Sprayed concrete support parameter adaptability design method considering blasting damage

Abstract

The invention relates to a shotcrete support parameter adaptability design method considering blasting damage, and belongs to the technical field of tunnel engineering. The problems that the friction coefficient value is empirical, parameter design is not matched with the actual working condition and the design accuracy is low due to neglecting of the shape change of the surface of the surrounding rock caused by blasting damage in the prior art are solved. According to the technical scheme, the method comprises the steps of quantifying a surrounding rock roughness coefficient and calculating a friction coefficient through multi-angle image acquisition and image recognition; the lining thickness is determined by combining the clearance requirement, the deformation allowance and the blasting damage risk; establishing a two-way unequal-pressure elastic mechanical model, and solving lining stress distribution based on a stress function and coulomb friction constraint; and taking support cost minimization as a target, and inversely solving the optimal concrete strength grade and reinforcement ratio by adopting an optimization algorithm. Accurate self-adaptive design of support parameters is realized, stress calculation precision is improved, safety is guaranteed, and cost is reduced.

Description

Technical Field

[0001] This invention belongs to the field of tunnel engineering technology and relates to an adaptive design method for shotcrete support parameters that takes into account blasting damage. Background Technology

[0002] After tunnel blasting excavation, the surface morphology of the surrounding rock exhibits significant irregularities. Its roughness directly affects the interfacial friction characteristics between the surrounding rock and the shotcrete lining, thus influencing the load-bearing efficiency of the support structure. Existing shotcrete lining design methods for tunnels often rely on engineering experience or simplified mechanical models, failing to fully consider the actual changes in the surrounding rock surface morphology caused by blasting damage and neglecting the impact of surrounding rock roughness on the contact friction coefficient and stress distribution. This leads to a mismatch between the design parameters and actual engineering conditions. This mismatch manifests as low design accuracy and poor adaptability, often resulting in insufficient load-bearing efficiency or wasted costs in the support structure.

[0003] Traditional design methods often lack quantitative analysis of the surface roughness of the surrounding rock, and the friction coefficient is usually based on empirical assumptions, failing to accurately calculate the actual profile after blasting damage. Furthermore, the determination of lining thickness does not adequately consider clearance requirements, allowances for surrounding rock deformation, and the risk of spalling due to blasting damage, potentially leading to conservative design or safety risks. Regarding mechanical models, existing technologies often employ simplified assumptions, failing to fully consider the frictional characteristics between the surrounding rock and lining interface and the biaxial unequal compressive stress conditions, resulting in stress distribution calculations that deviate from reality.

[0004] The present invention aims to solve the above-mentioned technical problems by introducing image recognition technology to quantify the surface roughness of the surrounding rock, and combining it with mechanical analysis and optimization algorithms to achieve adaptive optimization design of support parameters, thereby improving the adaptability of the support structure to engineering practice. Summary of the Invention

[0005] In view of this, the purpose of this invention is to provide an adaptive design method for shotcrete support parameters that takes into account blasting damage. By accurately quantifying the surface characteristics of the surrounding rock after blasting, combined with mechanical analysis and optimization calculations, suitable support parameters are derived in reverse, thereby improving the adaptability of the support structure design to engineering practice.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] An adaptive design method for shotcrete support parameters considering blast damage includes the following steps: Step 1: Multi-angle image acquisition is performed on the surface of the surrounding rock of the tunnel after blasting excavation, and the surface contour of the surrounding rock is extracted using image recognition technology. The surface roughness coefficient of the surrounding rock is then calculated based on the extracted contour. The friction coefficient between the surrounding rock and the lining is calculated according to a pre-defined quadratic polynomial formula. ; Step two: Taking into account the tunnel design clearance requirements, the allowable deformation of the surrounding rock, and the risk of blasting damage and spalling, the minimum design thickness of the shotcrete lining is determined through clearance matching calculations. ; Step 3: The surrounding rock-lining structure is simplified into a biaxial unequal pressure elastic mechanical model containing circular holes in an infinitely large body. The control equation is established using stress functions, and nonlinear constraints are introduced based on the Coulomb friction model. The stress distribution of the lining is solved by numerical optimization method. Step four: Based on the lining stress distribution obtained in step three, establish an optimization equation with the goal of minimizing support cost, reverse-engineer the shotcrete strength grade and reinforcement ratio, and solve for the optimal parameters through an optimization algorithm to complete the adaptive design of support parameters.

[0008] Furthermore, in step one, the roughness coefficient The calculation formula is ,in This represents the actual area of ​​the surrounding rock structural surface morphology. This represents the nominal area of ​​the surrounding rock surface.

[0009] Furthermore, in step one, the coefficient of friction The calculation formula is .

[0010] Furthermore, in step two, the minimum design thickness The calculation formula is ,in This represents the maximum difference between the actual contour of the surrounding rock and the design clearance line. This indicates the allowance for surrounding rock deformation. This indicates the allowable amount of spalling due to blasting damage.

[0011] Furthermore, in step three, the stress function Represented as ,in and Let represent the radius and angle of any point on the tunnel, respectively. These are coefficients to be determined.

[0012] Furthermore, in step three, the governing equations include 13 equations established based on stress boundary conditions, displacement boundary conditions, and the uniqueness of undetermined coefficients. The numerical optimization method employs MATLAB software. fmincon The function is used to solve the problem.

[0013] Furthermore, in step three, the nonlinear constraint condition is established based on the Coulomb friction model, and its expression is: ,in Indicates radial stress. This represents the tangential shear stress.

[0014] Furthermore, in step four, the objective function of the optimization equation is: ,in This represents the concrete construction loss coefficient. Indicates the lining volume. This indicates the unit price of concrete. This represents the steel reinforcement loss coefficient during construction. Indicates the total mass of the reinforcing steel bars. This indicates the unit price of steel bars.

[0015] Furthermore, in step four, the optimization algorithm is solved using the Particle Swarm Optimization (PSO) algorithm.

[0016] Furthermore, in step four, the inversely calculated shotcrete strength grade and reinforcement ratio must meet the constraint condition: tangential shear stress. Circumferential normal stress ,and ,in This represents the standard value of the axial compressive strength of concrete.

[0017] The beneficial effects of this invention are as follows: (1) In traditional design methods, the friction coefficient of the interface between the surrounding rock and the lining often relies on empirical estimation, which fails to truly reflect the actual roughness of the surrounding rock surface after blasting excavation. This invention innovatively uses multi-angle image acquisition and image recognition technology to accurately extract the contour of the surrounding rock surface after blasting, and quantitatively calculates the roughness coefficient based on the contour data. Furthermore, through experimentally verified quadratic polynomial relations... Scientific determination of friction coefficient This technical approach fundamentally solves the problem of relying on empirical values ​​for the friction coefficient, making the boundary conditions in subsequent mechanical analysis more consistent with engineering realities and significantly improving the calculation accuracy of the stress distribution state of the lining.

[0018] (2) In determining the thickness of the shotcrete lining, this invention does not consider a single factor in isolation, but creatively integrates the tunnel design clearance requirements, the actual surrounding rock contour obtained after blasting, the allowable amount of surrounding rock deformation, and the risk of surrounding rock spalling caused by blasting damage in a systematic way. The minimum design thickness is determined through clearance matching calculation. h min The method sets a reasonable range for lining thickness. This ensures that the lining thickness fully meets the safety requirements of tunnel clearance, effectively avoids the risks caused by insufficient thickness, and avoids material waste and cost increases caused by overly conservative design, thus achieving the optimal balance between safety and economy.

[0019] (3) This invention abandons the traditional simplified mechanical model and innovatively simplifies the surrounding rock-lining structure into a biaxial unequal pressure elastic mechanical model containing circular holes in an infinitely large object. This model more realistically simulates the complex geostress environment of the tunnel. By introducing the stress function proposed by A. Bobet and establishing a set of governing equations, combined with the Coulomb friction model (obtained scientifically) The nonlinear constraints, constructed with the lining as the core, are solved using numerical optimization algorithms (such as the fmincon function in MATLAB). This complete mechanical analysis system successfully overcomes the complex mechanical calculation problems caused by irregular cross-sections, material nonlinearity, and contact surface friction characteristics. The derived stress expressions can accurately reflect the influence of each parameter on the lining stress, providing a reliable and solid theoretical foundation for parameter optimization.

[0020] (4) This invention transforms the engineering design problem into a clear mathematical optimization problem. Based on the accurate stress distribution obtained in step three, and with the constraints of meeting all strength and stability requirements, an optimization equation is established with the clear objective of minimizing the total support cost. Then, intelligent algorithms such as Particle Swarm Optimization (PSO) are used for efficient solution, automatically retrieving the optimal shotcrete strength grade, reinforcement ratio, and other key parameters. This optimization design mode can not only significantly reduce material and construction costs while ensuring the strength, durability, and construction feasibility of the support structure, but also transform the design process from repeated trial and error based on experience to rapid optimization based on models, greatly improving design efficiency and scientific rigor.

[0021] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0022] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein: Figure 1 This is a schematic diagram of the invention; Figure 2 This is a flowchart of the present invention; Figure 3 These are the locations of various points in the surrounding rock of the tunnel after blasting excavation; Figure 4 This provides surface information of various points in the surrounding rock of the tunnel after blasting excavation. Figure 5 Images of various points in the surrounding rock of the tunnel after blasting excavation. Detailed Implementation

[0023] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0024] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures. They should not be construed as limiting the invention. To better illustrate the embodiments of the invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0025] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "front," and "rear" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present invention. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0026] This invention includes the following steps: Step 1: Take photos of the surrounding rock surface of the tunnel after blasting excavation from multiple angles to obtain clear images of the surrounding rock surface; use image recognition technology to perform visual analysis on the acquired images, remove image noise and redundant background, and extract the actual contour lines of the surrounding rock surface; based on the extracted surface contours, obtain the actual area of ​​the surrounding rock structural surface morphology. With nominal area Thus, the surface roughness coefficient of the surrounding rock can be calculated. This allows for a quantitative analysis of the surface roughness of the surrounding rock; furthermore, the corresponding friction coefficient is calculated using a quadratic polynomial. Its expression is:

[0027] Step 2: Combining the tunnel design clearance requirements and the actual contour of the surrounding rock after blasting, and considering the allowable deformation of the surrounding rock and the risk of rock spalling due to blasting damage, determine the minimum design thickness of the shotcrete lining through clearance matching calculations. At the same time, based on engineering experience and specification requirements, a reasonable range of values ​​for the lining thickness is set to ensure that the lining thickness can meet the clearance requirements and provide a foundation for subsequent stress bearing.

[0028] Step 3: Simplify the tunnel surrounding rock-lining structure into a biaxial unequal pressure elastic mechanical model containing circular holes in an infinitely large body, where the lining is a uniform, isotropic elastic body and the surrounding rock is a nonlinear elastic body after blasting damage. Figure 1 middle, Let be the inner radius of the lining. The outer radius of the lining is denoted by , and both are average values ​​from the surface point to the geometric center point. The lateral pressure coefficient, This represents the vertical force component of the surrounding rock.

[0029] Based on the stress function proposed by A. Bobet, the stress function under isotropic conditions... Available undetermined coefficients Represented as:

[0030] In the formula: , These represent the radius and angle of any point on the tunnel, respectively.

[0031] Based on stress, displacement boundary conditions, and undetermined coefficients To ensure uniqueness, the following 13 equations are established:

[0032] Based on the above 13 equations, we need to solve 14 unknowns. When the number of equations is less than the number of unknowns, there are usually infinitely many solutions. MATLAB can be used to find the optimal or approximate solution to the system of equations through optimization methods. Given that friction problems involve linear and nonlinear relationships, as well as equality and inequality relationships, the fmincon function can be used for solving them. The basic form of its objective function f(x) can be expressed as:

[0033] Where A and B are the coefficient matrix and constant vector in the linear inequality constraint, respectively; Aeq and Beq are the coefficient matrix and constant vector in the linear equality constraint, respectively; C(x) and Ceq(x) are the nonlinear inequality constraint and the nonlinear equality constraint function, respectively; lb and ub are the variables... xThe lower and upper bounds of the constraint.

[0034] Based on the actual engineering requirements, to ensure the overall safety of the tunnel, the shear stress between the surrounding rock and the lining must not exceed the maximum static friction force that the materials can withstand. The contact surface must conform to the Coulomb friction model, combined with the friction coefficient obtained in step 1. Establish the inequality relationship between shear stress and radial stress on the contact surface:

[0035] Based on the Coulomb friction model, a nonlinear inequality Ceq(x) is established for solving the fmincon function, and the function is transformed into a minimization problem, i.e.:

[0036] The stress distribution expression for shotcrete lining is derived as follows:

[0037] Step 4: Using the lining stress distribution expression obtained in Step 3 as the core, and combining it with the load-bearing requirements of shotcrete support, establish an optimization equation to inversely calculate key strength parameters such as shotcrete strength grade and reinforcement ratio; set the optimization objective as minimizing support cost, and use the particle swarm optimization algorithm to solve for the optimal parameters. The objective function is:

[0038] In the formula: This is the concrete construction loss coefficient. For the lining volume, This refers to the unit price of concrete. This is the steel reinforcement construction loss coefficient. The total mass of the reinforcing steel bars. This refers to the unit price of steel bars.

[0039] Substitute the optimal parameters obtained through iteration into the stress expression in step 3 to verify whether the lining stress meets the bearing requirements. If it does not meet the requirements, readjust the constraints of the optimization equation until the appropriate support strength parameters are obtained, thus completing the adaptive design of the shotcrete support parameters. Figure 2 This is a flowchart of the present invention.

[0040] Example Step 1: Image acquisition and friction coefficient calculation of the surrounding rock surface like Figure 3 and Figure 4 As shown, the surface of the tunnel surrounding rock after blasting and excavation is photographed from multiple angles using a camera to obtain surface information at each point.

[0041] like Figure 5As shown, digital image processing is performed on the images collected at each point to obtain the processed image, and the surface contour of the surrounding rock is further extracted; based on the extracted surface contour, the actual area of ​​the surrounding rock structural surface morphology is obtained. With nominal area Calculate the roughness Furthermore, using quadratic polynomials Calculate the corresponding coefficient of friction, i.e. .

[0042] Step 2: Determining the minimum design thickness of the lining Based on the tunnel design clearance requirements, the design clearance width of this tunnel is... ,high Based on the design conventions for single-centered circular clearance sections, the design clearance radius is determined to be 8.60m; and using the actual contour line of the surrounding rock extracted in step one, the maximum difference between the actual contour line and the design clearance line is calculated. Considering the allowance for deformation of Class IV surrounding rock. Explosion damage spalling allowance The minimum design thickness of the lining is determined through clearance matching calculations. Based on engineering experience and standard limits, the lining thickness is set within the range of [0.20m, 0.26m] to ensure both clearance safety and structural stress requirements.

[0043] Step 3: Establishing the mechanical model and solving for stress distribution The tunnel surrounding rock-lining structure is simplified into an infinitely large biaxial unequal pressure elastic mechanical model containing circular holes; the elastic modulus of shotcrete is taken as E=28GPa, Poisson's ratio μ=0.2, and the elastic modulus of surrounding rock is... Based on the regional geological survey report, the maximum principal stress is set according to the geostress conditions. minimum principal stress The stress function proposed by A. Bobet is adopted. Thirteen governing equations were established based on stress and displacement boundary conditions; since the number of equations was less than the number of unknowns, MATLAB was used. fmincon Function solving, setting variable constraint range , And based on the Coulomb friction model, nonlinear constraints were established. ( This ensures that no sliding failure occurs at the contact surface. Substituting the above parameters and constraints, all undetermined coefficients are calculated, and the expression for the lining stress distribution is derived, yielding the key stress index: maximum circumferential normal stress. Maximum radial normal stress Maximum tangential shear stress .

[0044] Step 4: Optimization and Verification of Support Parameters With the goal of minimizing support costs, the optimization function is established as follows:

[0045] in: , unit price of steel bars .

[0046] Constraints: Shotcrete type C20~C35, reinforcement ratio 0.1%~0.3%, lining thickness 0.20~0.26m, tangential shear stress , , The Particle Swarm Optimization (PSO) algorithm was used to solve the problem. The algorithm parameters were set as follows: number of particles 50, number of iterations 100, and inertia weight. Learning factor After iterative optimization, the key parameter for minimizing the objective function is: concrete type C25 (…). , , ), reinforcement ratio Lining thickness .

[0047] The design parameters were verified. , , All constraints are met, indicating that the support parameters are designed reasonably.

[0048] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for adaptive design of shotcrete support parameters considering blast damage, characterized in that: Includes the following steps: Step 1: Multi-angle image acquisition is performed on the surface of the surrounding rock of the tunnel after blasting excavation, and the surface contour of the surrounding rock is extracted using image recognition technology. The surface roughness coefficient of the surrounding rock is then calculated based on the extracted contour. The friction coefficient between the surrounding rock and the lining is calculated according to a pre-defined quadratic polynomial formula. ; Step two: Taking into account the tunnel design clearance requirements, the allowable deformation of the surrounding rock, and the risk of blasting damage and spalling, the minimum design thickness of the shotcrete lining is determined through clearance matching calculations. ; Step 3: The surrounding rock-lining structure is simplified into a biaxial unequal pressure elastic mechanical model containing circular holes in an infinitely large body. The control equation is established using stress functions, and nonlinear constraints are introduced based on the Coulomb friction model. The stress distribution of the lining is solved by numerical optimization method. Step four: Based on the lining stress distribution obtained in step three, establish an optimization equation with the goal of minimizing support cost, reverse-engineer the shotcrete strength grade and reinforcement ratio, and solve for the optimal parameters through an optimization algorithm to complete the adaptive design of support parameters.

2. The adaptive design method for shotcrete support parameters considering blasting damage according to claim 1, characterized in that: In step one, the roughness coefficient The calculation formula is ,in This represents the actual area of ​​the surrounding rock structural surface morphology. This represents the nominal area of ​​the surrounding rock surface.

3. The adaptive design method for shotcrete support parameters considering blasting damage according to claim 2, characterized in that: In step one, the coefficient of friction The calculation formula is .

4. The adaptive design method for shotcrete support parameters considering blasting damage according to claim 1, characterized in that: In step two, the minimum design thickness The calculation formula is ,in This represents the maximum difference between the actual contour of the surrounding rock and the design clearance line. This indicates the allowance for surrounding rock deformation. This indicates the allowable amount of spalling due to blasting damage.

5. The adaptive design method for shotcrete support parameters considering blasting damage according to claim 1, characterized in that: In step three, the stress function Represented as ,in and Let represent the radius and angle of any point on the tunnel, respectively. These are coefficients to be determined.

6. The adaptive design method for shotcrete support parameters considering blasting damage according to claim 5, characterized in that: In step three, the governing equations include 13 equations established based on stress boundary conditions, displacement boundary conditions, and the uniqueness of undetermined coefficients. The numerical optimization method employs MATLAB software. fmincon The function is used to solve the problem.

7. The adaptive design method for shotcrete support parameters considering blasting damage according to claim 6, characterized in that: In step three, the nonlinear constraint condition is established based on the Coulomb friction model, and its expression is: ,in Indicates radial stress. This represents the tangential shear stress.

8. The adaptive design method for shotcrete support parameters considering blasting damage according to claim 1, characterized in that: In step four, the objective function of the optimization equation is: ,in This represents the concrete construction loss coefficient. Indicates the lining volume. This indicates the unit price of concrete. This represents the steel reinforcement loss coefficient during construction. Indicates the total mass of the reinforcing steel bars. This indicates the unit price of steel bars.

9. The adaptive design method for shotcrete support parameters considering blast damage according to claim 8, characterized in that: In step four, the optimization algorithm is solved using the particle swarm optimization algorithm (PSO).

10. The adaptive design method for shotcrete support parameters considering blasting damage according to claim 1, characterized in that: In step four, the inversely calculated shotcrete strength grade and reinforcement ratio must meet the constraint condition: tangential shear stress. Circumferential normal stress ,and ,in This represents the standard value of the axial compressive strength of concrete.

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