Tunnel perimeter hole blasting parameter optimization method, storage medium and computer equipment

Abstract

The present invention relates to the field of rock and soil blasting technology, and more specifically to a method, storage medium, and computer equipment for optimizing tunnel perimeter hole blasting parameters. The blasting parameter optimization method comprises the following steps: obtaining tunnel perimeter hole blasting parameters; inputting the tunnel perimeter hole blasting parameters into a finite element-block discrete element coupled physical model for parameter optimization to obtain optimized parameters; and optimizing the perimeter hole spacing and charge amount parameters under different joint densities based on establishing a finite element-block discrete element coupled physical model under different joint densities. The present invention can provide optimization schemes for various joint densities. When excavating to different locations, the optimization scheme can be directly adopted based on the measured joint density, thereby reducing the time spent on downtime waiting for the optimization scheme to be formulated.

Description

Technical Field

[0001] The present invention relates to the technical field of rock and soil blasting, and in particular to a method for optimizing tunnel perimeter hole blasting parameters, a storage medium and a computer device. Background Art

[0002] Whether it is a railway or highway tunnel, over-excavation and under-excavation are common phenomena during construction. Frequent over-excavation and under-excavation during tunnel blasting are mainly caused by the heterogeneity and anisotropy of natural rock masses. Natural rock masses are not homogeneous and contain a large number of defects such as joints, cracks, and faults. Among geological conditions, joints and cracks have the most significant impact on the blasting effect of rock masses. Joint density refers to the density of joint development in the rock mass. If the design of smooth blasting hole parameters and charging parameters does not have sufficient understanding of the surrounding rock geological conditions such as joint density, the uneven propagation of the explosive energy will inevitably lead to severe damage to the surrounding rock after the blast and phenomena such as over-excavation and under-excavation. Summary of the Invention

[0003] The present invention aims to provide a method, storage medium, and computer device for optimizing tunnel perimeter blasting parameters to address the technical problems encountered in prior art tunnel blasting, such as insufficient understanding of surrounding rock geological conditions such as joint density in the design of smooth blasting hole parameters and charge parameters, and the uneven propagation of explosive energy, which leads to significant post-blast damage to the surrounding rock and over-excavation and under-excavation. The specific technical solution is as follows:

[0004] The present invention provides a method for optimizing tunnel perimeter blasting parameters, comprising the following steps:

[0005] Obtain the tunnel perimeter blasting parameters;

[0006] The tunnel perimeter blasting parameters are input into the finite element-block discrete element coupled physical model for parameter optimization to obtain the optimized parameters;

[0007] The construction of the finite element-block discrete element coupled physical model includes the following steps:

[0008] S1. Establish a finite element-block discrete element coupled physical model;

[0009] S2. Determine the parameters, equivalent blasting loads and boundary conditions of the finite element-block discrete element coupled physical model;

[0010] S3. Balancing the initial geostress: Specifically, setting static boundaries, setting both sides and the bottom of the finite element-block discrete element coupled physical model as fixed boundaries, and using a stress boundary on the top to simulate the overlying soil;

[0011] Remove the rock mass within the line connecting the surrounding eyes to simulate tunnel excavation;

[0012] The equivalent blasting load in S2 is applied to the tunnel contour surface, the blasting numerical calculation is performed, and the boundary of the finite element-block discrete element coupled physical model is replaced by a viscous boundary;

[0013] S4. Verify the validity of the finite element-block discrete element coupled physical model by comparing the blasting numerical calculation results obtained in S3 with the field test results. If the conditions are met, directly output the model; if not, redefine the parameters, equivalent blasting loads, and boundary conditions of the finite element-block discrete element coupled physical model.

[0014] Parameter optimization specifically includes optimizing the peripheral eye spacing and charge parameters, specifically: increasing the peripheral eye spacing and reducing the charge in preset steps, setting multiple different values ​​for each, first optimizing the peripheral eye spacing, extracting the over-excavation data under each working condition, and drawing a comparison chart of the over-excavation of each part, determining the optimized peripheral eye spacing based on the comparison of the over-excavation situation, and then optimizing the charge under the optimized peripheral eye spacing, and determining the optimized charge.

[0015] A further improvement of the tunnel perimeter blasting parameter optimization method of the present invention is that S1 specifically includes using a joint and fissure model (block discrete element model) within the tunnel influence area to reflect the characteristics of the fragmented rock mass. First, a DFN model is established based on the joint development characteristics and statistical characteristic values ​​of the joint and fissure rock mass, and then the generated random cracks are used to cut the internal rock mass; a continuous medium model is used outside the influence area, and the equivalent transfer law of nodal force and displacement is adopted, and finally a finite element-block discrete element coupled physical model is constructed to simulate the numerical value of the fragmented rock mass.

[0016] The further improvement of the tunnel perimeter blasting parameter optimization method of the present invention is that S2 specifically includes determining the microscopic parameters of the finite element-block discrete element coupling physical model and the equivalent mechanical parameters of rock masses with different joint densities; simulating the blasting load by applying an equivalent stress time history on the equivalent elastic boundary; and adopting a viscous boundary as the deformation boundary of the finite element-block discrete element coupling physical model, and setting an independent damper at the boundary.

[0017] The present invention further improves the tunnel perimeter blasting parameter optimization method in that, when simulating the blasting load by applying the equivalent stress time history method on the equivalent elastic boundary, according to the Chapman-Jouguet condensed explosive detonation wave model, the initial detonation pressure peak value P0 for the uncoupled charge acting on the blasthole wall is:

[0018]

[0019] Where: ρ0 is the density of explosive, D is the detonation velocity of explosive, a is the diameter of the cartridge, b is the diameter of the blast hole, γ is the specific heat capacity of the detonation gas (γ = 3);

[0020] The parameters of the explosive material selected for blasting are brought into it and then into the simplified triangular load function P D (t):

[0021] P D (t) = P0f(t);

[0022]

[0023] Then based on P D (t) Get the equivalent blasting load P e (x,t):

[0024]

[0025] Where: f(t) represents the transfer function, t represents the load time, t r Indicates the load rise time, t z represents the total time of loading, x represents the loading distance, r0 represents the blasthole radius, L s Indicates the peripheral hole spacing;

[0026] Finally, the equivalent blasting load boost time and total action time are obtained.

[0027] A further improvement of the tunnel perimeter blasting parameter optimization method of the present invention is that Rayleigh damping is used to reduce the amplitude of the natural vibration mode of the system when the linear spring-damper model is used to set the unit as the boundary condition. It is assumed that the damping matrix C is linearly related to the stiffness matrix M and the mass matrix K:

[0028] [C]=α[M]+β[K];

[0029] α=ξ min ω min ;

[0030] β=ξ min / ω min ;

[0031] Where: α is the mass damping proportional coefficient, β is the stiffness damping proportional coefficient, ξ min is the critical damping ratio, ω min is the circular frequency corresponding to the critical damping ratio;

[0032] The mass damping proportional coefficient is set to zero (α=0), and only the stiffness damping proportional coefficient (β) is considered; ξ min Take 2%-5%;

[0033] The deformation boundary of the finite element-block discrete element coupled physical model is set as a viscous boundary as a boundary condition. An independent damper is set at the boundary to provide viscous traction. The calculation formula is as follows:

[0034] t n =-ρC n v n ;

[0035] t s =-ρC s v s ;

[0036] Where: t n is the normal traction force on the boundary, t s is the tangential traction force on the boundary, v s is the normal component of the boundary velocity, v n is the tangential component of the boundary velocity, ρ is the mass density, C n is the longitudinal wave velocity, C s is the shear wave velocity.

[0037] A further improvement of the tunnel perimeter eye blasting parameter optimization method of the present invention lies in that S5 specifically comprises: based on the method of S1, the mass-density keyword built into the DFN model is used for step-by-step control to establish two blasting models with different joint densities, wherein the parameters of the finite element-block discrete element coupling physical model adopt the equivalent mechanical parameters of the rock mass with different joint densities obtained in S2, and the initial ground stress of the model is balanced according to S3; the rock mass within the perimeter eye connection line is removed; the equivalent blasting load is applied to the tunnel contour surface, and the blasting numerical calculation is performed.

[0038] A further improvement of the tunnel perimeter hole blasting parameter optimization method of the present invention is that, in the parameter optimization of the perimeter hole spacing and charge amount under different joint densities using the S4 method, the corresponding optimized parameters are selected according to the rock joint density at different excavation advances in engineering practice.

[0039] The present invention also provides a readable storage medium storing a computer program, wherein the computer program is suitable for being loaded by a processor and executing the above-mentioned tunnel perimeter hole blasting parameter optimization method.

[0040] The present invention also provides a computer device, which includes a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the above-mentioned tunnel perimeter hole blasting parameter optimization method is executed.

[0041] The application of the technical solution of the present invention has the following beneficial effects:

[0042] The tunnel perimeter blasting parameter optimization method of the present invention determines the numerical model parameters by taking into account the actual joint density, thereby improving the accuracy of the numerical model. It adopts a finite element-block discrete element coupled physical model to improve the computational efficiency of the numerical model and achieve accurate simulation at the engineering scale. It proposes a method for determining the location and degree of tunnel overexcavation by comprehensively considering the rock mass strain rate and strain increment. The effectiveness of the model is verified by comparing it with the actual overexcavation situation on site. It also provides optimization schemes under various joint density conditions. When excavating to different locations, the optimization scheme can be directly adopted according to the measured joint density. , that is, the optimized peripheral eye spacing and charging amount, reducing the time of suspension waiting for the formulation of the optimization plan; compared with the existing blasting parameter optimization method, the present invention takes into account the influence of joint density on the blasting effect of the tunnel peripheral eyes based on the finite element-block discrete element coupling physical model, making the blasting parameter optimization more efficient, and improving the accuracy of the parameter optimization results. It solves the technical problems in the prior art of tunnel blasting, that is, the design of smooth blasting hole parameters and charging parameters is insufficient to understand the surrounding rock geological conditions such as joint density, and the uneven propagation of explosion energy leads to large surrounding rock damage after blasting, over-excavation and under-excavation, etc.

[0043] In addition to the above-described objects, features and advantages, the present invention has other objects, features and advantages. The present invention will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0045] Figure 1 It is a flow chart of the tunnel perimeter hole blasting parameter optimization method of the present invention;

[0046] Figure 2 Schematic diagram of the finite element-block discrete element coupled physical model of the tunnel perimeter hole blasting parameter optimization method of the present invention;

[0047] Figure 3 yes Figure 2 Enlarged view of frame A in the middle;

[0048] Figure 4 It is the equivalent blasting load coordinate diagram of the tunnel perimeter hole blasting parameter optimization method of the present invention;

[0049] Figure 5 It is an over-excavation discrimination diagram of a discrete element model of a tunnel perimeter eye blasting parameter optimization method according to the present invention.

[0050] Among them, 1 represents joints. DETAILED DESCRIPTION

[0051] The following detailed description of the embodiments of the present invention is given in conjunction with the accompanying drawings, clearly and completely describing the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0052] See also Figures 1 to 5 As shown, a method for optimizing tunnel perimeter blasting parameters includes the following steps:

[0053] Obtain the tunnel perimeter blasting parameters;

[0054] The tunnel perimeter blasting parameters are input into the finite element-block discrete element coupled physical model for parameter optimization to obtain the optimized parameters;

[0055] The construction of the finite element-block discrete element coupled physical model includes the following steps:

[0056] S1. Establish a finite element-block discrete element coupled physical model;

[0057] S2. Determine the parameters, equivalent blasting loads and boundary conditions of the finite element-block discrete element coupled physical model.

[0058] Among them, steps S1 and S2 are obtained by the method of application number 202411062690.3, entitled "A method for determining equivalent mechanical parameters of jointed and fissured rock mass", which is as follows:

[0059] Step 1: Select the jointed and fissured rock mass for which the equivalent mechanical parameters need to be determined; remove the intact rock block without joints from the jointed and fissured rock mass to obtain the mechanical parameters of the intact rock block; obtain the joint development characteristics and statistical characteristic values ​​of the jointed and fissured rock mass; specifically, conduct an indoor compression test on the intact rock block to obtain the mechanical parameters of the intact rock block including elastic modulus, Poisson's ratio, uniaxial compressive strength, cohesion and internal friction angle.

[0060] Obtaining the joint development characteristics and statistical characteristic values ​​of jointed and fissured rock masses includes the following steps:

[0061] Step 1.1, collecting joint geometric characteristic data of the jointed and fissured rock mass, including joint dip, joint inclination, joint spacing, and joint trace length;

[0062] Step 1.2: Draw a joint rose diagram based on the joint geometric characteristic data obtained in step 1.1, divide the joints into dominant groups, and obtain dominant joint information;

[0063] The QQ plot is used to test the four distribution models of normal distribution, lognormal distribution, exponential distribution and uniform distribution for each parameter in the joint geometric characteristic data, and the most appropriate distribution model is selected.

[0064] Step 1.3, draw the frequency histogram of the joint geometric characteristic data, combine it with the most appropriate distribution model and fit it to obtain the corresponding probability density curve;

[0065] Step 1.4: Obtain joint development characteristics based on the probability density curve, joint geometric characteristic data, and dominant joint information; obtain statistical characteristic values ​​of joint development characteristics of the jointed and fissured rock mass, including joint occurrence, joint trace length, and joint spacing, based on the probability density curve.

[0066] Step 2: Based on the joint development characteristics and statistical characteristic values ​​in step 1, the weakening law of the jointed and fissured rock mass and the size of the characterizing unit body are obtained;

[0067] The weakening laws of the jointed and fissured rock mass obtained in step 2 specifically include:

[0068] Step 2.1.1: Based on the dominant joint information obtained in step 1.2, the joint attitude is transformed into joint angle using the plane unit normal vector; and joint network models with different numbers of joints are established using CAD.

[0069] Step 2.1.2, obtaining a joint model entity based on the joint network model obtained in step 2.1.1; obtaining a jointed rock specimen based on the joint model entity;

[0070] Step 2.1.3: Perform a uniaxial compression test on the rock-like specimen obtained in step 2.1.2. Calculate the elastic modulus and peak strength based on the stress-strain curve. Use the following equation to fit the elastic modulus and peak strength to obtain the weakening law of the jointed and fissured rock mass:

[0071]

[0072] Where: E0 is the elastic modulus of the weakened rock mass, σ f0 is the peak strength of the weakened rock mass, E i is the elastic modulus of the intact rock mass, σ fi is the peak strength of the intact rock block, n is the number of joints, and a is the average length of the joints.

[0073] The second step of obtaining the characterization unit size of the jointed and fissured rock mass includes the following steps:

[0074] Step 2.2.1: Establish a discrete fracture network model based on the joint development characteristics and statistical characteristic values ​​of joint dip, joint inclination, joint density, and joint length obtained in step 1.4;

[0075] Step 2.2.2: Use block discrete element software to construct a cubic specimen. Use the discrete fracture network model obtained in step 2.2.1 to cut the cubic specimen. Obtain cubic units with a side length of L at different spatial locations within the cubic specimen to obtain discrete element specimens of the jointed and fractured rock mass. The values ​​of L are 1 m, 2 m, 4 m, 6 m, 8 m, 10 m, 12 m, and 14 m.

[0076] Step 2.2.3. Conduct uniaxial compression numerical tests on the discrete element specimens obtained in step 2.2.2 to obtain the mechanical parameters of discrete element specimens of different sizes. Draw a graph with the vertical axis being the mechanical parameters of the discrete element specimens and the horizontal axis being the side length scale. The horizontal axis where the curve tends to be stable represents the unit body size.

[0077] Step 3: Based on the mechanical parameters of the intact rock block, the joint development characteristics and their statistical characteristic values, and the weakening law of the jointed and fissured rock mass, the strength and deformation parameters of the jointed and fissured rock mass are obtained. Specifically, according to the average joint length information, uniaxial compressive strength and elastic modulus of the intact rock block obtained from on-site statistics, the strength and deformation parameters of the jointed and fissured rock mass (i.e., the elastic modulus of the weakened rock mass and the peak strength of the weakened rock mass) are calculated using the obtained joint weakening law.

[0078] Step 4: Based on the mechanical parameters of the intact rock block obtained in step 1, the characterization unit size obtained in step 2, and the elastic modulus and peak strength of the weakened rock mass obtained in step 3, a trial-and-error method is used to obtain the joint mechanical parameters including stiffness, cohesion, and internal friction angle; a triaxial compression test is carried out to obtain the cohesion and internal friction angle of the jointed and fissured rock mass.

[0079] In step 4, the mechanical parameters of the joints are obtained by trial and error based on the mechanical parameters of the complete rock block obtained in step 1, the characterization unit size obtained in step 2, and the strength and deformation parameters of the jointed and fissured rock mass obtained in step 3, specifically comprising the following steps:

[0080] Step 4.1. Establish a discrete element numerical model representing the unit volume size obtained in step 2, input the mechanical parameters of the intact rock mass obtained in step 1 and the joint mechanical parameters obtained in step 4, and the strength and deformation parameters of the jointed and fissured rock mass obtained in step 3 as target parameters;

[0081] Step 4.2: Conduct uniaxial compression numerical tests on the discrete element numerical model to obtain stress-strain curves. Based on the stress-strain curves, obtain the elastic modulus E and peak strength σ of the simulated rock mass. f ;

[0082] Step 4.3: Make a judgment, specifically: when |weakened rock mass elastic modulus E0-simulated rock mass elastic modulus E| / weakened rock mass elastic modulus E0≤δ1 and |weakened rock mass peak strength σ f0-Simulated rock mass peak strength σ f | / Weakened rock mass peak strength σ f0 When ≤δ2, it is determined that the requirements are met and the joint mechanical parameters are output; otherwise, it is determined that the requirements are not met, and the data of stiffness, cohesion and internal friction angle are adjusted, and the process returns to step 4.2; where: δ1 and δ2 are set thresholds.

[0083] The above are the detailed operation steps of S1 and S2. For specific embodiments, please refer to the embodiment with application number 202411062690.3, entitled "A method for determining equivalent mechanical parameters of jointed and fissured rock mass", which will not be repeated here.

[0084] Furthermore, in S1, based on the application number 202411062690.3, entitled “A method for determining equivalent mechanical parameters of jointed and fissured rock mass”, the joint development characteristics and statistical characteristic values ​​of the jointed and fissured rock mass are obtained, and the geometric parameter distribution characteristics and statistical characteristic values ​​of the joints are obtained as shown in Table 1. The above data are used to calculate the joint density of this section, and the number of joints per unit volume P is obtained. 30 is 4.35, the joint area per unit volume P 32 It is 5.8, from which we can know that the joint density is level II.

[0085] Table 1 Statistical eigenvalues ​​of joint geometric parameters

[0086]

[0087]

[0088] In the table, NE indicates northeast direction, and SE indicates southeast direction.

[0089] The lateral size of the model is 60m×60m. The tunnel is buried at a depth of 285m. The overlying rock and soil is realized by applying equivalent uniformly distributed stress on the top of the model. The horizontal tectonic stress is represented by the lateral pressure coefficient. The lateral pressure coefficient is selected as 0.5 according to the on-site ground stress report. Fixed boundaries are used on both sides and the bottom of the model. In the tunnel influence area, a joint and fissure model (block discrete element model) is used to reflect the characteristics of the fragmented rock mass. First, a DFN model is established based on the joint development characteristics and statistical characteristic values ​​of the joint and fissure rock mass, and then the generated random cracks are used to cut the internal rock mass; a continuous medium model is used outside the influence area, and the equivalent transfer law of node force and displacement is used to finally construct a finite element-block discrete element coupled physical model that simulates the numerical value of the fragmented rock mass. The specific calculation model is as follows: Figure 2 and Figure 3 As shown in the figure, number 1 is a joint.

[0090] Preferably, in S2, the model microscopic parameters and the equivalent mechanical parameters of rock masses with different joint densities are determined based on the application number 202411062690.3, entitled “A method for determining equivalent mechanical parameters of jointed and fissured rock masses”; wherein the mechanical parameter results of the joints are shown in Table 2:

[0091] Table 2 Calibrated joint mechanical parameters

[0092] Normal stiffness kn / GPa·m-1 Shear stiffness ks / GPa·m-1 <![CDATA[Cohesion c j / kPa]]> <![CDATA[Angle of friction φ j / °]]> 3 1.5 700 18

[0093] Since the joint density in different parts of the tunnel excavation is different, different joint densities are set so that different blasting parameters can be used according to the excavation conditions to obtain the cohesion and internal friction angle of the rock mass, as shown in Table 3:

[0094] Table 3 Equivalent mechanical parameters of jointed and fissured rock masses with different joint densities

[0095] Joint density level Elastic modulus E / GPa Poisson's ratio υ Cohesion c / kPa Internal friction angle φ / ° Level I 1.83 0.28 660 46.8 Level II 1.37 0.26 600 43.5 Level III 1.22 0.25 460 40.7

[0096] The internal block discrete element part of the model adopts the parameters in Table 3, and the external continuous medium model adopts the parameters in Table 4.

[0097] The blasting load is simulated by applying the equivalent stress time history method on the equivalent elastic boundary; the deformation boundary of the finite element-block discrete element coupling physical model adopts a viscous boundary, and an independent damper is set on the boundary.

[0098] Preferably, when simulating the blasting load by applying the equivalent stress time history method on the equivalent elastic boundary, according to the Chapman-Jouguet condensed explosive detonation wave model, the peak value of the initial detonation pressure acting on the blasthole wall without coupling charge is P0:

[0099]

[0100] Where: ρ0 is the density of explosive, D is the detonation velocity of explosive, a is the diameter of the cartridge, b is the diameter of the blast hole, γ is the specific heat capacity of the detonation gas (γ = 3);

[0101] The parameters of the explosive material selected for blasting are brought into it and then into the simplified triangular load function P D (t):

[0102] P D (t) = P0f(t);

[0103]

[0104] Then based on P D (t) Get the equivalent blasting load P e (x,t):

[0105]

[0106] Where: f(t) represents the transfer function, t represents the load time, t r Indicates the load rise time, t z represents the total time of loading, x represents the loading distance, r0 represents the blasthole radius, L s Indicates the peripheral hole spacing;

[0107] Finally, the equivalent blasting load boost time and total action time are obtained.

[0108] Based on the commonly used No. 2 rock emulsion explosive for on-site blasting in railway tunnels, its material parameters are shown in Table 4. Substituting them into the above formula, the equivalent blasting load time history can be obtained. The blasting load pressure rise time is about 0.8ms, and the total action time is about 8ms. Figure 4 shown. Figure 4 The triangular load function P in D (t) Response to quasi-static blast load. Figure 4 The vertical axis P represents the load, the horizontal axis t represents the time, and P0 represents the peak value of the initial detonation pressure.

[0109] Table 4 Explosive material parameters

[0110] Hole diameter (mm) Coil diameter (mm) <![CDATA[Explosive density (kg / m 3 )]]> Explosive detonation velocity (m / s) Peripheral eye distance (mm) 40 32 1000 3400 500

[0111] Preferably, when setting the unit as the boundary condition using a linear spring-damper model, Rayleigh damping is used to reduce the amplitude of the natural vibration mode of the system, assuming that the damping matrix C is linearly related to the stiffness matrix M and the mass matrix K:

[0112] [C]=α[M]+β[K];

[0113] α=ξ min ω min ;

[0114] β=ξ min / ω min ;

[0115] Where: α is the mass damping proportional coefficient, β is the stiffness damping proportional coefficient, ξ min is the critical damping ratio, ω min is the circular frequency corresponding to the critical damping ratio;

[0116] The mass damping proportional coefficient term is set to zero (α=0), and only the stiffness damping proportional coefficient (β) is considered; ξ min Take 2%-5%;

[0117] The deformation boundary of the finite element-block discrete element coupled physical model is set as a viscous boundary as a boundary condition. An independent damper is set at the boundary to provide viscous traction. The calculation formula is as follows:

[0118] t n =-ρC n v n ;

[0119] t s =-ρC s v s ;

[0120] Where: t n is the normal traction force on the boundary, t s is the tangential traction force on the boundary, v s is the normal component of the boundary velocity, v n is the tangential component of the boundary velocity, ρ is the mass density (the mass of the substance per unit volume), C n is the longitudinal wave velocity, C s is the shear wave velocity.

[0121] S3. Balancing the initial geostress: Specifically, setting static boundaries, setting both sides and the bottom of the finite element-block discrete element coupled physical model as fixed boundaries, and using a stress boundary on the top to simulate the overlying soil;

[0122] Remove the rock mass within the line connecting the surrounding eyes to simulate tunnel excavation;

[0123] The equivalent blasting load in S2 is applied to the tunnel contour surface for blasting numerical calculation. The boundary of the finite element-block discrete element coupled physical model is replaced with a viscous boundary to prevent stress waves from rebounding at the boundary and affecting the calculation results.

[0124] S4. Verify the validity of the finite element-block discrete element coupled physical model by comparing the blasting numerical calculation results obtained in S3 with the field test results. If the conditions are met, the model is directly output; if not, the parameters, equivalent blasting loads, and boundary conditions of the finite element-block discrete element coupled physical model are redefined. The discrete element model defines over-excavation based on whether the strain reaches 0.2% of the peak strain, and comprehensively considers the rock mass strain rate and strain increment to determine the location and degree of over-excavation in the tunnel, such as Figure 5 Through a detailed comparative analysis of the measured overbreak results and the discrete element model, it is found that the discrete element model is reasonable and superior in simulating the overbreak and underbreak behavior of tunnel blasting when considering joint characteristics. Figure 5 In the figure, red indicates the over-excavation area, and green indicates the normal excavation area.

[0125] The parameter optimization specifically includes: in order to control the over-excavation of the on-site project, different peripheral hole spacing and charge conditions close to the on-site conditions are set. The original blasting plan has a peripheral hole spacing of 50 cm and a charge of 0.8 kg·m -1 According to the on-site blasting situation, the distance between blastholes can be increased to reduce the charge amount. Therefore, the distance between blastholes can be increased by about 10% to reduce the charge amount. For the convenience of calculation, the three values ​​selected are 55cm, 60cm, 65cm, and 0.75kg·m -1 , 0.70kg·m -1 , 0.65kg·m -1 Based on S1, S2, and S3, we first simulated and analyzed different blasthole spacings. Overexcavation data for each condition was extracted, and a comparison chart of overexcavation at each location was plotted. Based on this comparison of overexcavation, we determined the optimal peripheral hole spacing parameters. The results clearly show that the optimal blasthole spacing is approximately 60 cm. To avoid underexcavation, the peripheral hole spacing should not exceed 65 cm, assuming all other conditions remain unchanged.

[0126] Then, simulation calculation and analysis of different charge amounts were carried out based on S1, S2, and S3. The over-excavation data under each working condition were extracted to draw a comparison chart of the over-excavation of each part. The optimized charge amount parameters were determined based on the comparison of the over-excavation situation. When the charge amount was reduced to 0.70 kg·m -1 The maximum over-excavation value and average linear over-excavation of each part of the tunnel basically meet the requirements of the specification. -1 When the over-excavation in each part is much smaller than the over-excavation value allowed by the specification, and no over-excavation is detected at the left arch foot, right arch waist and right arch foot. At this time, under-excavation is very likely to occur and should be avoided.

[0127] The present invention also includes S5. In actual engineering, tunnels may have serious problems of local over-excavation due to inconsistent density of joints at different parts. Therefore, more consideration should be given to the construction environment on site, timely adjustments should be made, and flexible responses should be taken. Therefore, based on S1, S2, and S3, a finite element-block discrete element coupled physical model is established under different joint densities, and the method of S4 is adopted to optimize the parameters of peripheral eye spacing and charge amount under different joint densities.

[0128] Specifically: Based on the S1 method, the built-in mass-density keyword in the DFN model (Deep Feedback Network, a deep learning model for recommendation systems) is used for step-by-step control to establish two blasting models with different joint densities. The parameters of the finite element-block discrete element coupled physical model use the equivalent mechanical parameters of the rock mass with different joint densities obtained in S2. The initial ground stress of the model is balanced according to S3; the rock mass within the peripheral eye connection line is removed; the equivalent blasting load is applied to the tunnel contour surface, and the blasting numerical calculation is performed. The S4 method is used to optimize the parameters of the peripheral eye spacing and charge under different joint densities. In engineering practice, the corresponding optimized parameters are selected according to the rock mass joint density at different excavation advances. The following optimized results are obtained as shown in Table 5:

[0129] Table 5 Peripheral hole blasting parameters for different joint density levels

[0130] Joint density level Hole spacing / cm Charge amount / kg·m-1 Level I 50 0.8 Level II 60 0.7 Level III 65 0.6

[0131] The present invention also provides a readable storage medium storing a computer program, wherein the computer program is suitable for being loaded by a processor and executing the above-mentioned tunnel perimeter hole blasting parameter optimization method.

[0132] The present invention also provides a computer device, which includes a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the above-mentioned tunnel perimeter hole blasting parameter optimization method is executed.

[0133] The tunnel perimeter blasting parameter optimization method of the present invention determines the numerical model parameters by taking into account the actual joint density, thereby improving the accuracy of the numerical model. It adopts a finite element-block discrete element coupled physical model to improve the computational efficiency of the numerical model and achieve accurate simulation at the engineering scale. It proposes a method for determining the location and degree of tunnel overexcavation by comprehensively considering the rock mass strain rate and strain increment. The effectiveness of the model is verified by comparing it with the actual overexcavation situation on site. It also provides optimization schemes under various joint density conditions. When excavating to different locations, the optimization scheme can be directly adopted according to the measured joint density. , that is, the optimized peripheral eye spacing and charging amount, reducing the time of suspension waiting for the formulation of the optimization plan; compared with the existing blasting parameter optimization method, the present invention takes into account the influence of joint density on the blasting effect of the tunnel peripheral eyes based on the finite element-block discrete element coupling physical model, making the blasting parameter optimization more efficient, and improving the accuracy of the parameter optimization results. It solves the technical problems in the prior art of tunnel blasting, that is, the design of smooth blasting hole parameters and charging parameters is insufficient to understand the surrounding rock geological conditions such as joint density, and the uneven propagation of explosion energy leads to large surrounding rock damage after blasting, over-excavation and under-excavation, etc.

[0134] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A method for optimizing tunnel perimeter blasting parameters, characterized in that: The steps include: Obtain the tunnel perimeter blasting parameters; The tunnel perimeter blasting parameters are input into the finite element-block discrete element coupled physical model for parameter optimization to obtain the optimized parameters; The construction of the finite element-block discrete element coupled physical model includes the following steps: S1. Establish a finite element-block discrete element coupled physical model; S2. Determine the parameters, equivalent blasting loads and boundary conditions of the finite element-block discrete element coupled physical model; S3. Balancing the initial geostress: Specifically, setting static boundaries, setting both sides and the bottom of the finite element-block discrete element coupled physical model as fixed boundaries, and using a stress boundary on the top to simulate the overlying soil; Remove the rock mass within the line connecting the surrounding eyes to simulate tunnel excavation; The equivalent blasting load in S2 is applied to the tunnel contour surface, the blasting numerical calculation is performed, and the boundary of the finite element-block discrete element coupled physical model is replaced by a viscous boundary; S4. Verify the validity of the finite element-block discrete element coupled physical model by comparing the blasting numerical calculation results obtained in S3 with the field test results. If the conditions are met, directly output the model; if not, redefine the parameters, equivalent blasting loads, and boundary conditions of the finite element-block discrete element coupled physical model. Parameter optimization specifically includes optimizing the peripheral eye spacing and charge parameters, specifically: increasing the peripheral eye spacing and reducing the charge in preset steps, setting multiple different values ​​for each, first optimizing the peripheral eye spacing, extracting the over-excavation data under each working condition, and drawing a comparison chart of the over-excavation of each part, determining the optimized peripheral eye spacing based on the comparison of the over-excavation situation, and then optimizing the charge under the optimized peripheral eye spacing, and determining the optimized charge.

2. The tunnel perimeter hole blasting parameter optimization method according to claim 1, characterized in that: S1 specifically includes: In the tunnel influence area, a block discrete element model is used to reflect the characteristics of the fractured rock mass. Specifically: Firstly, the DFN model is established based on the joint development characteristics and statistical characteristic values ​​of the jointed and fissured rock mass. Secondly, the generated random cracks are used to cut the internal rock mass; Finally, a continuous medium model is adopted outside the affected area, and the equivalent transfer law of nodal force and displacement is used to construct a finite element-block discrete element coupled physical model to simulate the numerical value of the fractured rock mass.

3. The tunnel perimeter hole blasting parameter optimization method according to claim 1, characterized in that: S2 specifically includes: determining the microscopic parameters of the finite element-block discrete element coupling physical model and the equivalent mechanical parameters of rock masses with different joint densities; simulating blasting loads by applying an equivalent stress time history method on the equivalent elastic boundary; and adopting a viscous boundary as the deformation boundary of the finite element-block discrete element coupling physical model, and setting an independent damper at the boundary.

4. The method for optimizing tunnel perimeter blasting parameters according to claim 3, characterized in that: When simulating blasting loads by applying the equivalent stress time history method on the equivalent elastic boundary, according to the Chapman-Jouguet condensed explosive detonation wave model, the initial detonation pressure peak value acting on the blasthole wall without coupling charge is P0: Where: ρ0 is the density of explosives, D is the detonation velocity of explosives, a is the diameter of the cartridge, b is the diameter of the blast hole, and γ is the specific heat capacity of the detonation gas; The parameters of the explosive material selected for blasting are brought into it and then into the simplified triangular load function P D (t): P D (t)=P0f(t); Then based on P D (t) Get the equivalent blasting load P e (x,t): Where: f(t) represents the transfer function, t represents the load time, t r Indicates the load rise time, t z represents the total time of loading, x represents the loading distance, r0 represents the blasthole radius, L s Indicates the peripheral hole spacing; Finally, the equivalent blasting load boost time and total action time are obtained.

5. The method for optimizing tunnel perimeter blasting parameters according to claim 3, characterized in that: In the linear spring-damper model setting element as the boundary condition, Rayleigh damping is used to reduce the amplitude of the natural vibration mode of the system. It is assumed that the damping matrix C is linearly related to the stiffness matrix M and the mass matrix K: [C]=α[M]+β[K]; a = x min oh min ; β=ξ min / h min ; Where: α is the mass damping proportional coefficient, β is the stiffness damping proportional coefficient, ξ min is the critical damping ratio, ω min is the circular frequency corresponding to the critical damping ratio; The mass damping proportional coefficient is set to zero, and only the stiffness damping proportional coefficient is considered; ξ min Take 2%-5%; The deformation boundary of the finite element-block discrete element coupled physical model is set as a viscous boundary as a boundary condition. An independent damper is set at the boundary to provide viscous traction. The calculation formula is as follows: t n =-ρC n v n ; t s =-ρC s v s ; Where: t n is the normal traction force on the boundary, t s is the tangential traction force on the boundary, v s is the normal component of the boundary velocity, v n is the tangential component of the boundary velocity, ρ is the mass density, C n is the longitudinal wave velocity, C s is the shear wave velocity.

6. The method for optimizing tunnel perimeter blasting parameters according to claim 2, characterized in that: It also includes S5, specifically: based on the method of S1, the mass-density keyword built into the DFN model is used for step-by-step control to establish two blasting models with different joint densities, where the parameters of the finite element-block discrete element coupling physical model use the equivalent mechanical parameters of the rock mass with different joint densities obtained in S2, and the initial ground stress of the model is balanced according to S3; the rock mass within the peripheral eye connection line is removed; the equivalent blasting load is applied to the tunnel contour surface, and the blasting numerical calculation is performed.

7. The method for optimizing tunnel perimeter blasting parameters according to claim 1, characterized in that: When the S4 method is used to optimize the parameters of peripheral eye spacing and charge amount under different joint densities, the corresponding optimized parameters are selected according to the rock joint density at different excavation advances in engineering practice.

8. A readable storage medium, characterized in that: The readable storage medium stores a computer program, and the computer program is suitable for being loaded by a processor and executing the tunnel perimeter hole blasting parameter optimization method according to any one of claims 1 to 7.

9. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores a computer program, and when the computer program is executed by the processor, the tunnel perimeter eye blasting parameter optimization method according to any one of claims 1 to 7 is executed.

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