the preceding and following tunnels. This indicates the slope angle of the tunnel mountain.

[0025] The asymmetric lateral pressure coefficient is primarily constructed based on two core mechanical principles. The first is the stress tensor rotation principle. This is because when the tunnel body has a slope angle, the principal stress directions within the rock mass are no longer absolutely horizontal and vertical, but rather rotate. According to the semi-infinite space slope stress solution in elasticity, the surface inclination causes the stress circle to deviate from the origin. To express this rotated state in a horizontal-vertical coordinate system, the lateral pressure coefficient in the horizontal direction needs to be compensated. The second is the wedge effect. Since the overburden thickness on the deeply buried side is greater than that on the shallowly buried side, the biased rock mass can be approximated as a wedge. The tunnel's central rock wall is actually in a non-uniform pressure field. For the two detection points at the same height, the potential energy difference caused by the difference in their actual burial depth is transmitted laterally through the shear strength of the central rock wall, thus causing lateral compression on the central rock wall.

[0026] As can be seen from the expression of the correction factor, The equivalent burial depth method is used to construct the tunnel. The equivalent burial depth method indicates that the degree of bias pressure is proportional to the difference in burial depth on both sides of the central rock wall and the tunnel spacing. Therefore, it is used to reflect the severity of the bias pressure on the central rock wall. The larger the value, the stronger the bias pressure on the central rock wall and the greater the lateral shear force it experiences. It is derived from Coulomb's earth pressure theory, by incorporating the slope angle and then deforming. According to the stress projection principle, when the slope angle is 45°, The shear stress generated is the greatest when the slope angle is at its maximum, so this term is actually to capture the effect of the slope angle on the shear stress.

[0027] When configuring the initial stress environment of the 3D model, an initial value for the stress tensor needs to be set for each detection point. The stress tensor includes horizontal stress, vertical self-weight stress, and shear stress, where: Initial value of vertical self-weight stress The natural unit weight of the rock mass The actual burial depth of the detection point The product of these is: Initial value of horizontal stress It is the product of the asymmetric lateral pressure coefficient and the vertical self-weight stress, i.e.: Initial value of shear stress It is the product of the tangent of the slope angle and the vertical self-weight stress, that is: .

[0028] As can be seen from the above calculation formula, for a set of detection points at the same height, since one is on the deep buried side and the other is on the shallow buried side, their actual burial depths are different, and the magnitude of the force exerted by the mountain is different. Therefore, the corresponding stress tensors are also different, and the stress tensor projections on the slip surface will be different.

[0029] In this step, by correcting the lateral pressure coefficient and abandoning the software's built-in automatic gravity loading before the equilibrium calculation, the asymmetric lateral pressure coefficient is manually injected into the 3D model. This forces the model to have an initial stress environment with bias pressure before the simulation, so that when performing finite difference analysis (i.e., 3D-FDM) on the tunnel 3D model, the bias pressure effect on the tunnel can be reflected in the simulation process, so as to truly reflect the stress state of the rock wall under this bias pressure, thereby more accurately identifying potential risk areas.

[0030] S3: The three-dimensional model is simulated and analyzed based on the finite difference method to generate a simulated displacement gradient that reflects the degree of shear deformation of the rock wall. The actual displacement gradient of the rock wall is then calculated based on the displacement parameters. Combined with the optimization algorithm, the equivalent values ​​of cohesion and internal friction angle are generated respectively.

[0031] Both simulated and actual displacement gradients are displacement gradients, calculated from the simulated values ​​(i.e., displacement parameters obtained through 3D-FDM simulation analysis) and measured values ​​of the displacement parameters at the detection points, respectively. The displacement gradient is positively correlated with the difference in displacement parameters between the detection points on both sides of the central rock wall and negatively correlated with the net thickness of the central rock wall. The formula for calculating the displacement gradient is: In the formula Represents the displacement gradient. , They represent the first The horizontal and vertical displacements of the detection points on the left side of the group. , They represent the first The horizontal and vertical displacements of the detection points on the right side of the group, with subscripts... This indicates the group index of the detection point. This represents the total number of detection point groups on a detection cross section (i.e., half the total number of detection points on a detection cross section). The net thickness of the rock wall is represented by the above formula. By substituting displacement parameters from different data sources, the simulated displacement gradient and the actual displacement gradient can be obtained respectively.

[0032] As can be seen from the formula for calculating the displacement gradient, it measures the ratio between the displacement difference on both sides of the middle rock wall and the net thickness. The displacement difference on both sides is caused by shear force. Therefore, the displacement gradient essentially reflects the shear strain of the middle rock wall.

[0033] When generating equivalent values ​​for cohesion and internal friction angle, the optimization objective is to minimize the error between the simulated displacement gradient and the actual displacement gradient, using the cohesion and internal friction angle of the rock mass as optimization variables. The LM algorithm can be used for inversion, and its objective function can be expressed as: In the formula Describe the objective function. This represents the damping factor used to balance search speed and stability. Represents the identity matrix, used to ensure that the computation converges. , These represent the equivalent values ​​of cohesion and internal friction angle, respectively. , These represent the actual displacement gradient and the simulated displacement gradient, respectively. The damping factor is usually preset to a small integer, such as 0.01. If the error decreases significantly after iteration, it indicates that the current model is linearized well, and the damping factor can be further reduced, for example, set to one-tenth of the original value, making the LM algorithm more inclined towards the Gauss-Newton method to obtain a faster convergence speed. Conversely, if the error increases, it indicates that the step size is too large or the nonlinearity is too strong, and the damping factor can be further increased, for example, set to ten times the original value, making the LM algorithm more inclined towards the gradient descent method, utilizing its better stability to find the correct descent direction.

[0034] By making the simulated displacement gradient approximate the actual displacement gradient, the algorithm can sense the deflection of the middle rock wall caused by bias pressure, thereby fitting the actual cohesion and internal friction angle of the rock mass under bias pressure, and better reflecting the true mechanical properties of the tunnel under bias pressure, thus generating a risk cloud map in subsequent steps.

[0035] S4: Based on the equivalent value of the internal friction angle and the slope angle, the azimuth angle of the slip surface of the middle rock wall is generated. Then, by combining the equivalent values ​​of cohesion and internal friction angle, the azimuth angle and the stress tensor of each detection point, the projected shear stress and projected stress of each detection point on the slip surface are calculated.

[0036] The azimuth of the slip surface of the middle rock wall is obtained based on the Mohr-Coulomb criterion and the Rankine active pressure theory. Specifically, it is 45° plus half the equivalent value of the internal friction angle, and then minus half the slope angle. The azimuth angle is used to reflect the degree to which the slip surface of the middle rock wall deviates from the deep-buried side to the shallow-buried side under the lateral pressure of the tunnel body. The specific expression is: As can be seen from the expression for the azimuth angle, the first part is based on the Mohr-Coulomb limit equilibrium theory. According to this theory, when a material undergoes shear failure, the angle between the slip surface and the direction of the maximum principal stress is 45° plus the equivalent value of half the internal friction angle. This reflects the fracture situation within the rock mass determined by the internal friction angle. Furthermore, under normal circumstances, the overburden at the top of the tunnel is relatively uniform (i.e., the tunnel is located in the middle of the mountain), the middle rock wall is not subjected to bias pressure, and the slip surface does not deflect. Its azimuth angle is determined only by the intrinsic property of the equivalent value of the internal friction angle of the rock mass. However, when the tunnel is not located in the middle of the mountain, the ground is not horizontal but has a slope angle. According to the Rankine active pressure theory, the direction of the principal stress in the rock mass will deflect. Since the azimuth angle is the angle between the slip surface and the horizontal plane, when the direction of the principal stress deflects, it is necessary to subtract about half of the slope angle (which can be regarded as an approximation in engineering applications).

[0037] The projected shear stress and projected normal stress at each test point on the slip surface are calculated using stress transformation formulas, which represent the projection of the stress tensor at that test point onto the slip surface. The theoretical basis for this stress transformation is the stress tensor projection theory and the Coulomb-Mohr strength theory, both commonly used standard equations, differing only in the direction of rotation, which does not affect the calculation results. The rotation direction in the standard formulas is usually defined as a counterclockwise rotation from the horizontal direction to the normal direction; in engineering applications, it is a clockwise rotation from the vertical axis to the slip surface angle. In this embodiment, the expressions for the two sets of formulas are as follows: In the formula , , These represent horizontal stress, vertical self-weight stress, and shear stress, respectively. , These represent the projected shear stress and the projected stress projected onto the slip surface, respectively.

[0038] In this step, by introducing the slope angle as a correction factor, the azimuth angle of the middle rock wall slip surface can be changed according to the inclination of the mountain, which can truly reflect the physical properties of the middle rock wall shearing and sliding from the deep buried side to the shallow buried side under the action of bias pressure.

[0039] S5: Generate asymmetric risk factors for each detection point based on the projected shear stress and projected stress on the slip surface. Then, compare the asymmetric risk factors of each detection point with several preset judgment intervals in sequence, and generate a risk cloud map of the tunnel based on the comparison results.

[0040] The asymmetric risk factors at each testing point are expressed as fractions. The numerator is the absolute value of the projected shear stress at that testing point (to avoid directional influence); the denominator is the product of the projected stress and the tangent of the equivalent value of the internal friction angle at that testing point, plus the equivalent value of the cohesion. Asymmetric Risk Factors The expression is as follows: As can be seen from the expression of the asymmetric risk factor, its numerator is equivalent to the actual shear stress projected onto the slip surface at the test point under biased pressure, while the denominator is the maximum stress that the slip surface can withstand under biased pressure, calculated by the Mohr-Coulomb strength theory. Therefore, the asymmetric risk factor is essentially the ratio of the "actual value" to the "theoretical maximum value"; the larger the ratio, the greater the risk of failure.

[0041] The logic for generating a risk cloud map for the tunnel based on the comparison results is as follows: Several judgment intervals are arranged in ascending order, and they are continuous and have no overlap. Each set of judgment intervals corresponds to a risk level. Sequentially identify the judgment interval of the asymmetric risk factor at each detection point, and assign the risk level of the judgment interval to the corresponding detection point; Each risk level is assigned a color, and in the 3D model of the tunnel, the color is rendered with the detection point as the center and the preset grid length as the radius, thereby generating a risk cloud map of the entire tunnel.

[0042] For example, when setting the judgment intervals, the first interval can be set to 0 to 0.6. When the asymmetric risk factor is within this interval, it means that the rock mass is in the elastic stage, the risk level is level 1 (no risk), and the corresponding color is green. The second interval is set to 0.6 to 0.85, which means that the rock mass has entered the plastic evolution period and has a shearing tendency. The risk level is level 2 (low risk), and the corresponding color is yellow. The third interval is set to 0.85 to 1, which means that the rock mass is close to the limit equilibrium state and has a significant slip risk. The risk level is level 3 (high risk), and the corresponding color is orange. The third interval is set to greater than or equal to 1, which means that the rock mass at this location has been damaged. The risk level is level 4 (damage), and the corresponding color is red.

[0043] All the above judgment intervals are closed at the beginning and open at the end, ensuring continuity and no overlap, thus classifying each detection point. Furthermore, if the number of detection points is small, methods such as Kriging interpolation and radial basis function interpolation can be used to smooth the risk cloud map.

[0044] In this step, by constructing an asymmetric risk factor, the mechanical properties of the inverted rock wall can be condensed and standardized into a scalar value. Then, through a rendering method centered on the detection point and with a preset grid as the radius, risk prediction can be expanded from a "point" to a "surface" and a "volume". In other words, this method can not only intuitively show whether the tunnel has risks, but also accurately indicate which height and longitudinal section of the rock wall has the highest risk level. Thus, stress concentration zones can be identified in advance before large deformation of the rock mass occurs, and they can be supported and reinforced.

[0045] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0046] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0047] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0048] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for inverting the shear mechanical properties of tunnels with small clearance, characterized in that, The specific steps include: S1: Several detection points are symmetrically set on both sides of the middle rock wall of the tunnel to collect displacement parameters at different heights on both sides of the middle rock wall, and the slope angle of the tunnel mountain, the natural unit weight of the rock mass and the actual burial depth of each detection point are collected simultaneously. S2: The actual burial depth and slope angle are combined to correct the lateral pressure coefficient of the tunnel, and the asymmetric lateral pressure coefficient of each detection point is obtained. At the same time, a three-dimensional model of the tunnel is constructed, and the stress tensor is set according to the asymmetric lateral pressure coefficient of each detection point to configure the initial stress environment of the three-dimensional model. The lateral pressure coefficient is obtained from an empirical formula in the theory of earth pressure at rest, specifically the difference between a preset empirical constant and the sine value of the initial value of the internal friction angle. The asymmetric lateral pressure coefficient is the product of the lateral pressure coefficient and the correction factor, plus the lateral pressure coefficient. The correction factor is constructed based on Coulomb's earth pressure theory and the equivalent burial depth theory, and includes three multiplied sub-terms. The first sub-term is a preset terrain correction constant, the second sub-term is the ratio between the difference in actual burial depth of the detection points on both sides of the rock wall at the same height and the axial distance between the tunnel's first and second tunnels, and the third sub-term is the sine value of twice the slope angle. S3: The three-dimensional model is simulated and analyzed based on the finite difference method to generate a simulated displacement gradient that reflects the degree of shear deformation of the middle rock wall. Then, the actual displacement gradient of the middle rock wall is calculated based on the displacement parameters. Combined with the optimization algorithm, the equivalent values ​​of cohesion and internal friction angle are generated respectively. The simulated displacement gradient and the actual displacement gradient are both displacement gradients, calculated from the simulated and measured values ​​of the displacement parameters at the detection points, respectively. The displacement gradient is positively correlated with the difference in displacement parameters between the detection points on both sides of the middle rock wall and negatively correlated with the net thickness of the middle rock wall. When generating equivalent values ​​of cohesion and internal friction angle, the optimization objective is to minimize the error between the simulated displacement gradient and the actual displacement gradient, and the cohesion and internal friction angle of the rock mass are used as optimization variables for optimization. S4: Based on the equivalent value of the internal friction angle and the slope angle, the azimuth angle of the sliding surface of the middle rock wall is generated. Then, by combining the equivalent values ​​of cohesion and internal friction angle, the azimuth angle and the stress tensor of each detection point, the projected shear stress and projected stress of each detection point on the sliding surface are calculated. S5: Generate asymmetric risk factors for each detection point based on the projected shear stress and projected stress on the slip surface. Then, compare the asymmetric risk factors of each detection point with several preset judgment intervals in sequence, and generate a risk cloud map of the tunnel based on the comparison results.

2. The method for inverting the shear mechanical properties of a small-clearance tunnel according to claim 1, characterized in that: Based on the tunnel's excavation location, the two sides of the rock wall in the tunnel are defined as the deep-buried side and the shallow-buried side, respectively. The side closer to the tunnel mountain is the deep-buried side, and the side farther away from the tunnel mountain is the shallow-buried side. The displacement parameters include vertical displacement and horizontal displacement. When collecting displacement parameters, several detection sections are uniformly set along the tunnel axis, and for each detection section, the detection points are uniformly and symmetrically set on both sides of the middle rock wall.

3. The method for inverting the shear mechanical properties of a small-clearance tunnel according to claim 2, characterized in that: When configuring the initial stress environment of the 3D model, an initial value for the stress tensor needs to be set for each detection point. This stress tensor includes horizontal stress, vertical self-weight stress, and shear stress, where: The initial value of the vertical self-weight stress is the product of the natural unit weight of the rock mass and the actual burial depth of the detection point; The initial value of the horizontal stress is the product of the asymmetric lateral pressure coefficient and the vertical self-weight stress; The initial value of the shear stress is the product of the tangent of the slope angle and the vertical self-weight stress.

4. The method for inverting the shear mechanical properties of a small-clearance tunnel according to claim 3, characterized in that: The azimuth angle of the slip surface of the middle rock wall is obtained based on the Mohr-Coulomb criterion and the Rankine active pressure theory. Specifically, it is 45° plus the equivalent value of half the internal friction angle, and then minus half the slope angle. The azimuth angle is used to reflect the degree to which the slip surface of the middle rock wall deviates from the deep buried side to the shallow buried side under the lateral pressure of the tunnel mountain. The projected shear stress and projected stress of each detection point on the slip surface are calculated by stress transformation formula and are used to represent the projection of the stress tensor of the detection point on the slip surface.

5. The method for inverting the shear mechanical properties of a small-clearance tunnel according to claim 4, characterized in that: The asymmetric risk factors at each testing point are expressed as fractions, where the numerator is the absolute value of the projected shear stress at that testing point, and the denominator is the product of the projected stress and the tangent of the equivalent value of the internal friction angle at that testing point, plus the equivalent value of the cohesion.

6. The method for inverting the shear mechanical properties of a small-clearance tunnel according to claim 5, characterized in that: The logic for generating a risk cloud map for the tunnel based on the comparison results is as follows: The judgment intervals are arranged in ascending order, and are continuous and non-overlapping with each other. Each group of judgment intervals corresponds to a risk level. Sequentially identify the judgment interval of the asymmetric risk factor at each detection point, and assign the risk level of the judgment interval to the corresponding detection point; Each risk level is assigned a color, and in the 3D model of the tunnel, the color is rendered with the detection point as the center and the preset grid length as the radius, thereby generating a risk cloud map of the entire tunnel.

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