CN113221431B - Compression penetration test numerical simulation method based on particle discrete element and lattice Boltzmann - Google Patents
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Abstract
The invention discloses a compression penetration test numerical simulation method based on particle discrete elements and a lattice Boltzmann, which comprises the following steps: s1, carrying out three-dimensional particle discrete element simulation of a sand rain method and a quasi-vibration compaction method, and preparing virtual compression samples with different relative compactness; s2, axial pressure is applied to the virtual compression sample step by step, three-dimensional particle discrete element numerical simulation of a lateral confinement compression test is carried out, and a discrete element numerical model which is compressed stably under each pressure is obtained; s3, respectively slicing the discrete element numerical models subjected to pressure compression at each stage, processing the sliced images, and establishing corresponding pore structure models; s4, carrying out the lattice Boltzmann numerical simulation of seepage aiming at the established pore structure model. The method overcomes the defects of the existing indoor compression penetration test technology, has the advantages of simple principle, convenient implementation, high calculation efficiency and good application effect, and verifies the feasibility and superiority of the compression penetration test numerical simulation method based on the particle discrete element and the lattice Boltzmann.
Description
Technical Field
The invention relates to the technical field of numerical simulation of a rock-soil body compression penetration test, in particular to a compression penetration test numerical simulation method based on particle discrete elements and a lattice Boltzmann.
Background
The problem of geological body seepage flow change of foundations, side slopes, tunnels and the like caused by external load change of soil filling, excavation, building construction and the like exists in engineering construction of roads, railways, municipal works, airports, water conservancy and the like, and the research of the problem has important theoretical and engineering significance for settlement calculation after foundation filling and excavation, stability analysis of side slopes, tunnels and the like, water environment evaluation and the like.
At present, partial scholars measure compression deformation and deformed permeability coefficients of broken rock masses, sandy soil, clay and the like under different pressures through an indoor compression permeability test. However, such indoor compression penetration tests have a number of deficiencies, including mainly: (1) because the pressure measuring pipe is arranged, the height-diameter ratio of the sample is larger, and the vertical compressive stress of the lower soil body is obviously lower when the axial pressure acts, so that the whole sample is compressed unevenly; (2) axial pressure in the test process is applied through the weight, and the instantaneous reduction of soil body pores caused by the instantaneous loading of the weight can generate an impact dynamic water pressure to influence the test result; (3) in the process of the penetration test, as the side wall of the sample is a rigid boundary, concentrated seepage is easily generated at the boundary accessory, and the test result is influenced; (4) the test is time-consuming and is difficult to know the change of the microscopic structure and the seepage field in the sample, and further research on the microscopic mechanism of the compressive deformation of the rock and soil mass and the permeability change in the deformation process is hindered.
With the development of computers and numerical calculation methods, virtual test simulation technology has been widely applied in the field of geotechnical engineering. Among a plurality of numerical calculation methods, the particle discrete element method is particularly suitable for deformation simulation of rock and soil materials under the action of external load, and the lattice Boltzmann method is good at simulating seepage in complex porous media. Therefore, the two advanced numerical simulation methods are combined, and a compression permeation test numerical simulation method based on the discrete particle element and the Boltzmann is provided, so that the defects of the indoor compression permeation test are overcome, and technical support is provided for subsequent scientific research and engineering application.
Disclosure of Invention
The invention aims to solve the technical problem of providing a compression and permeation test numerical simulation method based on a particle discrete element and a lattice Boltzmann, aiming at the defects in the prior art, and realizing effective simulation of deformation of a virtual rock-soil body sample under lateral compression and permeability after deformation by combining the particle discrete element method in the field of solid mechanics and the lattice Boltzmann method in the field of fluid mechanics.
The technical scheme adopted by the invention for solving the technical problems is as follows:
the invention provides a compression permeation test numerical simulation method based on particle discrete elements and a lattice Boltzmann, which comprises the following steps:
s1, performing discrete element simulation by adopting a sand rain method and a pseudo-vibration compaction method to prepare virtual compression samples with different relative compactness; the method comprises the following steps:
s1.1, in a model space higher than a sample, generating non-overlapping particle aggregates according to a grading requirement, applying gravity load, and performing discrete element method iterative computation, wherein the particle speed is reset to zero again at certain computation cycles in the iteration to control the maximum speed of the particles after falling not to exceed a certain speed threshold, and the most loose state of the particle accumulation body is obtained after the falling is finished and the particle is computed to be balanced;
s1.2, applying a set axial pressure on the top of the particle accumulation body, setting the friction coefficient between particles to be 0, simulating the optimal vibration action approximately, and obtaining the most compact state of the particle accumulation body after calculating balance;
s1.3, maintaining the axial pressure at the top of the particle accumulation body unchanged, gradually reducing the inter-particle friction coefficient from the most loose state to simulate the vibration effect, obtaining the relationship between the inter-particle friction coefficient and the porosity of the particle accumulation body, and estimating the inter-particle friction coefficient required by obtaining the accumulation body with the given relative compactness by combining the most loose state and the most compact state through the relationship;
s1.4, compacting the loosest accumulated body under the required inter-particle friction coefficient by set axial pressure to obtain a particle accumulated body under the given relative compactness;
s2, applying axial pressure to the virtual compression sample step by step, and carrying out three-dimensional particle discrete element numerical simulation of a side limit compression test to obtain a discrete element numerical model which is compressed and stabilized under each level of pressure;
s3, slicing the discrete element numerical model after pressure compression at each stage, processing the sliced image, and establishing a corresponding pore structure model; the method comprises the following steps:
s3.1, cutting the cylindrical sample which is deformed and stabilized under each stage of pressure by a series of equally spaced sections along the axial direction, and deriving model slice images at the sections, wherein the model slice images comprise circular boundaries of the cylindrical wall on the sections on the side surfaces and corresponding circles of spherical particles on the sections;
s3.2, conducting batch processing on the derived slice images, adjusting the size of each pixel on the slice images to be equal to the vertical interval between adjacent slices, identifying the pixel belonging to the pore on each slice, corresponding to a fluid unit in a lattice Boltzmann model, so as to realize voxelization of discrete element numerical value samples, and establishing a pore structure model corresponding to the samples;
s4, carrying out lattice Boltzmann numerical simulation of seepage aiming at the established pore structure model; the method comprises the following steps:
s4.1, importing the pore structure model after deformation stabilization under each stage of pressure into a lattice Boltzmann calculation program, and setting calculation parameters, wherein the calculation parameters comprise: performing iterative calculation of lattice Boltzmann migration and collision on a particle collision model, a discrete velocity model and a fluid boundary condition;
and S4.2, stopping iterative calculation after the seepage field converges to a stable state, and calculating the permeability of the numerical value sample under the pressure level by utilizing Darcy' S law according to the applied water pressure difference.
Further, in step S1 of the present invention, the aspect ratio of the prepared virtual compressed samples with different relative compactness is not more than 0.6, so as to ensure that the sample is uniformly stressed during the subsequent compression.
Further, in step S1.1 of the present invention, the maximum speed after controlling the particles to fall down does not exceed a certain speed threshold: 0.8 m/s.
Further, in step S1.2, step S1.3, and step S1.4 of the present invention, the set axial pressure is: 14 kPa.
Further, in step S1.2, step S1.3, step S1.4, and step S2 of the present invention, the method for implementing the axial pressure includes:
generating a loading plate on the top of the sample, wherein the loading plate consists of three layers of particles, each layer of particles is regularly arranged according to a hexagon or a quadrangle, a contact constitutive model among the particles adopts a linear parallel bonding model, the rigidity of the parallel bonding is 50-100 times of the contact rigidity among the sample particles, and the strength of the parallel bonding is set to be 1.0 multiplied by 10100Pa, simulating a rigid loading plate which does not deform by using the method, and converting the required load into concentrated force on particles on the top layer of the loading plate for applying, wherein the conversion formula is as follows:
wherein, Fplaten1The axial concentrated force to be applied to each particle on the top layer of the loading plate is sigma which is the set axial compressive stress, A is the cross-sectional area of the virtual compression sample, and N isplaten1The number of particles in the top layer of the loaded plate.
Furthermore, in the step S1.3 of the present invention, the relationship between the inter-particle friction coefficient and the porosity of the particle accumulation body is determined by a plurality of numerical test points through an exponential function
Fitting to obtain; wherein n is porosity, μfricThe coefficient of friction between particles, a, b, c are fitting parameters.
Further, in the step S2 of the present invention, each stage of axial pressure is slowly applied at a loading speed of 10kPa/5000steps to avoid the influence of dynamic force during loading, and the side and bottom of the sample are restrained by rigid boundaries during loading.
Further, in step S3.2 of the present invention, the method for processing slice images includes:
during the processing of the slice images, the boundary of the circular wall on each slice image is inwards retracted by a distance equal to the radius of the minimum particle in the model, so that the boundary is overlapped with the nearby particles to avoid the generation of concentrated seepage near the boundary during the subsequent seepage simulation.
Further, in step S3.2 of the present invention, the method for processing slice images includes:
in the slice image processing process, marking the area outside the circular boundary and inside the square boundary of the picture as a solid area; besides identifying pore cells on the slice image, the solid area is further divided into two types of flow-solid boundary cells and solid internal cells, and the specific method is as follows: if the adjacent units around a certain solid unit are all solid units and comprise corresponding adjacent units on adjacent slices, the solid unit is marked as a solid internal unit; if one or more of the adjacent cells is a pore cell, i.e., a fluid cell, then the cell is labeled as a flow-solid boundary cell.
Further, in step S4.1 of the present invention, the specific calculation parameters include:
a fluid particle collision model which adopts a single relaxation time BGK collision model; a discrete velocity model, which adopts a D3Q19 model; the boundary condition is that the wall surfaces around the model and the surface of the solid particles are non-slip fluid-solid boundaries, a rebound method is adopted for processing, the fluid flow direction is along the axial direction of the sample and is driven by the pressure difference between an inlet and an outlet, and a Zou/He method is adopted for processing the pressure boundaries;
in the step S4.1, the migration and collision of the solid internal unit are not performed in the seepage calculation process, so as to reduce the calculation time.
The invention has the following beneficial effects: the compression penetration test numerical simulation method based on the particle discrete element and the lattice Boltzmann has the advantages of simple principle, convenient implementation, stable calculation and good effect, can overcome the defects of the conventional indoor compression penetration test, and is particularly shown in the following steps: 1) the seepage is simulated by a lattice Boltzmann method, the water pressure of any point in a flow field can be conveniently obtained, and a piezometer tube does not need to be arranged on the side surface of a sample like an indoor test, so that the aspect ratio of the sample can be set to be a small value to ensure that the sample is compressed more uniformly. 2) The lateral confinement compression deformation is simulated by a particle discrete element method, 3 layers of particles bonded together form a rigid loading plate, and axial pressure is slowly applied step by step through the particles of the loading plate, so that the influence of the power action can be effectively reduced. 3) By processing the image of the sample after the compression deformation, the boundary of the sample is overlapped with nearby particles, and further concentrated seepage generated near the boundary during seepage simulation is avoided. 4) The particle discrete element and lattice Boltzmann method is a mesomechanics simulation method, and a mesostructure and a corresponding seepage field of a sample in a compression deformation process can be conveniently obtained based on the compression penetration test numerical simulation of the particle discrete element and lattice Boltzmann, so that the understanding of people on the compression deformation of rock and soil mass and the internal mechanism of the permeability characteristic change in the deformation process can be further deepened.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a flow chart of a numerical simulation method of a compression penetration test based on discrete particle elements and a lattice Boltzmann according to an embodiment of the present invention;
FIG. 2 is a schematic view of a virtual compressed sample model according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a side-bounded compression model according to an embodiment of the invention;
FIG. 4 is a schematic view of slice image processing according to an embodiment of the present invention;
FIG. 5 is a graph of axial pressure versus porosity versus permeability for an embodiment of the present invention;
FIG. 6 is a cloud view of a flow field of an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in figure 1, the invention discloses a compression permeation test numerical simulation method based on particle discrete elements and a lattice Boltzmann, which comprises the following steps:
and S1, carrying out discrete element simulation of a sand rain method and a quasi-vibration compaction method, and preparing virtual compression samples with different relative compactness. The method comprises the following specific steps:
s1.1, generating non-overlapping particle aggregates in a model space which is higher than a sample according to the grading requirement, applying gravity load, carrying out discrete element method iterative computation, resetting the particle speed to zero at intervals of certain computation cycles in the iterative computation so as to control the maximum speed of the particles after falling not to exceed 0.8m/S, and obtaining the most loose state of the particle accumulation body after the falling is finished and the computation is balanced;
s1.2, applying axial pressure of 14kPa on the top of the particle accumulation body, setting the friction coefficient between particles to be 0 to approximate to an optimal vibration effect, and obtaining the most compact state of the particle accumulation body after calculation and balance;
s1.3, maintaining 14kPa axial pressure at the top of the particle accumulation body, gradually reducing the friction coefficient among particles from the most loose state to simulate the vibration effect, obtaining the relationship between the friction coefficient among the particles and the porosity of the particle accumulation body, and estimating the friction coefficient among the particles required by obtaining the accumulation body with the given relative compactness by combining the most loose state and the most compact state through the relationship;
s1.4, compacting the loosest piled body under the axial pressure of 14kPa under the required inter-particle friction coefficient to obtain the granular piled body under the given relative compactness.
As shown in FIG. 2, the particle packing of relative density 0 (i.e. the most loose state), 0.5 and 1 (i.e. the most compact state) established by the above steps based on three-dimensional particle dispersion element software PFC3D 5.0.0 is modeled as a cylinder with a diameter of 500mm, the side and bottom are limited by walls, the particle diameter is 20-40mm, the number of particles is 2333, and the height of the particle packing is less than 300 mm.
S2 three-dimensional particles for applying axial pressure to develop lateral confinement compression testAnd (5) carrying out particle discrete element numerical simulation. As shown in FIG. 3, the axial pressure is realized by generating a loading plate on the top of the sample, the loading plate is composed of three layers of particles, each layer of particles is arranged according to a hexagon rule, a contact constitutive model among the particles adopts a linear parallel bonding model, the rigidity of the parallel bonding is 100 times of the contact rigidity among the sample particles, and the strength of the parallel bonding is set to be 1.0 multiplied by 10100Pa, so as to simulate a rigid loading plate without deformation, and convert the required load into concentrated force on particles on the top layer of the loading plate for application.
In this example, a confined compression test was performed on a numerical sample having a relative density of 0.5 in fig. 2, with axial pressures applied as follows: 50kPa, 100kPa, 200kPa, 300kPa, 400kPa, axial pressure of each stage is slowly applied at a loading rate of 10kPa/5000steps, and iterative calculation to equilibrium is continued after loading to a preset pressure. And (3) arranging measuring balls at 5 different positions in the model, measuring 5 porosity values, and taking an average value as the porosity of the numerical value sample after deformation stability under the pressure.
And S3, slicing the compressed numerical model, processing the slice image, and establishing a corresponding pore structure model. The method comprises the following specific steps:
s3.1, cutting the cylindrical sample which is deformed and stabilized under each stage of pressure by a series of equally spaced sections along the axial direction, and deriving model slice images at each section, wherein the model slice images comprise the circular boundary of the cylindrical wall on the slice and the corresponding circle of the spherical particles on the slice;
and S3.2, carrying out batch processing on the derived slice images, adjusting the size of each pixel on the slice images to be equal to the vertical interval between adjacent slices, identifying pixels (corresponding to fluid units in a lattice Boltzmann model) belonging to pores on each slice, so as to realize voxelization of discrete element numerical value samples, and establishing a pore structure model corresponding to the samples.
As shown in fig. 4, which is a process of virtually compressing a sample slice image and an established pore structure model, for the sake of uniformity, this embodiment slices a portion of the sample that has deformed and stabilized under each level of pressure, the length of which is 200mm in the axial direction from the bottom, and slices the portion in the axial direction by a total of 200 sheets (the side length of the cubic unit of the lattice Boltzmann model is 1 mm). The circular wall boundaries on each slice image were indented 10mm inward so that the boundaries overlapped with nearby particles to avoid concentrated seepage near the boundaries during subsequent seepage simulations. And, the area outside the circle boundary and within the picture square boundary (the actual length corresponding to the side length is 600mm) is taken as the solid area, and the solid area is further divided into two types of flow-solid boundary unit and solid internal unit, the concrete method is: if 26 adjacent units (including corresponding adjacent units on the upper and lower adjacent slices) around a certain solid unit are all solid units, marking the solid unit as a solid internal unit; if one or more of the adjacent cells are pore cells (i.e., fluid cells), the solid cell is labeled as a flow-solid boundary cell. And in the subsequent seepage grid Boltzmann simulation process, the calculation is not carried out on the solid internal unit, so that the calculation time can be greatly saved.
And S4, carrying out lattice Boltzmann numerical simulation of seepage aiming at the established pore structure model. The method comprises the following specific steps:
and S4.1, introducing the pore structure model after deformation stabilization under each stage of pressure into a lattice Boltzmann calculation program, setting a particle collision model, a discrete velocity model, a fluid boundary condition and related calculation parameters, and performing lattice Boltzmann migration and collision iterative calculation.
And S4.2, stopping iterative calculation after the seepage field converges to a stable state, and calculating the permeability of the numerical value sample under the pressure according to the applied water pressure difference by utilizing Darcy' S law.
The seepage grid Boltzmann simulation of the embodiment is implemented by performing parallel computation on an open-source distributed computing platform palobos by adopting 8 computing threads. Fluid particle collisions employ a single relaxation time BGK collision model. The discrete velocity model is a D3Q19 model. The peripheral wall surfaces of the model and the surfaces of the solid particles are non-slip fluid-solid boundaries and are treated by a rebound method. The fluid flow direction is along the sample axis, driven by the pressure difference between the inlet and outlet, and the pressure boundary is processed by the Zou/He method. The relaxation time τ was taken to be 0.8 and the pressure difference was 1 × 10-7(grid unit). As shown in fig. 5The pressure-porosity-permeability relationship obtained from the simulation is shown, and the flow field cloud obtained from the lattice Boltzmann simulation is shown in fig. 6. The compression and permeation test numerical simulation method based on the discrete particle element and the Boltzmann can better simulate the lateral limit compression deformation of the rock-soil body and the change characteristic of the permeability in the deformation process, and further verifies the advantages of the invention.
It should be understood that the above are only specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily made by those skilled in the art within the technical scope of the present invention disclosed herein should be covered within the scope of the present invention.
Claims (10)
1. A compression penetration test numerical simulation method based on particle discrete elements and lattices Boltzmann is characterized by comprising the following steps:
s1, performing discrete element simulation by adopting a sand rain method and a quasi-vibration compaction method to prepare virtual compression samples with different relative compactness; the method comprises the following steps:
s1.1, generating non-overlapping particle aggregates according to the grading requirement in a model space higher than a sample, applying gravity load, carrying out discrete element method iterative computation, resetting the particle speed to zero every certain computation cycle in the iterative computation so as to control the maximum speed of the particles after falling not to exceed a certain speed threshold, and obtaining the most loose state of the particle accumulation body after the falling is finished and the computation is balanced;
s1.2, applying a set axial pressure on the top of the particle accumulation body, setting the friction coefficient between particles to be 0, simulating the optimal vibration action approximately, and obtaining the most compact state of the particle accumulation body after calculating balance;
s1.3, maintaining the axial pressure at the top of the particle accumulation body unchanged, gradually reducing the inter-particle friction coefficient from the most loose state to simulate the vibration effect, obtaining the relationship between the inter-particle friction coefficient and the porosity of the particle accumulation body, and estimating the inter-particle friction coefficient required by obtaining the accumulation body with the given relative compactness by combining the most loose state and the most compact state through the relationship;
s1.4, compacting the loosest accumulated body under the required inter-particle friction coefficient by set axial pressure to obtain a particle accumulated body under the given relative compactness;
s2, applying axial pressure to the virtual compression sample step by step, and carrying out three-dimensional particle discrete element numerical simulation of a side limit compression test to obtain a discrete element numerical model which is compressed and stabilized under each level of pressure;
s3, slicing the discrete element numerical model after pressure compression at each stage, processing the sliced image, and establishing a corresponding pore structure model; the method comprises the following steps:
s3.1, cutting the cylindrical sample which is deformed and stabilized under each stage of pressure by a series of equally spaced sections along the axial direction, and deriving model slice images at the sections, wherein the model slice images comprise circular boundaries of the cylindrical wall on the sections on the side surfaces and corresponding circles of spherical particles on the sections;
s3.2, conducting batch processing on the derived slice images, adjusting the size of each pixel on the slice images to be equal to the vertical interval between adjacent slices, identifying the pixel belonging to the pore on each slice, corresponding to a fluid unit in a lattice Boltzmann model, so as to realize voxelization of discrete element numerical value samples, and establishing a pore structure model corresponding to the samples;
s4, carrying out lattice Boltzmann numerical simulation of seepage aiming at the established pore structure model; the method comprises the following steps:
s4.1, importing the pore structure model after deformation stabilization under each stage of pressure into a lattice Boltzmann calculation program, and setting calculation parameters, wherein the calculation parameters comprise: performing iterative calculation of lattice Boltzmann migration and collision on a particle collision model, a discrete velocity model and a fluid boundary condition;
and S4.2, stopping iterative calculation after the seepage field converges to a stable state, and calculating the permeability of the numerical value sample under the pressure level by utilizing Darcy' S law according to the applied water pressure difference.
2. The method for numerical simulation of a compression and permeation test based on Boltzmann of discrete particles according to claim 1, wherein the aspect ratio of the prepared virtual compressed samples with different relative compactness in the step S1 is not more than 0.6, so as to ensure uniform stress on the samples during subsequent compression.
3. The method for numerical simulation of a compression penetration test based on Boltzmann of discrete particles according to claim 1, wherein in the step S1.1, the maximum speed of the particles after falling is controlled not to exceed a certain speed threshold: 0.8 m/s.
4. The method for numerical simulation of a compression and permeation test based on Boltzmann of discrete particles according to claim 1, wherein the axial pressure set in the steps S1.2, S1.3 and S1.4 is: 14 kPa.
5. The method for numerical simulation of a compression and permeation test based on Boltzmann of discrete particles and grid according to claim 1, wherein in the step S1.2, the step S1.3, the step S1.4 and the step S2, the axial pressure is realized by:
generating a loading plate on the top of the sample, wherein the loading plate consists of three layers of particles, each layer of particles is regularly arranged according to a hexagon or a quadrangle, a contact constitutive model among the particles adopts a linear parallel bonding model, the rigidity of the parallel bonding is 50-100 times of the contact rigidity among the sample particles, and the strength of the parallel bonding is set to be 1.0 multiplied by 10100Pa, simulating a rigid loading plate which does not deform by using the method, converting the required load into a concentrated force on particles on the top layer of the loading plate to apply, wherein the calculation formula is as follows:
wherein, Fplaten1The axial concentrated force to be applied to each particle on the top layer of the loading plate is sigma which is the set axial compressive stress, A is the cross-sectional area of the virtual compression sample, and N isplaten1The number of particles in the top layer of the loaded plate.
6. The method for numerical simulation of compressive permeability test based on Boltzmann of discrete particles according to claim 1, wherein in step S1.3, the relationship between the friction coefficient between particles and the porosity of the particle stack is determined by a plurality of numerical test points through an exponential function
Fitting to obtain; wherein n is porosity, μfricThe coefficient of friction between particles, a, b, c are fitting parameters.
7. The method for numerical simulation of compression infiltration tests based on Boltzmann of discrete elements and lattices of particles according to claim 1, wherein in the step S2, the axial pressure of each stage is slowly applied at a loading speed of 10kPa/5000steps to avoid the influence of dynamic action during loading, and the side and bottom of the sample during the axial loading are restrained by rigid boundaries.
8. The method for numerical simulation of a compression penetration test based on Boltzmann of discrete particles and grid according to claim 1, wherein in the step S3.2, the method for processing slice images comprises:
during the processing of the slice images, the boundary of the circular wall on each slice image is inwards retracted by a distance equal to the radius of the minimum particle in the model, so that the boundary is overlapped with the nearby particles to avoid the generation of concentrated seepage near the boundary during the subsequent seepage simulation.
9. The method for numerical simulation of a compression penetration test based on Boltzmann of discrete particles and grid according to claim 1, wherein in the step S3.2, the method for processing slice images comprises:
in the slice image processing process, marking the area outside the circular boundary and inside the square boundary of the picture as a solid area; besides identifying pore cells on the slice image, the solid area is further divided into two types of flow-solid boundary cells and solid internal cells, and the specific method is as follows: if the adjacent units around a certain solid unit are all solid units and comprise corresponding adjacent units on adjacent slices, the solid unit is marked as a solid internal unit; if one or more of the adjacent cells is a pore cell, i.e., a fluid cell, then the cell is labeled as a flow-solid boundary cell.
10. The method for numerical simulation of compressive permeability test based on Boltzmann of discrete elements and lattices in accordance with claim 1, wherein in the step S4.1, the specific calculation parameters include:
a fluid particle collision model which adopts a single relaxation time BGK collision model; a discrete velocity model, which adopts a D3Q19 model; the boundary condition is that the peripheral wall surfaces of the model and the surfaces of the solid particles are non-slip flow-solid boundaries, a rebound method is adopted for processing, the flow direction of the fluid is along the axial direction of the sample and is driven by the pressure difference of an inlet and an outlet, and the pressure boundary is processed by a Zou/He method;
in the step S4.1, the migration and collision of the solid internal unit are not performed in the seepage calculation process, so as to reduce the calculation time.
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