Continuous and discontinuous numerical simulation method for evaluating size effect of cryptocrystalline basalt

Abstract

The invention relates to a continuous and discontinuous numerical simulation method for researching cryptocrystalline basalt size effect evaluation, which can comprehensively consider heterogeneity of a rock internal structure and mechanical response of samples with different sizes so as to reveal the influence of the size effect on rock mechanical characteristics. By establishing a numerical model based on an actual rock microstructure and applying a continuous and discontinuous numerical simulation technology, the mechanical behaviors of cryptocrystalline basalt of different sizes under a uniaxial or triaxial compression condition can be accurately simulated; the obtained rock mass mechanical parameters under the REV size can be used as input parameters of large-scale numerical simulation of engineering rock mass, and a scientific basis is provided for rock engineering design and construction.

Description

Technical Field

[0001] The invention belongs to the technical field of rock mechanics and numerical simulation, and particularly relates to a continuous and discontinuous numerical method for simulating the size effect evaluation of cryptocrystalline basalt. Background Art

[0002] Cryptocrystalline basalt is a typical hard and brittle rock with well-developed internal microcracks and is widely used in engineering construction. The mechanical properties and behavior characteristics of hard and brittle rocks can be mastered through indoor mechanical tests, but it is difficult to deeply reveal the internal mechanism of progressive deformation and failure of rocks. The essence of hard and brittle rock failure is the result of internal crack initiation, expansion and mutual penetration, which actually undergoes a transformation process from continuous to discontinuous. At present, there is still a lack of simulation methods to reveal the initiation, expansion and penetration process of internal cracks in hard and brittle rocks.

[0003] The finite element-discrete element coupled method (FDEM) pioneered by Munjiza combines the advantages of both continuous and discontinuous numerical methods and has become the most promising simulation technology for particle interaction, cracking and fragmentation processes of brittle rock materials.

[0004] Due to the existence of microcracks, the mechanical properties of cryptocrystalline basalt, such as strength and deformation, have a certain size dependence. With the rapid development of computational rock mechanics, the discrete fracture network simulation technology (DFN) based on statistics and probability theory has provided a new approach for the study of rock mass structure. The synthetic rock mass method (SRM) is a numerical method that combines the DFN model representing the discontinuous structure with the conventional numerical model representing the complete matrix, which can fully consider the scale effect and anisotropic characteristics of the rock mass properties. At present, there is no combination of discrete fracture network simulation technology and continuous-discontinuous numerical methods to evaluate the size effect of cryptocrystalline basalt. Summary of the invention

[0005] The purpose of the present invention is to provide a continuous and discontinuous numerical simulation method for evaluating the size effect of cryptocrystalline basalt, which can simulate the response of rock samples of different sizes under mechanical loading and reveal the influence of size effect on the mechanical properties of rock. The method of the present invention can not only provide the macroscopic mechanical parameters of rock, but also reveal the initiation, expansion and penetration process of cracks inside rock, providing a scientific basis for rock engineering design and construction.

[0006] To this end, the above-mentioned purpose of the present invention is achieved through the following technical solutions:

[0007] A continuous and discontinuous numerical simulation method for evaluating the size effect of cryptocrystalline basalt, the method comprising the following steps:

[0008] S1. Collect cryptocrystalline basalt samples and obtain their microstructural data;

[0009] S2. Establish a statistical model of hidden microcracks based on microstructure data;

[0010] S3, Generate random fracture networks of different sizes based on the statistical model of micro-fractures;

[0011] S4. Use continuous and discontinuous numerical simulation software to construct a numerical model and perform mechanical loading on the numerical model;

[0012] S5. Analyze the simulation results and evaluate the influence of size effect on the mechanical properties of cryptocrystalline basalt.

[0013] Furthermore, in step S1: microstructure data is obtained by taking photos of cracks on the rock surface and performing image processing.

[0014] Furthermore, in step S2: the statistical model of microcracks includes the statistical distribution of geometric parameters such as length, inclination, density, etc. of the cracks.

[0015] Furthermore, in step S3: a Monte Carlo method is used to generate random variables of various geometric parameters respectively, and the coordinates of the starting point and the end point of the crack are calculated, thereby generating a set of random crack networks.

[0016] Furthermore, during the random crack generation process: it is determined whether the generated random crack is within the sample, if so, the crack is accepted, otherwise it is abandoned and the next crack is generated until all cracks meet the requirements.

[0017] Furthermore, in step S3: random fracture networks of different sizes are obtained by first generating two fracture network models of sufficiently large sizes based on the statistical characteristic data of micro-cracks, and then randomly sampling to generate a fracture network model of smaller size, with the aspect ratio set to a constant value, and the specific size is determined according to actual engineering requirements.

[0018] Furthermore, in step S4: the continuous-discontinuous numerical simulation software is Irazu or other software supporting FDEM technology, and the fracture network model representing the microcracks is embedded in the FDEM code representing the complete matrix to create a numerical model representing the cryptocrystalline basalt block.

[0019] Furthermore, the mesoscopic mechanical parameters of the numerical model are obtained by running a series of uniaxial compression numerical tests, and by continuously adjusting and iterating the mesoscopic mechanical parameters, the macroscopic mechanical parameters of the synthetic rock are matched with the test results of the indoor test.

[0020] Furthermore, the constitutive model of the numerical model is that the continuous unit part representing the complete matrix adopts a linear elastic constitutive model, and the discontinuous crack network model part representing the subtle cracks adopts the maximum tensile stress criterion and the Mohr-Coulomb failure criterion.

[0021] Furthermore, the loading scheme and boundary conditions of the numerical model are as follows: the rock loading mode is uniaxial compression, two slightly wider loading plates are arranged at the upper and lower ends, and axial loading is achieved through displacement control.

[0022] Furthermore, in step S5: numerical simulation is run to record and analyze the stress-strain response, macroscopic mechanical parameters and crack propagation changes of samples of different sizes under mechanical loading, and to study the influence of size effect on the mechanical properties of cryptocrystalline basalt.

[0023] The beneficial effects of the present invention are as follows: 1. The distribution characteristics of the microcracks in cryptocrystalline basalt are accurately and quantitatively described by probability statistics. 2. A numerical model for accurately characterizing the internal defects of cryptocrystalline basalt is constructed by synthetic rock mass method. 3. The changing laws of the initiation, initiation, expansion and penetration of cracks in hard and brittle basalt are revealed by continuous and discontinuous numerical analysis. 4. The scale dependence of the geometric and mechanical properties of basalt blocks containing microcracks is accurately revealed. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A flow chart of the numerical simulation method for evaluating the size effect of cryptocrystalline basalt provided by the present invention;

[0025] Figure 2 The cryptocrystalline basalt block and the sketch of the cryptocrystalline basalt cracks provided by the present invention;

[0026] Figure 3 The statistical laws of the geometric parameters of the micro-cracks provided by the present invention;

[0027] Figure 4 Schematic diagram of the numerical model of cryptocrystalline basalt of different sizes provided by the present invention;

[0028] Figure 5-1 , 5-2 , 5-3, and 5-4 respectively show the effects of the test size provided by the present invention on different mechanical parameters of cryptocrystalline basalt. DETAILED DESCRIPTION

[0029] To further understand the present invention, the present invention is described in more detail below in conjunction with the accompanying drawings and specific embodiments.

[0030] like Figure 1 As shown, the present invention provides a continuous and discontinuous numerical method for simulating the evaluation of the size effect of cryptocrystalline basalt, comprising the following steps:

[0031] Step S1, collecting cryptocrystalline basalt samples and obtaining their microstructure data;

[0032] Step S2, establishing a hidden microcrack statistical model based on microstructure data;

[0033] Step S3, generating random fracture networks of different sizes based on a micro-fracture statistical model;

[0034] Step S4, constructing a numerical model using continuous and discontinuous numerical simulation software, and performing mechanical loading on the model;

[0035] Step S5, analyzing the simulation results to evaluate the influence of the size effect on the mechanical properties of cryptocrystalline basalt.

[0036] The specific steps are as follows:

[0037] S1: The macro- and micro-structural characteristics of cryptocrystalline basalt were obtained before mechanical loading, revealing the development characteristics of micro-cracks.

[0038] S101: Using the window measurement method, a large number of cryptocrystalline basalt blocks taken from the underground powerhouse chambers were photographed and their dimensions were measured (usually tens of centimeters). Then they were imported into CAD for image processing to obtain parameters that characterize the crack characteristics, mainly including the length, orientation (the angle between the crack direction and the length direction of the rock block), density, etc. The actual objects and sketches of the cryptocrystalline cracks of some rock blocks are shown in Figure 2 .

[0039] from Figure 2 It can be seen that irregular micro-cracks are commonly developed in basalt. They are short, closed, randomly distributed, and extend intermittently. The sizes range from a few centimeters to tens of centimeters, and there is no obvious regularity in the orientation. The cracks in some samples are basically consistent with the length direction of the rock blocks, and belong to Grade V hard structural surfaces.

[0040] S2: Based on the microcrack structure data, the statistical laws of microcrack geometric parameters are obtained.

[0041] S201: Figure 3 As shown in the figure, for cracks with a length of 10 mm or more, a total of 28 rock blocks and about 800 cracks were statistically analyzed. The inclination angle of the hidden microcracks obeys a uniform distribution, and the length obeys a log-normal distribution (μ = 3.68, σ = 0.58). The calculated distribution density is 0.0003 cracks / mm 2 , area ratio P21 is 0.014mm / mm 2 .

[0042] S3: Generate random fracture network models of different sizes based on the micro-crack statistical model.

[0043] S301: In order to understand the influence of sample size on the geometric and mechanical parameters of cryptocrystalline basalt and explore its scale correlation, a larger research area with a size of 5m×5m was determined. The corresponding number of cracks was calculated based on the crack density, and the number of cracks was 7500.

[0044] S302: Based on the statistical distribution forms and parameters of the fracture occurrence, trace length and density, the Monte Carlo method is used to generate random variables of each geometric parameter, calculate the starting point and end point coordinates of the fracture, and thus generate a set of random fracture networks.

[0045] S303: Determine whether the generated random crack is in the sample. If so, accept the crack; otherwise, give up and continue to generate the next crack until all cracks meet the requirements.

[0046] S304: Randomly sample the large-sized random fracture network model to generate fracture network models of smaller sizes (20 DFN models are generated for each size), whose widths are 25, 50, 100, 150, 200, 300, 400, 500 and 600 mm respectively, and the aspect ratio is constant at 2, see Figure 4 .

[0047] S4: Use continuous and discontinuous numerical simulation software to construct a numerical model and perform mechanical loading on the model.

[0048] S401: The generated fracture network model representing cryptocrystalline fractures of different sizes is embedded into the FDEM code representing the complete matrix to create a numerical model that accurately represents the cryptocrystalline basalt.

[0049] S402: Verify the microscopic parameters to be input into the continuous and discontinuous numerical simulations.

[0050] First, two sufficiently large fracture grid models (2m×2m) were generated; then virtual drilling and coring were randomly performed on the numerical model, and standard-sized specimens were made, retaining only the complete specimens and those with internal fractures. The presence or absence of fractures, the length, inclination, and number of fractures were all different for each specimen. A series of uniaxial compression numerical tests were run, and the macroscopic mechanical parameters of the synthetic rock were matched with the test results of the indoor test by continuously adjusting and iterating the mesoscopic mechanical parameters. The input mesoscopic parameters are shown in Table 1.

[0051] Table 1 Micromechanical parameters used in numerical simulation of cryptocrystalline basalt

[0052]

[0053] S403: Select a constitutive model for continuous and discontinuous numerical simulations.

[0054] The linear elastic constitutive model is used for the continuous unit part representing the complete matrix, and the maximum tensile stress criterion and the Mohr-Coulomb failure criterion are used for the discontinuous crack network model part representing the hidden microcracks.

[0055] S404: Formulate loading schemes and apply boundary conditions for continuous and discontinuous numerical simulations.

[0056] The numerical simulation uses uniaxial compression loading to carry out uniaxial compression tests on rocks of different sizes. Two slightly wider loading plates are arranged at the upper and lower ends, and axial loading is achieved through displacement control.

[0057] Step S5, analyzing the simulation results to evaluate the influence of the size effect on the mechanical properties of cryptocrystalline basalt.

[0058] Taking into account the randomness of fracture network modeling and the amount of computational work, 10 numerical models were created at each level of size, and the average value of all sample calculation results was taken as the result of this working condition.

[0059] Taking the size effect of mechanical parameters as an example, Figure 5-1 , 5-2 , 5-3, and 5-4 give the changing patterns of compressive strength, tensile strength, cohesion and friction angle of cryptocrystalline basalt under different sample sizes.

[0060] As the size of the sample increases, the mean uniaxial compressive strength of the model decreases, and the decrease is more obvious at small sizes. After a certain size, it maintains a roughly constant range, and the discrete degree and fluctuation range of the uniaxial compressive strength of different samples at the same size decrease. When the sample size is ≤200mm, the coefficient of variation is greater than 20%, and the fluctuation range of the uniaxial compressive strength is very wide, which means that the model at this size is not representative. When the sample size is 300-400mm, the coefficient of variation basically drops to about 10% (the coefficient of variation of 400mm is slightly greater than 20%), and the fluctuation range of the uniaxial compressive strength at this time is significantly reduced; when the sample size is greater than 500mm, the coefficient of variation is below 10%, and the uniaxial compressive strength at this time tends to the asymptotic value as a whole. Therefore, the mechanical REV width characterized by the discrete degree and fluctuation range of the uniaxial compressive strength of samples at different sizes is 500mm, and the uniaxial compressive strength at this size is about 52.53MPa.

[0061] Therefore, combining the discrete fracture network simulation technology with the continuous-discontinuous numerical method can better evaluate the size effect of the mechanical properties of cryptocrystalline basalt.

[0062] The above-mentioned specific implementation methods are used to explain the present invention and are only preferred embodiments of the present invention, rather than limiting the present invention. Any modifications, equivalent substitutions, improvements, etc. made to the present invention within the spirit of the present invention and the protection scope of the claims shall fall within the protection scope of the present invention.

Claims

1. A continuous and discontinuous numerical simulation method for evaluating the size effect of cryptocrystalline basalt, characterized by: The method comprises the following steps: S1. Collect cryptocrystalline basalt samples and obtain their microstructural data; S2. Establish a statistical model of hidden microcracks based on microstructure data; S3, Generate random fracture networks of different sizes based on the statistical model of micro-fractures; S4. Use continuous and discontinuous numerical simulation software to construct a numerical model and perform mechanical loading on the numerical model; S5. Analyze the simulation results and evaluate the influence of size effect on the mechanical properties of cryptocrystalline basalt.

2. The continuous and discontinuous numerical simulation method for evaluating the size effect of cryptocrystalline basalt according to claim 1, characterized in that: In step S2: the statistical model of micro-cracks includes the statistical distribution of geometric parameters, and the geometric parameters include the length, inclination and density of the cracks.

3. The continuous and discontinuous numerical simulation method for evaluating the size effect of cryptocrystalline basalt according to claim 1, characterized in that: In step S3: the Monte Carlo method is used to generate random variables of various geometric parameters respectively, and the coordinates of the starting point and the end point of the crack are calculated, so as to generate a set of random crack networks.

4. The continuous and discontinuous numerical simulation method for evaluating the size effect of cryptocrystalline basalt according to claim 3, characterized in that: During the random crack generation process: determine whether the generated random crack is within the specimen. If so, accept the crack; otherwise, abandon it and continue to generate the next crack until all cracks meet the requirements.

5. The continuous and discontinuous numerical simulation method for evaluating the size effect of cryptocrystalline basalt according to claim 1, characterized in that: In step S3: random fracture networks of different sizes are obtained by first generating two fracture network models of sufficiently large sizes based on the statistical characteristic data of micro-fractures, and then randomly sampling to generate a fracture network model of smaller size, with the aspect ratio set to a constant value.

6. The continuous and discontinuous numerical simulation method for evaluating the size effect of cryptocrystalline basalt according to claim 1, characterized in that: In step S4: the continuous-discontinuous numerical simulation software is software that supports FDEM technology, and the fracture network model representing the microcracks is embedded in the FDEM code representing the complete matrix to create a numerical model representing the cryptocrystalline basalt block.

7. The continuous and discontinuous numerical simulation method for evaluating the size effect of cryptocrystalline basalt according to claim 6, characterized in that: The mesoscopic mechanical parameters of the numerical model are obtained by running a series of uniaxial compression numerical tests, and by continuously adjusting and iterating the mesoscopic mechanical parameters, the macroscopic mechanical parameters of the synthetic rock are matched with the test results of the indoor test.

8. The continuous and discontinuous numerical simulation method for evaluating the size effect of cryptocrystalline basalt according to claim 6, characterized in that: The constitutive model of the numerical model is that the continuous unit part representing the complete matrix adopts the linear elastic constitutive model, and the discontinuous crack network model part representing the hidden microcracks adopts the maximum tensile stress criterion and the Mohr-Coulomb failure criterion.

9. The continuous and discontinuous numerical simulation method for evaluating the size effect of cryptocrystalline basalt according to claim 6, characterized in that: The loading scheme and boundary conditions of the numerical model are as follows: the rock loading mode is uniaxial compression, two slightly wider loading plates are arranged at the upper and lower ends, and axial loading is achieved through displacement control.

10. The continuous and discontinuous numerical simulation method for evaluating the size effect of cryptocrystalline basalt according to claim 1, characterized in that: In step S5: numerical simulation is run to record and analyze the stress-strain response, macroscopic mechanical parameters and crack propagation variation of samples of different sizes under mechanical loading, and to study the influence of size effect on the mechanical properties of cryptocrystalline basalt.

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