Quality assessment method for anchor bolt construction layout of main powerhouse

Abstract

The present invention provides a method for evaluating the quality of anchor construction layout of a main powerhouse, which relates to the field of underground engineering and includes the following steps: S1, model construction: establishing a three-dimensional numerical model of different anchor layout schemes; S2, simulation calculation and result evaluation: performing excavation simulation calculations based on the three-dimensional numerical models of different anchor layout schemes, obtaining numerical simulation calculation results of surrounding rock deformation, stress distribution, distribution of damaged and fractured areas, and stress of support structures; evaluating the numerical simulation calculation results of different anchor layout schemes, obtaining evaluation indicators, and determining the optimal scheme based on the evaluation indicators. The coordination between the above structures has the following beneficial effects: First, it can comprehensively improve the accuracy of the evaluation, through the all-round integration of geological survey data, in-depth analysis of the surrounding rock lithology, joint and fissure direction, and ground stress distribution, and comprehensive consideration of the physical properties of the anchor itself, and closely combining with key indicators of the construction link.

Description

Technical Field

[0001] The present invention relates to the field of underground engineering, and in particular to a method for evaluating the quality of anchor rod construction layout of a main powerhouse. Background Art

[0002] In the construction of large-scale underground projects, such as the excavation of the underground powerhouse of the Shuangjiangkou Hydropower Station, support design is crucial to ensuring project safety and economy. The support design scheme for the remaining excavation layer of the main powerhouse directly affects the progress, cost, and stability of the entire project. Among them, the system anchor rod is one of the main support methods, and the selection of its length requires comprehensive consideration of multiple factors.

[0003] At present, as the project progresses, the overall stability of the surrounding rock is relatively good, which provides certain conditions for optimizing the support design. However, under the premise of ensuring project safety, there is currently a lack of systematic and accurate quality assessment methods for the evaluation of the anchor bolt construction layout of the main powerhouse. This makes it difficult to comprehensively and scientifically judge whether the anchor bolt layout is reasonable and whether it can effectively ensure the safety and stability of the main powerhouse. Summary of the Invention

[0004] In view of the shortcomings of the above-mentioned existing technologies, the technical problem to be solved by the present invention is to provide a method for evaluating the quality of anchor rod construction layout in the main factory building, which can evaluate the layout quality of anchor rods at different construction stages in real time, and effectively solve the problems of insufficient consideration of construction process factors and difficulty in dynamic evaluation in existing methods.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is as follows: the present invention provides a method for evaluating the quality of anchor bolt construction layout of a main powerhouse, comprising the following steps:

[0006] S1. Model construction: Establish three-dimensional numerical models of different anchor arrangement schemes;

[0007] S2. Simulation calculation and result evaluation: Perform excavation simulation calculation based on the three-dimensional numerical model of different anchor arrangement schemes to obtain the numerical simulation calculation results of surrounding rock deformation, stress distribution, distribution of damaged and fractured areas, and stress on the support structure;

[0008] Evaluate the numerical simulation results of different anchor arrangement schemes, obtain evaluation indicators, and determine the optimal scheme based on the evaluation indicators;

[0009] S3. Error value analysis: Compare the numerical simulation calculation results with the on-site monitoring data according to the optimal solution to obtain the comparison results, and calculate the error rate of each evaluation indicator based on the comparison results;

[0010] S4. Establish a comparison model: establish an error correction model for the evaluation method based on the comparison results, and adjust the parameters in the numerical model based on the deviation values ​​between the numerical simulation calculation results and the field monitoring data.

[0011] In a preferred solution, in step S2, the deformation of the surrounding rock under different anchor arrangement schemes, including the top arch settlement and side wall displacement, is compared to evaluate the deformation control effect.

[0012] Analyze the stress state of the surrounding rock under different anchor arrangement schemes, including the degree of stress concentration and uniformity of stress distribution, and evaluate the improvement of the stress state;

[0013] Analyze the distribution characteristics of the surrounding rock damage and fracture zones under different bolt arrangement schemes, including the location, size and shape of the damage zone and the range of the strong relaxation zone and weak relaxation zone, and evaluate the control effect of the expansion of the surrounding rock damage and fracture zone;

[0014] Analyze the internal force distribution of anchor rods under different anchor rod arrangement schemes, including the maximum internal force of anchor rods and the internal force distribution law, and evaluate the internal force distribution of anchor rods.

[0015] In a preferred solution, in step S3, the numerical simulation calculation results are compared with the on-site monitoring data to verify the accuracy and reliability of the assessment method. The specific comparison content includes:

[0016] Deformation comparison: Compare the surrounding rock deformation under the action of anchor bolts calculated by numerical simulation with the deformation measured on-site, including deformation at different locations and excavation levels;

[0017] Stress comparison: Compare the surrounding rock stress distribution under the action of the anchor bolt calculated by numerical simulation with the stress distribution monitored on site to verify the accuracy of the stress calculation;

[0018] Comparison of damage zones: Compare the distribution of surrounding rock damage zones under the action of anchor bolts calculated by numerical simulation with the damage zones obtained by on-site monitoring to evaluate the accuracy of damage zone prediction.

[0019] In the preferred solution, the error rate formulas for deformation comparison, stress comparison, and damage zone comparison are expressed as follows:

[0020] The deformation error calculation formula is: ;

[0021] The calculation formula for deformation error rate is: ;

[0022] The stress error calculation formula is: ;

[0023] The formula for calculating the stress error rate is: ;

[0024] The error calculation formula is: ;

[0025] The error rate calculation formula is: ;

[0026] The deformation error rate calculation formula, stress error rate calculation formula and depth error rate calculation formula can be used to quantify the difference between the simulation calculation results and the on-site monitoring data. By calculating the difference, the degree of numerical deviation between the simulation value and the monitoring value can be obtained.

[0027] In a preferred solution, in step S4, the following steps are further included:

[0028] S41. Analyze the deformation error rate, stress error rate, and depth error rate under different anchor arrangement schemes, and adjust the parameters in the three-dimensional numerical model;

[0029] Among them, if the deformation calculated by simulation is large overall, it means that the value of rock deformation modulus is too high and the deformation modulus parameter should be reduced;

[0030] If the stress calculation error is large, it indicates that the initial geostress field parameters or the parameters of the interaction between the anchor and the rock mass should be re-evaluated;

[0031] S42. Establish an error correction model by analyzing data from multiple monitoring points and different excavation stages.

[0032] In a preferred solution, in step S42, the specific steps of establishing the deformation error correction model are as follows:

[0033] Assume that the deformation value of on-site monitoring is , the simulated deformation value is , the correction formula is obtained by data fitting:

[0034] ;

[0035] in, and is the fitting coefficient;

[0036] Calculated based on data from multiple monitoring points and The value of is fitted by the least square method, so that The deformation correction model is obtained by substituting the simulation calculation results into the deformation correction model to obtain the corrected deformation value, and the deviation between the simulation calculation value and the on-site monitoring deformation value is corrected according to the corrected deformation value.

[0037] In a preferred solution, in step S42, the specific steps of establishing the stress error correction model are as follows:

[0038] The stress value of on-site monitoring is The simulated stress value is , the correction formula is obtained by data fitting:

[0039] ;

[0040] in, and is the fitting coefficient;

[0041] Collect stress data from multiple monitoring points and calculate it by least square fitting method. Minimum, obtain stress correction model, substitute simulation calculation result into stress correction model, obtain corrected stress value, correct the deviation between simulation calculation value and on-site monitoring stress value according to corrected stress value. In the preferred solution, the present invention provides one.

[0042] The present invention provides a method for evaluating the quality of anchor bolt construction layout in a main powerhouse. Through the coordination between the above structures, the method has the following beneficial effects:

[0043] First, it can comprehensively improve the accuracy of assessment by comprehensively integrating geological survey data, deeply analyzing the lithology of the surrounding rock, the direction of joints and fissures, and the distribution of ground stress, and comprehensively considering the physical properties of the anchor rods themselves, closely combining the key indicators of the construction links, building a comprehensive assessment system, and using data analysis models and algorithms to convert the data into intuitive and quantitative assessment results.

[0044] Second, by establishing an error correction model, the deviation between numerical simulation and on-site monitoring data can be accurately calibrated, providing a reliable basis for optimizing the anchor support scheme and ensuring the stability of the surrounding rock of the main factory building, effectively improving the scientificity and accuracy of engineering design and construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The present invention will be further described below with reference to the accompanying drawings and embodiments:

[0046] Figure 1 This is the contour map of the first-level excavation displacement Uz of the installation room of the present invention;

[0047] Figure 2 It is the contour map of the first-level excavation displacement Uy of the installation room of the present invention;

[0048] Figure 3 It is the contour map of the first-level excavation stress σ1 of the installation room of the present invention;

[0049] Figure 4 This is the contour map of the first-level excavation stress σ3 of the installation room of the present invention;

[0050] Figure 5 This is a diagram of the damage mode of the surrounding rock in the first level of excavation of the installation room of the present invention;

[0051] Figure 6 The present invention is the first stage under different confining pressure C 1.C 3 and R d The relationship curve diagram;

[0052] Figure 7 is a schematic diagram of the pseudo-viscous unit of stage I of the present invention;

[0053] Figure 8 The crack closure degree under σ3 = 1MPa of the present invention is R d The relationship curve diagram;

[0054] Figure 9 This is a graph showing the relationship between the four types of stress thresholds and confining pressures of the present invention;

[0055] Figure 10 This is a curve diagram showing the relationship between Rcc d, Rci d, Rcd d and confining pressure in the present invention. DETAILED DESCRIPTION

[0056] In order to better understand the purpose, structure and function of the present invention, the embodiments and features in the embodiments of the present invention can be combined with each other without conflict. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0057] Example

[0058] like Figures 1 to 10 As shown, this embodiment provides a method for evaluating the quality of anchor bolt construction layout in a main powerhouse, comprising the following steps:

[0059] S1. Model construction: Build a three-dimensional numerical model of different anchor arrangement schemes. The specific steps are as follows:

[0060] S11. Based on the actual situation of the underground powerhouse of Shuangjiangkou Hydropower Station, the following different anchor arrangement schemes were designed for numerical model construction:

[0061] Option A:

[0062] Anchor spacing: 1.2m×1.2m (longitudinal×transverse).

[0063] Layout position: Evenly arranged from the top arch to the bottom of the side wall.

[0064] Anchor rod internal force: The internal force of the prestressed anchor rod is 100kN, and the diameter of the ordinary mortar anchor rod is 28mm.

[0065] Option B:

[0066] Anchor spacing: 1.5m×1.5m (longitudinal×transverse).

[0067] Layout position: The top arch is arranged densely, the middle part of the side wall is appropriately sparse, and the bottom is densely arranged.

[0068] Anchor rod internal force: The internal force of the prestressed anchor rod is 120kN, and the diameter of the ordinary mortar anchor rod is 32mm.

[0069] Option C:

[0070] Anchor spacing: 1.8m×1.8m (longitudinal×transverse).

[0071] Layout position: The top arch and the bottom of the side walls are densely packed, and the middle part is evenly arranged.

[0072] Anchor rod internal force: The internal force of the prestressed anchor rod is 150kN, and the diameter of the ordinary mortar anchor rod is 36mm.

[0073] S12. Model parameter setting

[0074] Effect of deformation modulus and Poisson's ratio

[0075] According to the elastic theory, the relationship between the deformation and stress of the rock mass can be expressed by the elastic modulus. and Poisson's ratio To describe. In FLAC 3D When performing simulation calculations in software such as , these parameters are important factors affecting rock deformation and stress distribution.

[0076] According to the following table 1, the physical and mechanical parameters of the rock mass corresponding to different surrounding rock types are obtained, such as the natural density of slightly fresh granite interbedded with granite fine-grained rock, pegmatite veins, massive and sub-massive rock mass. , deformation modulus , Poisson's ratio , the initial geostress field data are obtained by inversion using the multiple regression method or GAN method, such as the major principal stress in the installation area is about 28.0-30.0MPa, and the minor principal stress is about 12.0-14.0MPa. 3D The software builds a three-dimensional numerical model;

[0077] Table 1 Recommended values ​​of physical and mechanical properties of surrounding rock in underground caverns

[0078]

[0079] In the numerical model, the material properties of the rock mass are set according to these parameters and used to calculate the deformation and stress response of the rock mass during excavation.

[0080] Through model calculations, the deformation and stress distribution of the rock mass after excavation under different anchor arrangement schemes can be obtained. These results are compared with field monitoring data to evaluate the accuracy of the model.

[0081] Initial geostress field: The geostress field data obtained by inversion using the multiple regression method or the GAN method are used. For example, the major principal stress in the installation area is approximately 28.030.0 MPa, and the minor principal stress is approximately 12.014.0 MPa.

[0082] Specifically, the calculation steps of the multiple regression method are as follows:

[0083] When using the multiple regression method to invert the initial geostress field, the geostress regression calculated value As the dependent variable, the stress calculation value corresponding to the measured point under each working condition (self-weight stress calculation, boundary load, etc.) obtained by finite element calculation is used. As the independent variable, the regression stress It can be regarded as a linear combination of stress calculations of various working conditions, and the formula is: ;

[0084] in, is the multiple regression coefficient;

[0085] For the least squares residual sum of squares , and its calculation formula is:

[0086] ;

[0087] in, is the total number of observation points, is the observation point number, is the total number of working conditions, To calculate the number of working conditions, is the number of stress components, For the Observation point The regression calculation value of the ground stress component is For the Observation point Measured values ​​of the ground stress components.

[0088] According to the principle of multiple regression method, representative ground stress measurement points are selected and finite element calculation is performed to obtain the stress calculation values ​​under various working conditions. .

[0089] Using the least squares method, the residual sum of squares To obtain the minimum value, we can solve the equation:

[0090] ;

[0091] in, is the design matrix, is the matrix of multiple regression coefficients, is the observation vector, and the multiple regression coefficient matrix is ​​obtained .

[0092] Any point The regression initial stress is: ;

[0093] The distribution characteristics of the initial geostress field obtained by inversion are basically consistent with the measured geostress field. The extreme value of the first principal stress at each measuring point basically increases with the increase of burial depth, and the value fluctuates between 14.88MPa and 37.82MPa.

[0094] The GAN inversion method is used to calculate the paleo-stress field based on the lateral stress coefficient. The specific steps are as follows:

[0095] Lateral stress coefficient and stress components The relationship is:

[0096] ;

[0097] in, For the stress components, is the bulk density, For burial depth.

[0098] However, the current geostress field is affected by the terrain undulation and the physical and mechanical properties of the rock mass, resulting in large variations in the geostress coefficient at different locations. However, in ancient times, the topography and landforms were less undulating and the geological structure was not complex. Therefore, it is more appropriate to use the lateral stress coefficient to invert the ancient geostress field.

[0099] The lateral stress coefficient at every point in the rock mass is a fixed value, which means that the stress component increases linearly with increasing burial depth. However, for deep-buried projects, the lateral stress coefficient is not linearly related to burial depth. Based on global measured ground stress data, Brown and Hoek found that the relationship between the lateral stress coefficient and burial depth is:

[0100] ;

[0101] in, 、 and are the maximum principal stress, minimum principal stress and vertical principal stress in the horizontal plane, respectively.

[0102] Through statistical analysis of the lateral stress coefficients of different rock masses, it is concluded that for deep buried projects, the relationship between the lateral stress coefficient and the burial depth is:

[0103] ;

[0104] in, and is the regression factor.

[0105] From the field survey data, the stress values ​​of the measured points are statistically analyzed, and effective measuring points are selected to determine the approximate lateral stress coefficient according to the above formula. .

[0106] Based on the uniform design experiment, and Set the floating range and design multiple and The paleo-stress field of the value.

[0107] According to multiple paleo-stress fields, using FLAC 3D Excavation of the stratum is carried out to obtain multiple current initial stress fields, from which the lateral stress coefficient at the current burial depth is determined.

[0108] Inversion of current geostress field based on GAN

[0109] The objective function of GAN is:

[0110] ;

[0111] in, Represents the discriminator's response to real data The discriminant probability of Represents the data generated by the discriminator to the generator The discriminant probability of is the real data distribution, is a random variable distribution.

[0112] The measurement points in the underground cavern and its surroundings, as well as the measurement points near the boundary of the numerical model, were selected as samples to determine the formula The floating range of the regression factors in .

[0113] Each regressor or The value range of is between 0.5 and 1.5 times of itself. 12 regression factors are taken as factors of uniform design experiment. Different regression factor values ​​are regarded as different levels. According to the principle of uniform design, the regression factor has 13 levels. Then, the 1st to 13th levels correspond to the regression factors 0.52, 0.60, 0.68, 0.76, 0.84, 0.92, 1.00, 1.08, 1.16, 1.24, 1.32, 1.40, and 1.48 times, respectively. As shown in Table 2, the regression factors of each test can be substituted into the formula and Calculate the stress components of each element and import them into FLAC 3DCalculations are performed. In each test, the calculated stress components and lateral stress coefficients of the measured points can be obtained. There are 8 valid measurement points, so 8 training samples can be created for each test, with a total of 13×8=104 samples.

[0114] Table 2 Table of factors with different levels in the U13 uniform design experiment

[0115]

[0116] Use real data to train samples. After the training is completed, input the x and y coordinates, input the current burial depth and lateral stress coefficient of the measuring point in the current stress field of the measuring point, and the regression factor of the paleostress field can be obtained. After GAN training, the regression factor of the optimized paleostress field can be predicted to obtain the optimized and value, and then optimize the ancient geostress field, and obtain the optimized present geostress field through excavation.

[0117] Table 3 Regression factors of paleo-stress field obtained using GAN and BP neural network

[0118]

[0119] Table 4 Stress component values ​​at each measuring point based on GAN and BP neural network

[0120]

[0121] The regression factors and calculated stress values ​​of the measuring points are listed in Tables 3 and 4. The relative errors of the measuring points are It can be calculated as:

[0122] ;

[0123] in, is the calculated stress component, is the measured stress component, is the 2-norm.

[0124] For a composite element with both rock mass and fault, the deformation and stress relationship of the equivalent element in the z' direction is:

[0125] ;

[0126] in, and are the equivalent elastic moduli of the rock mass and fault in the z' direction, and are the thickness of the rock mass and fault, respectively. and are the stresses applied to the equivalent element, rock mass and fault in the z´ direction, respectively.

[0127] Equivalent elastic modulus in z´ direction for:

[0128] ;

[0129] in, and are the equivalent Poisson's ratios of the rock mass and fault, respectively.

[0130] Equivalent Poisson's ratio It can be expressed as:

[0131] ;

[0132] Divide the rock mass into hexahedral units. For the units cut by faults, determine the relevant parameters of the rock mass and faults, such as layer thickness. and , elastic modulus and , Poisson's ratio and wait.

[0133] According to the above formula, the equivalent elastic modulus of the equivalent element in the z' direction is calculated and the equivalent Poisson's ratio .

[0134] The distribution of the current geostress field obtained by the GAN inversion method is reasonable and has a good fitting effect with the measured geostress field, with the fitting complex correlation coefficient reaching 0.9024.

[0135] S13. Model building

[0136] Using FLAC 3D The software establishes a three-dimensional numerical model. The model range and typical geological profiles are in accordance with the relevant provisions of Chapter 2 of the document. For example, the calculation range has a total length of 275.7m in the X direction (from 0098.82 in the factory horizontal direction to 0+176.88 in the factory horizontal direction), a total length of 300.0m in the Y direction, and the Z axis is vertically upward, with the bottom at an elevation of ▽2170.0m and the top extending to the surface of the mountain top.

[0137] S2. Simulation calculation and result evaluation: Perform excavation simulation calculation based on the three-dimensional numerical model of different anchor arrangement schemes to obtain the numerical simulation calculation results of surrounding rock deformation, stress distribution, distribution of damaged and fractured areas, and stress on the support structure;

[0138] Evaluate the numerical simulation results of different anchor arrangement schemes, obtain evaluation indicators, and determine the optimal scheme based on the evaluation indicators;

[0139] The preferred solution is Figures 1 to 4 As shown in Table 5, the simulation is carried out according to the excavation sequence of the underground powerhouse. For example, the first level of excavation is carried out first, i.e., the excavation of the A layer of the main powerhouse, the excavation of the a and b layers of the tailgate room, etc., and then the subsequent levels of excavation are carried out in sequence until the designed excavation state is reached.

[0140] Table 5 Graded excavation table of Shuangjiangkou underground powerhouse

[0141]

[0142] Obtaining calculation results: During the excavation process and after the excavation is completed, the surrounding rock deformation, stress distribution and other results are obtained. Furthermore, the cave displacement contour map, principal stress distribution information and surrounding rock plastic failure mode map of different excavation levels under each scheme are recorded, which is similar to the relevant data display in the calculation results of each excavation level of Working Condition 1 in Chapter 6 of the document.

[0143] S21. Deformation index evaluation

[0144] Comparison of top arch sinking:

[0145] Option A: After the first level of excavation, the average settlement of the main power building arch is about 18 mm (according to the value range of simulation results). As the excavation level increases, after the fifth level of excavation, the arch settlement increases to 25 mm.

[0146] Option B: After the first level of excavation, the average settlement of the main power building arch is about 16mm, and after the fifth level of excavation, it increases to 23mm.

[0147] Option C: After the first level of excavation, the average settlement of the main power building arch is about 20mm, and after the fifth level of excavation, it increases to 27mm.

[0148] Assuming that the arch subsidence is obtained through the displacement data statistics of the monitoring points, multiple monitoring points are set in the model, and the vertical displacement values ​​of each monitoring point at different excavation stages under different schemes are recorded, and the average value is taken to obtain the above results.

[0149] Side wall displacement comparison:

[0150] Option A: After the first level of excavation, the upstream side wall of the main power building displaced an average of about 15 mm into the tunnel, and the downstream side wall displaced about 12 mm. After the fifth level of excavation, the displacement of the upstream side wall increased to 30 mm, and the downstream side wall increased to 25 mm.

[0151] Option B: The side wall displacements at the corresponding positions are approximately 13mm and 10mm respectively. After the fifth level of excavation, the displacement of the upstream side wall increases to 28mm, and that of the downstream side wall increases to 23mm.

[0152] Option C: The side wall displacements are approximately 18 mm and 14 mm respectively. After the fifth level of excavation, the displacement of the upstream side wall increases to 35 mm, and that of the downstream side wall increases to 30 mm.

[0153] By monitoring horizontal displacement points at different locations on the side walls, the displacement data for each monitoring point under different schemes was calculated and averaged. By comparison, it can be seen that Scheme B is relatively effective in controlling arch subsidence and side wall displacement.

[0154] S22. Stress Index Assessment

[0155] Stress concentration degree:

[0156] Option A: After the first level of excavation, the stress concentration at the arch end of the main power building is relatively high, and the stress in the local area reaches about 45MPa (based on the value range of the simulation results).

[0157] Option B: The stress concentration at the arch end is relatively low, and the maximum stress value is about 42MPa.

[0158] Option C: The stress concentration at the arch end is relatively high, with the local stress reaching approximately 48 MPa.

[0159] As the excavation progresses, the stress concentration area changes, but Scheme B always maintains a relatively low stress concentration level.

[0160] Extract the stress values ​​of the key units of the main powerhouse arch end in the model, analyze the stress distribution, and determine the stress concentration area and extreme value. Stress calculation is based on the mechanical equilibrium equation and material constitutive relationship of the model, and is performed in FLAC. 3D Automatically calculated in the software.

[0161] The stress distribution uniformity can be quantitatively evaluated by using indicators such as stress variation coefficient. ;

[0162] in, is the stress standard deviation, To obtain the average stress, calculate the stress variation coefficient under different schemes and compare their sizes. The smaller the coefficient, the more uniform the stress distribution.

[0163] By analyzing the uniformity of surrounding rock stress distribution under different schemes, it was found that the stress distribution of Scheme B was relatively uniform, while Schemes A and C had stress mutation phenomena in some parts.

[0164] S23. Distribution characteristics of damage and rupture zone Failure mode: Figure 5 As shown in Figure 2, during the excavation process, the failure modes of the surrounding rock under different schemes are different;

[0165] In Scheme A, the depth of the top arch plastic failure zone is relatively shallow, and it is mainly superficial plastic failure;

[0166] In Plan B, the damage to the top arch and side walls is relatively concentrated, but the degree is relatively mild;

[0167] In Scheme C, the failure zone is deeper and obvious shear failure occurs in some parts.

[0168] As the excavation level increases, the damage range of each scheme gradually expands. Scheme B is relatively good in controlling the damage range and can effectively reduce the damage degree of the surrounding rock. The specific steps are as follows:

[0169] Criteria for surrounding rock relaxation zone

[0170] Based on the criterion of crack closure: radial crack expansion is the main cause of rock volume expansion, crack closure It can reflect the characteristics of the volume expansion of the rock mass in the radial direction. According to the document content, the surrounding rock unloading relaxation zone is based on The values ​​are divided into five zones, namely the destruction zone, strong relaxation zone, weak relaxation zone, stress disturbance zone and original rock zone. The specific criteria are as follows:

[0171] when When the surrounding rock is damaged, it needs to be supported immediately.

[0172] for The surrounding rock allows the tangential and radial stresses of the rock mass to be further released. The inflection point is determined by the change curve of the value and is regarded as the optimal support time.

[0173] Combined with the actual engineering support method, the surrounding rock is divided into three areas: the arch, the upstream side wall, and the downstream side wall. If there is rock mass that needs to be supported at a certain level of excavation in a certain area, the surrounding rock at that level in this area will be fully supported.

[0174] Calculation process

[0175] In conventional triaxial tests, the crack closure stress under different confining pressures is determined by analyzing the stress-strain curve of the rock specimen. , crack initiation stress , crack damage stress and peak stress , further, under the confining pressure When the , , .

[0176] Introducing the deviatoric stress peak intensity ratio To analyze the test data:

[0177] ;

[0178] in, is the deviatoric stress, is the peak intensity, i.e. Deviatoric stress at .

[0179] like Figure 9 、 10 As shown in the figure, the four different threshold stresses increase linearly with the increase of confining pressure, indicating that confining pressure has a great influence on the threshold stress. The crack closure stress is (0.15-0.23) , crack initiation stress is (0.3-0.7) , crack damage stress is (0.7-0.85) In this embodiment, the ratios of the crack closure stress, crack initiation stress, and crack damage stress to the peak strength are expressed as Rcc d, Rci d, and Rcd d, respectively. Table 6 below summarizes the ratios of the three threshold stresses to the peak strength of granite. For granite, under uniaxial compression, Rcc d, Rci d, and Rcd d are approximately 0.22, respectively. , 0.41 and 0.78 , and gradually decreases with the increase of confining pressure, indicating that there is a functional relationship between confining pressure and the values ​​of Rcc d, Rci d and Rcd d.

[0180] Table 6 Summary of Rcc d, Rci d, and Rcd d of granite

[0181]

[0182] Relationship between Rcc d, Rci d and Rcd d and confining pressure. As the confining pressure increases, Rcc d, Rci d and Rcd d gradually decrease. According to the fitting curve, Rcc d, Rci d and Rcd d eventually approach 0.1978, 0.3778 and 0.7066 respectively. Under low confining pressure, it gradually decreases with the increase of confining pressure, but tends to a constant value with the increase of confining pressure, indicating that the crack expansion is limited by the confining pressure, but this limiting ability will gradually stabilize with the increase of confining pressure.

[0183] according to The value of is used to determine the crack evolution stage and then calculate the crack closure degree. , under a certain confining pressure, different The axial and radial crack strains at , and thus the The specific calculation process is as follows:

[0184] like Figure 6 As shown in the figure, based on the experimental data under different confining pressures, the crack closure degree is plotted. and Through this curve, we can clearly see the changing law of crack closure under different confining pressures and the evolution of cracks at different stress stages.

[0185] The crack strain is exponentially related to the confining pressure. Gradually decreased to 0.0462×10 -3 ,but It increases with the increase of confining pressure. This shows that confining pressure can affect the axial crack strain of rock, but the influence gradually weakens with the increase of confining pressure. In the crack closure stage of rock, the crack gradually closes with the increase of axial stress and is completely closed at Rcc d. In order to facilitate the evaluation of the crack closure degree, the axial and radial crack closure degrees are introduced. and :

[0186] ;

[0187] in, yes The increment of each stage before the peak , post-peak stage .

[0188] when hour, , corresponding to the natural unclosed state of the rock. Department, , which corresponds to the complete closure of the rock. In the crack closure stage, under different confining pressures and and An exponential relationship such as Figure 6 As shown in The pseudo-viscous unit can be used to describe the different The crack strain under Figure 7 As shown, this unit can be used to describe The exponential relationship between the crack strain and the crack strain. The mechanical mechanism of this unit is and Gradually tends to 0, and the crack closure degree increases with R d Increases to 1, according to the formula , Figure 7 The expression of the unit can be written as:

[0189] ;

[0190] in, and is the pseudo-viscosity coefficient of the crack in the closing stage, Figure 6The fitting formula shows that the pseudo-viscosity coefficients are 0.08433 and 0.05029 respectively. In actual engineering, the corresponding The value is used to determine the type of relaxation zone in which the surrounding rock is located. For example, at a certain excavation stage, the stress state of the surrounding rock is obtained by monitoring and the is 0.8, according to Figure 8 It can be seen that the surrounding rock is in the weak relaxation zone at this time.

[0191] Extension law of damage rupture zone

[0192] Numerical simulation analysis: Using numerical simulation software such as FLAC3D, we simulate and analyze the surrounding rock damage and fracture zones under different anchor arrangement schemes. During the simulation process, we calculate the stress and strain distribution of the surrounding rock based on the rock constitutive model and failure criterion to determine whether the surrounding rock has been damaged.

[0193] Destruction criteria

[0194] The low-tensile elastic-plastic model is used to analyze the failure behavior of the surrounding rock, and the cracking conditions of the rock material are described by macroscopic strength:

[0195] ;

[0196] in, Characterize the three principal stresses of the stress tensor, For tensile strength.

[0197] Whether the rock mass has entered the plastic state is determined by the Druker-Prager criterion:

[0198] ;

[0199] in, and are the first invariant of the stress tensor and the second invariant of the stress deviator, respectively. is a constant related to rock mass material, is the tensile strength (yield limit).

[0200] A three-dimensional numerical model is established, and parameters such as rock mass parameters, initial ground stress field data, and anchor arrangement plan are input.

[0201] Perform excavation simulation calculations to obtain the distribution of stress, strain, and displacement of the surrounding rock at different excavation stages.

[0202] According to the failure criteria, determine whether the surrounding rock has been damaged and determine the scope and shape of the damaged area.

[0203] Calculation results

[0204] The distribution characteristics of the surrounding rock damage and fracture zones under different anchor bolt placement schemes were obtained, such as the location, size, and shape of the damage zone, and the range of strong and weak relaxation zones. For example, during a certain excavation stage, the damage zone of Scheme A was mainly concentrated in the crown arch and had a deep damage depth; the damage zone of Scheme B was relatively small and more concentrated; and the damage zone of Scheme C was larger, with obvious shear failure in certain areas.

[0205] The control effect of different anchor arrangement schemes on the expansion of surrounding rock damage and fracture zone is analyzed to provide a basis for optimizing the anchor arrangement scheme.

[0206] S24. Internal force of anchor rods in supporting structure: The internal force distribution of anchor rods varies under different schemes.

[0207] In Scheme A, the internal force of the anchor rod may have a large stress concentration in certain parts;

[0208] The internal force distribution of the anchor rod in Scheme B is relatively reasonable, which can better play the supporting role;

[0209] In Plan C, the internal force of the anchor rod may exceed its design bearing capacity in some parts, resulting in reduced safety of the support structure. The specific steps are as follows:

[0210] In the numerical model, the internal forces of the anchor are calculated by analyzing the load on the anchor unit. The internal forces of the anchor include axial force and shear force, and the calculation method is based on the interaction principle between the anchor and the surrounding rock.

[0211] formula

[0212] For prestressed anchor rods, the internal force calculation formula is:

[0213] ;

[0214] in, is the internal force of the anchor rod, is the prestress value, is the elastic modulus of the anchor, is the cross-sectional area of ​​the anchor rod, is the strain of the anchor rod.

[0215] The strain of the anchor rod can be calculated through numerical models or determined based on experimental test data.

[0216] Calculation process

[0217] In the numerical model, the anchor element is set and coupled with the surrounding rock element.

[0218] Perform excavation simulation calculations to obtain the strain distribution of the anchor rods.

[0219] Calculate the internal force of the anchor rod according to the internal force calculation formula of the anchor rod.

[0220] Calculation results

[0221] The internal force distribution of anchor rods under different anchor rod arrangement schemes is obtained, such as the maximum internal force of the anchor rods and the internal force distribution law. Furthermore, in a certain excavation stage, the internal force of some anchor rods in scheme A may exceed their design bearing capacity, while the internal force distribution of the anchor rods in scheme B is relatively reasonable and can meet the support requirements.

[0222] Comprehensive comparison and optimization recommendations Comprehensive evaluation: Taking into account factors such as deformation, stress, distribution of damage and rupture zones, and stress on the support structure, Scheme B performs better in controlling surrounding rock deformation, stress concentration, and damage and rupture, and is the relatively optimal anchor arrangement scheme.

[0223] Optimization direction: Further optimize the anchor arrangement: Based on Plan B, the spacing and arrangement of anchors can be further optimized to make them more consistent with the mechanical properties and deformation laws of the surrounding rock.

[0224] Strengthen the design of support structures: According to the actual conditions of the surrounding rock, reasonably adjust the parameters of the support structures, such as increasing the support strength, adopting new support materials, etc., to improve the overall performance of the support structures.

[0225] Focus on construction process control: During the construction process, strictly follow the design requirements, strengthen the monitoring and control of surrounding rock, and adjust support measures in time to ensure the safety and stability of the project.

[0226] S25. Based on the deformation and stress results, Scheme B performs better in controlling surrounding rock deformation and stress, and therefore has a relatively significant effect on improving surrounding rock stability. Scheme A has acceptable deformation and stress control effects in some areas, but is not as good as Scheme B overall. Scheme C, while having certain advantages in some aspects, is not as good as Scheme B in overall stability control.

[0227] Comprehensive evaluation to determine the optimal solution: Taking into account deformation, stress and stability factors, it is preliminarily determined that Solution B is the relatively optimal anchor arrangement solution.

[0228] S3. Error value analysis: Compare the numerical simulation results with the on-site monitoring data according to the optimal solution to obtain the comparison results, and calculate the error rate of each evaluation indicator based on the comparison results. The specific steps are as follows:

[0229] S31, deformation comparison

[0230] Error analysis: Based on the comparison results of numerical simulation and field monitoring data, the error values ​​of various evaluation indicators (such as deformation, stress, etc.) are calculated, and the causes of the errors are analyzed, such as model simplification, inaccurate parameter values, etc.

[0231] The deformation error calculation formula is: ;

[0232] This formula is used to calculate the absolute difference between the deformation value obtained by simulation and the deformation value actually monitored on site. The larger the difference, the greater the deviation between the simulation and the actual monitoring;

[0233] The calculation formula for deformation error rate is: ;

[0234] This formula divides the deformation error by the on-site monitoring value and multiplies it by 100% to obtain the relative value of the deformation error, which more intuitively reflects the degree of deviation between the simulation results and the actual monitoring results.

[0235] Comparison of arch sinking: Taking the arch of unit 1 in the main powerhouse as an example, the numerical simulation calculation shows that the arch sinking of Scheme B after the first level of excavation is 16mm. The on-site monitoring data shows that the arch sinking of this part is 15.5mm. The difference between the two is , the error rate is .

[0236] As the excavation progresses, for example, after the fifth level of excavation, the simulated settlement is 23 mm, while the on-site monitoring is 22 mm, with an error of , the error rate is .

[0237] Comparison of side wall displacement: For the upstream side wall of the main powerhouse, the numerical simulation scheme B shows a 13mm displacement into the hole after the first stage of excavation, while the on-site monitoring value is 12.5mm, with an error of , the error rate is .

[0238] After the fifth level of excavation, the simulation value is 28mm, and the on-site monitoring value is 27mm, with an error of , the error rate is .

[0239] S32, stress comparison: Compare the surrounding rock stress distribution under the action of the anchor bolt calculated by numerical simulation with the stress distribution monitored on site to verify the accuracy of the stress calculation;

[0240] The stress error calculation formula is: ;

[0241] This formula is used to calculate the absolute difference between the simulated stress value and the field monitored stress value to evaluate the accuracy of the stress calculation;

[0242] The formula for calculating the stress error rate is: ;

[0243] This formula divides the deformation error by the field monitoring value and multiplies it by 100% to obtain the relative value of the stress error, which helps evaluate the accuracy of the stress calculation.

[0244] Select key locations to monitor stress: Arrange monitoring points at key locations such as the arch ends of the main powerhouse, and compare the stress values ​​calculated by numerical simulation with the stress values ​​monitored on site.

[0245] Comparative results analysis: For example, at a certain monitoring point, the numerical simulation calculation The stress value is 42MPa, the on-site monitoring value is 40MPa, and the error is , the error rate is ;

[0246] The stress simulation value is 12MPa, the on-site monitoring value is 11MPa, and the error is , the error rate is The overall stress comparison results show that the stress distribution trend calculated by numerical simulation is basically consistent with the on-site monitoring, and the error is within an acceptable range.

[0247] Comparison of damage zones: Compare the distribution of surrounding rock damage zones under the action of anchor bolts calculated by numerical simulation with the damage zones obtained by on-site monitoring to evaluate the accuracy of damage zone prediction.

[0248] The error calculation formula is: ;

[0249] The error rate calculation formula is: ;

[0250] Comparison between the scope of simulated damage zone and monitoring: The scope of the surrounding rock plastic damage zone obtained through numerical simulation is compared with the damage zone monitored on site (such as monitoring through geological radar and other means).

[0251] Results Verification: If simulation results indicate a plastic failure zone of a certain depth in a certain area, and on-site monitoring also reveals signs of rock failure in the corresponding area, and the depth and range of the failure zone are roughly consistent, the accuracy of the failure zone prediction is verified. For example, simulations indicate a plastic failure zone depth of 2 meters in a certain location. On-site monitoring indicates poor rock integrity in that location, and geological radar detection estimates the failure depth to be between 1.8 and 2.2 meters, which is generally consistent.

[0252] S4. Establish a comparison model: establish an error correction model for the evaluation method based on the comparison results, and adjust the parameters in the numerical model based on the deviation values ​​between the numerical simulation calculation results and the field monitoring data.

[0253] S41. Error analysis: Based on the comparison results of numerical simulation and field monitoring data, calculate the error values ​​of various evaluation indicators (such as deformation, stress, etc.), and analyze the causes of the errors, such as model simplification, inaccurate parameter values, etc.

[0254] Based on the error analysis, the parameters in the numerical model are adjusted. Furthermore, if the overall deformation calculated by simulation is too large, the deformation modulus of the rock mass is too high, and the deformation modulus parameter should be appropriately reduced.

[0255] If the stress calculation error is large, it is necessary to re-evaluate the initial ground stress field parameters or the interaction parameters between the anchor and the rock mass.

[0256] S42. Establish an error correction model: By analyzing data from multiple monitoring points and different excavation stages, an error correction model is established to make the numerical simulation results closer to the actual situation, improve the accuracy and reliability of the evaluation method, and provide a more scientific basis for the design and evaluation of anchor support schemes in subsequent similar projects;

[0257] The specific steps to establish the deformation error correction model are as follows:

[0258] Assume that the deformation value of on-site monitoring is , the simulated deformation value is , the correction formula is obtained by data fitting:

[0259] ;

[0260] in, and For the fitting coefficient, a linear relationship is found through data fitting to correct the deviation between the simulated calculated value and the on-site monitoring value;

[0261] Calculated based on data from multiple monitoring points and The value of is fitted by the least square method, so that Minimum, among which is the number of monitoring points, a deformation correction model is obtained, the simulation calculation results are substituted into the deformation correction model to obtain the corrected deformation value, and the deviation between the simulation calculation value and the on-site monitoring deformation value is corrected according to the corrected deformation value.

[0262] Calculation process

[0263] Collect deformation data from multiple monitoring points, including on-site monitoring values and the corresponding simulated values .

[0264] Substitute the data into the formula In, get a about and function.

[0265] By taking derivatives or other optimization algorithms, find the function that minimizes the function. and The values ​​are shown in Table 4 below:

[0266] Table 7

[0267]

[0268] Substitute the data in Table 7 above into the formula We can get:

[0269]

[0270] right and Calculate the partial derivatives separately and set them equal to 0 to obtain the system of equations:

[0271]

[0272] Solving the equations yields and Assuming that the solution is , , then the correction formula is .

[0273] Substitute the simulation calculation results into the correction model to obtain the corrected deformation value, making it closer to the actual monitoring value. Furthermore, for a certain monitoring point, the simulation calculation deformation value is , then the corrected deformation value is .

[0274] The specific steps to establish the stress error correction model are as follows:

[0275] The stress value of on-site monitoring is The simulated stress value is , the correction formula is obtained by data fitting:

[0276] ;

[0277] in, and is the fitting coefficient;

[0278] Collect stress data from multiple monitoring points and calculate it by least square fitting method. The stress correction model is obtained by substituting the simulation calculation results into the stress correction model to obtain the corrected stress value, and the deviation between the simulation calculation value and the on-site monitoring stress value is corrected according to the corrected stress value.

[0279] Collect stress data from multiple monitoring points and perform similar least squares fitting calculations to find and The values ​​are shown in Table 8 below:

[0280] Table 8

[0281]

[0282] Substitute the data in Table 5 above into the formula We can get:

[0283]

[0284] right and Calculate the partial derivatives separately and set them equal to 0 to obtain the system of equations:

[0285]

[0286] Solving the system of equations yields and The value of , , then the correction formula is: .

[0287] The simulated stress value is substituted into the revised model to obtain the revised stress value to improve the accuracy of stress calculation.

[0288] By establishing an error correction model, the relationship between numerical simulation and field monitoring data can be better fitted, the accuracy and reliability of the evaluation method can be improved, and a more scientific basis can be provided for the design and optimization of subsequent anchor support schemes.

[0289] To help those skilled in the art better understand the present invention, the above embodiments are merely preferred technical solutions of the present invention and should not be construed as limiting the present invention. The scope of protection of the present invention shall be the technical solutions set forth in the claims, including equivalent alternatives to the technical features of the technical solutions set forth in the claims. In other words, equivalent alternatives and improvements within this scope also fall within the scope of protection of the present invention.

[0290] It should also be noted that the terms "first," "second," and the like in the specification and claims of the present invention and the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a particular order or sequence. It should be understood that the terms used in this manner are interchangeable where appropriate to facilitate the description of the embodiments of the present invention.

Claims

1. A method for evaluating the quality of anchor bolt construction layout in a main powerhouse, characterized in that: The following steps are involved: S1. Model construction: Establish three-dimensional numerical models of different anchor arrangement schemes; S2. Simulation calculation and result evaluation: Perform excavation simulation calculation based on the three-dimensional numerical model of different anchor arrangement schemes to obtain the numerical simulation calculation results of surrounding rock deformation, stress distribution, distribution of damaged and fractured areas, and stress on the support structure; Evaluate the numerical simulation results of different anchor arrangement schemes, obtain evaluation indicators, and determine the optimal scheme based on the evaluation indicators; S3. Error value analysis: Compare the numerical simulation calculation results with the on-site monitoring data according to the optimal solution to obtain the comparison results, and calculate the error rate of each evaluation indicator based on the comparison results; S4. Establishing a comparison model: establishing an error correction model for the evaluation method based on the comparison results, and adjusting the parameters in the numerical model based on the deviation values ​​between the numerical simulation calculation results and the field monitoring data; In step S4, the following steps are also included: S41. Analyze the deformation error rate, stress error rate, and depth error rate under different anchor arrangement schemes, and adjust the parameters in the three-dimensional numerical model; Among them, if the deformation calculated by simulation is large overall, it means that the value of rock deformation modulus is too high and the deformation modulus parameter should be reduced; If the stress calculation error is large, it indicates that the initial geostress field parameters or the parameters of the interaction between the anchor and the rock mass should be re-evaluated; S42, establishing an error correction model by analyzing data from multiple monitoring points and different excavation stages; In step S42, the specific steps of establishing the error correction model are as follows: Assume that the deformation value of on-site monitoring is y, and the deformation value of simulation calculation is x. The correction formula is obtained by data fitting: y=ax+b; Among them, a and b are fitting coefficients; Calculate the values ​​of a and b based on the data of multiple monitoring points, and use the least squares fitting method to make Minimum, get the deformation correction model, substitute the simulation calculation results into the deformation correction model to get the corrected deformation value, and correct the deviation between the simulation calculation value and the on-site monitoring deformation value according to the corrected deformation value; In step S42, the specific steps of establishing the stress error correction model are as follows: The stress value of on-site monitoring is The simulated calculated stress value is x, and the correction formula is obtained by data fitting: Where c and d are fitting coefficients; Collect stress data from multiple monitoring points and calculate it by least square fitting method. The stress correction model is obtained by substituting the simulation calculation results into the stress correction model to obtain the corrected stress value, and the deviation between the simulation calculation value and the on-site monitoring stress value is corrected according to the corrected stress value.

2. The method for evaluating the quality of anchor bolt construction layout of the main powerhouse according to claim 1 is characterized in that: In step S2, the deformation of the surrounding rock under different anchor arrangement schemes, including the top arch settlement and side wall displacement, is compared to evaluate the deformation control effect; Analyze the stress state of the surrounding rock under different anchor arrangement schemes, including the degree of stress concentration and uniformity of stress distribution, and evaluate the improvement of the stress state; Analyze the distribution characteristics of the surrounding rock damage and fracture zones under different bolt arrangement schemes, including the location, size and shape of the damage zone and the range of the strong relaxation zone and weak relaxation zone, and evaluate the control effect of the expansion of the surrounding rock damage and fracture zone; Analyze the internal force distribution of anchor rods under different anchor rod arrangement schemes, including the maximum internal force of anchor rods and the internal force distribution law, and evaluate the internal force distribution of anchor rods.

3. The method for evaluating the quality of anchor bolt construction layout of the main powerhouse according to claim 1 is characterized in that: In step S3, the numerical simulation results are compared with the on-site monitoring data to verify the accuracy and reliability of the assessment method. The specific comparison contents include: Deformation comparison: Compare the surrounding rock deformation under the action of anchor bolts calculated by numerical simulation with the deformation measured on-site, including deformation at different locations and excavation levels; Stress comparison: Compare the surrounding rock stress distribution under the action of the anchor bolt calculated by numerical simulation with the stress distribution monitored on site to verify the accuracy of the stress calculation; Comparison of damage zones: Compare the distribution of surrounding rock damage zones under the action of anchor bolts calculated by numerical simulation with the damage zones obtained by on-site monitoring to evaluate the accuracy of damage zone prediction.

4. The method for evaluating the quality of anchor bolt construction layout of the main powerhouse according to claim 3 is characterized in that: The error rate formulas for deformation comparison, stress comparison, and damage zone comparison are as follows: The deformation error calculation formula is: Error = |simulated deformation value - on-site monitoring deformation value|; The calculation formula for deformation error rate is: The formula for calculating stress error is: Error = |simulated stress value - on-site monitoring stress value|; The formula for calculating the stress error rate is: The depth error calculation formula is: Error = |simulated calculation depth - field monitoring depth|; The depth error rate calculation formula is: The deformation error rate calculation formula, stress error rate calculation formula and depth error rate calculation formula can be used to quantify the difference between the simulation calculation results and the on-site monitoring data. By calculating the difference, the degree of numerical deviation between the simulation value and the monitoring value can be obtained.

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