Pore ​​structure generation and permeability prediction method for anisotropic fiber materials

Abstract

The present invention provides a method for predicting the pore structure and permeability of anisotropic fiber materials. A fiber single-rod model is established based on the structural characteristic parameters of the fiber material, such as the zenith angle θ and the circumference angle #imgabs0#. The fiber single-rod construction process is repeated until the material target porosity ε is reached. In this process, the minimum spacing d allowed between fibers is set. gap And the maximum number of iterations N max As a restriction condition; then the permeability of the generated anisotropic fiber material is simulated and predicted using a finite volume simulation program written based on the open source fluid mechanics library OpenFOAM. Based on the pore scale characterization structure of the generated fiber material, the present invention combines the finite volume method to develop a prediction method for the permeability of the fiber material, which can quantitatively analyze the influence of structural parameters on the permeability and provide a reference for the design and preparation of fiber materials.

Description

Technical Field

[0001] The invention belongs to the technical field of fiber materials, and in particular relates to a method for generating pore structures of anisotropic fiber materials and predicting permeability. Background Art

[0002] Fiber materials have the advantages of large specific surface area, low volume density, strong impact resistance, and good structural design. They are widely used in technical fields such as hypersonic aircraft thermal protection, ultra-low energy consumption and energy-saving buildings, wind power generation, and solar thermal utilization. Permeability is an important parameter to characterize the flow characteristics of fiber materials and is a core parameter that affects the material's process performance. Rapid and accurate prediction of permeability is the basis for the design and application of fiber materials.

[0003] Experimental measurement, empirical formula calculation and simulation are the main means to obtain the permeability of fiber materials. The experimental method is the most direct and accurate, but the implementation cost is high, and the results of a single experiment are only valid for one material. The empirical formula is applicable to isotropic materials, and the scope of use is limited. In contrast, the permeability prediction method based on simulation has the advantages of short implementation cycle, low execution cost and wide application range, and has been widely used in recent years.

[0004] Permeability is closely related to the structural characteristics of materials. Accurately establishing a geometric model that characterizes the structural characteristics of materials is a prerequisite for ensuring the correctness of permeability simulation results. After completing the fiber structure modeling, the geometric model is meshed to achieve discretization of the calculation domain. Subsequently, simulation methods such as finite element or finite volume can be used to predict the permeability of fiber materials.

[0005] At present, scanning imaging reconstruction technology is the most accurate material structure modeling method, but the post-processing method of this type of method is complex. Another method is to compile a program to virtually generate a fiber pore structure based on the understanding of the material structure. This method has the advantages of fast modeling speed and flexible operation. It has developed rapidly in recent years, but most modeling programs can only generate isotropic fiber structures and are not suitable for the prediction of the permeability of anisotropic fiber materials. Therefore, it is necessary to construct a method for generating the pore structure of anisotropic fiber materials and predicting their permeability, explore the influence of the anisotropic structural characteristics of the material on the permeability, and provide guidance for the material structure design. Summary of the invention

[0006] The purpose of the present invention is to propose a method suitable for the generation of pore structure and permeability prediction of anisotropic fiber materials, to achieve accurate modeling of anisotropic pore structure and rapid and high-precision prediction of material permeability, and further to reveal the influence of anisotropic structural characteristics of fiber materials on their permeability performance and enrich the theory of fiber material structure design.

[0007] A method for generating pore structure and predicting permeability of anisotropic fiber materials is characterized by comprising the following steps:

[0008] Step 1. Set the calculation domain size and basic parameters of fiber materials;

[0009] Step 2. Set the structure generation control parameters, including the minimum spacing d allowed between fibers. gap And the maximum number of iterations N max ;

[0010] Step 3. Generate the zenith angle θ, which obeys the von Mises distribution;

[0011] Step 4. Generate circular angle Obey uniform random distribution;

[0012] Step 5. Pass through the origin O of the system coordinate system, with θ and Generate straight line l0 for zenith angle and circular angle;

[0013] Step 6. Randomly generate a point P(X P ,Y P ,Z P ), translate the straight line l0 along the vector OP to generate a new straight line l;

[0014] Step 7. Take line l as the center line, d f Generate cylindrical fiber rods for the diameter and calculate the minimum distance d between the fiber rods i ; Judge d i With d gap The size relationship between them is, if d i ≤d gap And N i <N max , then regenerate the current fiber rod, N i is the current iteration number, N max is the maximum number of iterations; if d i ≤d gap And N i ≥N max , then clear all fiber rod data and regenerate the structure; if d i >d gap , the currently generated fiber rod is considered valid, and its volume V in the calculation domain is calculated and recorded. i , the total volume of fibers in the calculation domain is accumulated Where M is the number of fibers currently generated, and the porosity ε in the current computational domain is calculated and saved. i =1-V f / V c , V c is the volume of the computational domain;

[0015] Step 8. Determine the porosity ε in the current calculation domain i and the target porosity ε; if ε i >ε, save the current fiber rod data and continue to generate the next fiber rod. i ≤ε, the current structure is considered to meet the requirements, the cylindrical surface of the fiber rod is divided into triangular facets, and the fiber structure in the calculation domain is output as an STL file;

[0016] Step 9. Smooth the generated structure in the open source CAD software FreeCAD, and then use the open source meshing tool SnappyHexMesh to adaptively mesh the structure;

[0017] Step 10. Import the generated grid file into the written finite volume simulation program, set the boundary conditions, and then perform simulation calculations to predict the permeability;

[0018] The finite volume simulation program is written based on the open source fluid mechanics library OpenFOAM, uses the SIMPLE algorithm to solve the steady-state momentum equation of the fluid, obtains the velocity field in the calculation domain through iterative calculation, and calculates the permeability using Darcy's law.

[0019] Furthermore, in step 1, the basic parameters include: the length of the calculation domain L X 、Width L Y 、Height L Z , fiber diameter d f As well as the material porosity ε, record the computational domain volume V c =L X L Y L Z , establish the system coordinate system XYZ along the length, width and height directions at the vertices of the computational domain, and the origin of the coordinate system is O.

[0020] Furthermore, in step 3, the probability density function of the von Mises distribution is in the form of f(θ|λ,κ)=e κcos(θ-λ) / 2πI0(κ), where θ∈[0,2π), λ represents the average value of the zenith angle θ, I0(κ) represents the modified Bessel function of order 0, κ is the characteristic value measuring the concentration of the zenith angle θ, when κ approaches 0, the probability density function is close to a uniform distribution; when κ approaches ∞, the distribution of the probability density function is close to a Gaussian distribution with a mean of λ and a variance of 1 / κ; the expression of the zenith angle θ is: θ=arccos(1-2R θ );where R θ is a uniform random distribution function of the zenith angle, ranging from 0 to 1.

[0021] Furthermore, in step 4, the circumferential angle Generate a circular angle in the XY plane: In the formula, R φ is a uniform random distribution function of the circular angle, with a value between 0 and 1.

[0022] Furthermore, in step 5, the zenith angle of the straight line is θ, that is, the angle between the straight line and the Z axis; the circumferential angle is That is, the angle between the projection of the straight line on the XY plane and the X axis; establish the straight line equation X / m=Y / n=Z / k of the straight line l0 in the XYZ coordinate system; randomly generate a point P(X P ,Y P ,Z P ), the equation of the straight line l is (XX P ) / m=(YY P ) / n=(ZZ P ) / k.

[0023] Further, in step 7, the minimum distance d between the fiber rods in step 7 is i is calculated by the following formula:

[0024]

[0025] Where P i P j The vector representing the line between the point on the current fiber centerline and the point on the generated fiber centerline, D i is the direction vector of the current fiber centerline, D j is the direction vector of the generated fiber centerline.

[0026] Furthermore, in step 9, when the structure meets the target porosity requirement, the generated structure is smoothed and post-processed in the open source CAD software FreeCAD, and then the structure is adaptively meshed using the open source meshing tool SnappyHexMesh.

[0027] Furthermore, the specific steps of step 10 are as follows: first, import the generated grid file into the finite volume simulation program; then, select the discrete format and set the calculation parameters, the convection term in the momentum equation is discretized using the first-order upwind format; based on the Gaussian theory, the diffusion term is discretized, the central difference interpolation format is used, and the grid non-orthogonality correction is performed; the smoothing solver is used for momentum prediction, and the multi-grid solver is used to solve the pressure Poisson equation; finally, the inlet and outlet pressures are set to p, respectively. inlet With p outlet , perform simulation calculations, and obtain the material thickness direction, i.e., the component velocity U in the Z-axis direction based on the simulation results Z , according to Darcy's law, solve the permeability K in the material thickness directionZZ =μU Z / (p inlet -p outlet ), where μ is the dynamic viscosity of the fluid.

[0028] Furthermore, in the process of solving the pressure Poisson equation, the relaxation factors of solution speed and pressure were set to 0.7, and the convergence residuals were set to 1×10 -6 .

[0029] Furthermore, the set inlet pressure p inlet Greater than outlet pressure p outlet .

[0030] Through the above scheme, the present invention compiles a virtual generation program, adopts von Mises distribution to characterize the non-uniform distribution characteristics of fibers, and establishes a pore structure geometric model of anisotropic fiber materials; develops a fiber material permeability simulation program based on the finite volume method, and verifies the accuracy of the constructed geometric model and permeability simulation program by comparing with the permeability prediction results in the empirical formula; uses the constructed geometric model as an input file, and the permeability data of this type of material can be obtained through the simulation program.

[0031] For anisotropic fiber materials, the present invention provides a complete solution including pore structure modeling and permeability prediction, which can provide data support for structural design and evaluation in related technical fields.

[0032] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention and implement it according to the contents of the specification, the following is a detailed description of the preferred embodiments of the present invention in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a flow chart of the method for generating the structure of anisotropic fiber materials and predicting the permeability;

[0034] Figure 2 is the probability density function of the von Mises distribution corresponding to different eigenvalues ​​κ;

[0035] Figure 3 The pore structures of fiber materials generated by different eigenvalues ​​κ, where (a) is κ = 5 and (b) is κ = 50;

[0036] Figure 4 The comparison between the geometric model of anisotropic fiber material generated by the present invention and the SEM image of real fiber material, (a) and (c) are the fiber arrangement in the thickness direction when κ=0.5 and κ=50, respectively, (b) and (d) are the fiber arrangement in the thickness direction when ρ=100kg / m 3 ,ρ=200kg / m 3SEM image of ceramic thermal insulation material in thickness direction;

[0037] Figure 5 is a geometric model of anisotropic fiber material generated by the present invention, wherein (a) is κ=1, (b) is κ=100;

[0038] Figure 6 It is a comparison between the predicted value of fiber material permeability and the value calculated by empirical formula. DETAILED DESCRIPTION

[0039] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments, but the protection scope of the present invention is not limited thereto.

[0040] Ginseng Figure 1 As shown, this embodiment provides a method for generating pore structure of anisotropic fiber material and predicting permeability, comprising the following steps:

[0041] Step 1, setting the calculation domain size and basic parameters of fiber materials;

[0042] Step 2, setting structure generation control parameters;

[0043] Step 3, generate the zenith angle θ, which obeys the von Mises distribution;

[0044] Step 4: Generate circular angle Obey uniform random distribution;

[0045] Step 5: Pass through the origin O of the system coordinate system with θ and Generate straight line l0 for zenith angle and circular angle;

[0046] Step 6: Randomly generate a point P(X P ,Y P ,Z P ), translate the straight line l0 along the vector OP to generate a new straight line l;

[0047] Step 7, take line l as the center line, d f Generate cylindrical fiber rods for the diameter and calculate the minimum distance d between the fiber rods i ;

[0048] Step 8: Determine the porosity ε in the current calculation domain i The size between the target porosity ε;

[0049] Step 9: Graphics post-processing and meshing;

[0050] Step 10: Set boundary conditions and perform permeability prediction.

[0051] The present invention provides a method for generating the pore structure of anisotropic fiber materials and predicting the permeability. In terms of the structural modeling of fiber materials, compared with the model reconstruction technology based on scanning imaging, the developed structure virtual generation method has the advantages of strong flexibility, controllable structural parameters, and simple model post-processing; in terms of the permeability prediction method, compared with the experimental test method, the developed permeability prediction method has the advantages of low implementation cost, low material cost, and fast prediction speed, and compared with the empirical formula calculation method, it has the advantage of a wide range of applications.

[0052] The specific steps of this method are:

[0053] 1. Set the calculation domain size and basic parameters of fiber materials.

[0054] The basic parameters include: calculation domain length L X 、Width L Y 、Height L Z , fiber diameter d f As well as the material porosity ε, record the computational domain volume V c =L X L Y L Z , establish the system coordinate system XYZ along the length, width and height directions at the vertices of the computational domain, and the origin of the coordinate system is O.

[0055] 2. Set the structure generation control parameters.

[0056] The control parameters for structure generation include: the minimum spacing d between fibers allowed gap And the maximum number of iterations N max , d gap The role of N is to prevent the distance between fibers from being too small, which will affect the quality of the subsequent grid system. max Its function is to prevent the program from abnormal and entering an endless loop.

[0057] 3. Generate the zenith angle θ, which obeys the von Mises distribution. The expression of the zenith angle θ is:

[0058] θ=arccos(1-2R θ )

[0059] In the formula, R θ is a uniform random distribution function of the zenith angle, ranging from 0 to 1.

[0060] The von Mises distribution has good mathematical controllability and is often used in directional statistics. Its probability density function is in the form of f(θ|λ,κ)=e κcos(θ-λ) / 2πI0(κ), where θ∈0,2π), λ represents the average value of the zenith angle θ, I0(κ) represents the modified Bessel function of order 0, κ is the eigenvalue measuring the concentration of the zenith angle θ, when κ approaches 0, the probability density function is close to a uniform distribution; when κ approaches ∞, the distribution of the probability density function is close to a Gaussian distribution with a mean of λ and a variance of 1 / κ. Figure 2 The variation of the von Mises probability density function with the eigenvalue κ is shown.

[0061] 4. Generate circular angle Follows uniform random distribution.

[0062] The circumference angle Generate a circular angle in the XY plane:

[0063]

[0064] In the formula, is a uniform random distribution function of the circular angle, with a value between 0 and 1.

[0065] 5. Passing through the origin O of the system coordinate system, with θ and Generate the line l0 for the zenith angle and the circular angle.

[0066] The zenith angle of the straight line (the angle between the straight line and the Z axis) is θ, and the circumferential angle (the angle between the projection of the straight line on the XY plane and the X axis) is The linear equation X / m=Y / n=Z / k of the line l0 is established in the XYZ coordinate system.

[0067] 6. Randomly generate a point P(X P ,Y P ,Z P ), translate the straight line l0 along the vector OP to generate a new straight line l, and establish the equation of the straight line l in the form of (XX P ) / m=(YY P ) / n=(ZZ P ) / k.

[0068] A straight line is established according to the zenith angle, and its straight line equation in the system coordinate system is:

[0069]

[0070] 7. Take straight line l as the center line, d f Generate cylindrical fiber rods for the diameter and calculate the minimum distance d between the fiber rods i .

[0071] For non-intersecting fiber rods, if the spacing is too small, it will affect the quality of the subsequent mesh system and even make it difficult to generate the mesh. Therefore, after generating a fiber rod, it is necessary to determine the distance between it and other fiber rods. According to the fiber diameter and the straight line equation of the fiber rod centerline, the minimum distance d between the generated fiber rods is calculated. i , the minimum distance calculation formula is as follows:

[0072]

[0073] Where P i P j The vector representing the line between the point on the current fiber centerline and the point on the generated fiber centerline, D i is the direction vector of the current fiber centerline, D j is the direction vector of the generated fiber centerline.

[0074] Judgement i With d gap The size relationship between them is, if d i ≤d gap And N i <N max , N i is the current iteration number, then the current fiber rod is regenerated. If d i ≤d gap And N i ≥N max , then clear all fiber rod data and regenerate the structure. If d i >d gap , the currently generated fiber rod is considered valid, and the volume V of the currently generated fiber rod in the calculation domain is calculated and recorded. i , the total volume of all fibers in the calculation domain is accumulated Where M is the number of fibers currently generated, and the porosity ε in the current computational domain is calculated and saved. i =1-V f / V c , where V c is the volume of the computational domain.

[0075] 8. Determine the porosity ε in the current calculation domain i The size between the target porosity ε.

[0076] For the generated fiber cylinder, determine whether it meets the target porosity requirement. i >ε, save the current fiber rod data and continue to generate the next fiber rod. i ≤ε, the current structure is considered to meet the requirements, the cylindrical surface is divided into triangular face elements, and the fiber structure in the calculation domain is output as an STL file.

[0077] 9. Graphics post-processing and grid division.

[0078] When the structure meets the target porosity requirements, in order to facilitate the subsequent meshing of the grid system, the generated geometric structure needs to be smoothed to reduce the presence of sharp parts in the structure. The generated structure is smoothed in the open source CAD software FreeCAD using the Laplace smoothing algorithm in the software. The structure is then adaptively meshed using the open source meshing tool SnappyHexMesh.

[0079] Figure 3 The pore structure of the fiber material generated when κ takes different values ​​is shown, where the calculation domain is a cube with a side length of 500 μm, the target porosity is 95%, and the fiber rod diameter is 10 μm.

[0080] Figure 4 The comparison between the fiber structure geometric model generated by different eigenvalues ​​κ and the SEM image of the real fiber material is shown. By adjusting the value of κ, the pore scale structure of the fiber material at different densities can be simulated and constructed. The results show that the virtual structure has a high degree of approximation to the real structure and can characterize the pore characteristics of the material in three-dimensional space.

[0081] 10. Set boundary conditions and make permeability predictions.

[0082] A finite volume simulation program was written based on the open source fluid mechanics library OpenFOAM. The SIMPLE algorithm was used to solve the steady-state momentum equation of the fluid. The velocity field in the calculation domain was obtained through iterative calculation, and the permeability was calculated using Darcy's law. First, the generated grid file was imported into the simulation program; then, the discrete format was selected and the calculation parameters were set. The convection term in the momentum equation was discretized using the first-order upwind format; the diffusion term was discretized based on Gaussian theory, and the central difference interpolation format was used and the grid non-orthogonal correction was performed; the smoothing solver was used for momentum prediction, and the multi-grid solver was used to solve the pressure Poisson equation. The relaxation factors for solving the velocity and pressure were set to 0.7, and the convergence residuals were set to 1×10 -6 ; Finally, set the inlet and outlet pressures to p inlet With p outlet , the inlet pressure must be greater than the outlet pressure, perform simulation calculations, and obtain the material thickness direction, that is, the component velocity U in the Z-axis direction based on the simulation results. Z , according to Darcy's law, solve the permeability K in the material thickness direction ZZ =μU Z / (p inlet -p outlet ), where μ is the dynamic viscosity of the fluid.

[0083] In order to verify the accuracy of the method in the present invention, fiber materials with different porosities were simulated to obtain the dimensionless permeability r f is the fiber radius, and is compared with the empirical formula prediction results of Woudberg and Clague et al. for calculating the dimensionless permeability of isotropic materials. The empirical formula proposed by Woudberg is as follows:

[0084]

[0085] The empirical formula proposed by Clague et al. is as follows:

[0086]

[0087] Figure 5 The geometric model of anisotropic fiber materials is shown. Different eigenvalues ​​κ represent different concentrations of zenith angles. As the κ value increases, the anisotropic characteristics of the fiber material are enhanced, showing obvious layered stacking characteristics. When the eigenvalue κ = 1, the material structure is closer to isotropy, and when κ = 100, the material shows obvious anisotropic characteristics. Figure 6 The permeability prediction results of fiber materials with a porosity range of 70%-90% are shown. The permeability simulation results of κ=1 and κ=100 are compared in the figure. The results show that the material permeability decreases as the characteristic value κ increases; Figure 6 It can be seen from the permeability simulation results and the calculation results of the empirical formula of Woudberg and Clague et al. that the error is small and within the allowable range, which verifies the accuracy of the fiber material geometric model and permeability prediction method in the present invention.

[0088] The present invention compiles a virtual generation program, adopts von Mises distribution to characterize the non-uniform distribution characteristics of fibers, and establishes a pore structure geometric model of anisotropic fiber materials; develops a fiber material permeability simulation program based on the finite volume method, and verifies the accuracy of the constructed fiber material geometric model and the permeability simulation program by comparing with the permeability prediction results in the empirical formula; uses the constructed fiber material geometric model as an input file, and can obtain the permeability data of this type of material through the simulation program.

[0089] For anisotropic fiber materials, the present invention provides a complete solution including pore structure modeling and permeability prediction, which can provide data support for structural design and evaluation in related technical fields.

[0090] The embodiments are preferred implementations of the present invention, but the present invention is not limited to the above-mentioned implementations. Any obvious improvements, substitutions or modifications that can be made by those skilled in the art without departing from the essential content of the present invention belong to the protection scope of the present invention.

Claims

1. A method for generating pore structure of anisotropic fiber material and predicting permeability, characterized in that: The steps include: Step 1. Set the calculation domain size and basic parameters of fiber materials; Step 2. Set the structure generation control parameters, including the minimum spacing d allowed between fibers. gap And the maximum number of iterations N max ; Step 3. Generate the zenith angle θ, which obeys the von Mises distribution; Step 4. Generate circular angle Obey uniform random distribution; Step 5. Pass through the origin O of the system coordinate system, with θ and Generate straight line l0 for zenith angle and circular angle; Step 6. Randomly generate a point P(X P ,Y P ,Z P ), translate the straight line l0 along the vector OP to generate a new straight line l; Step 7. Take line l as the center line, d f Generate cylindrical fiber rods for the diameter and calculate the minimum distance d between the fiber rods i ; Judge d i With d gap The size relationship between them is, if d i ≤d gap And N i <N max , then regenerate the current fiber rod, N i is the current iteration number, N max is the maximum number of iterations; if d i ≤d gap And N i ≥N max , then clear all fiber rod data and regenerate the structure; if d i >d gap , the currently generated fiber rod is considered valid, and its volume V in the calculation domain is calculated and recorded. i , the total volume of fibers in the calculation domain is accumulated Where M is the number of fibers currently generated, and the porosity ε in the current computational domain is calculated and saved. i =1-V f / V c , V c is the volume of the computational domain; Step 8. Determine the porosity ε in the current calculation domain i and the target porosity ε; if ε i >ε, save the current fiber rod data and continue to generate the next fiber rod. i ≤ε, the current structure is considered to meet the requirements, the cylindrical surface of the fiber rod is divided into triangular facets, and the fiber structure in the calculation domain is output as an STL file; Step 9. Smooth the generated structure in the open source CAD software FreeCAD, and then use the open source meshing tool SnappyHexMesh to adaptively mesh the structure; Step 10. Import the generated grid file into the written finite volume simulation program, set the boundary conditions, and then perform simulation calculations to predict the permeability; The finite volume simulation program is written based on the open source fluid mechanics library OpenFOAM, uses the SIMPLE algorithm to solve the steady-state momentum equation of the fluid, obtains the velocity field in the calculation domain through iterative calculation, and calculates the permeability using Darcy's law.

2. The method for generating pore structure of anisotropic fiber material and predicting permeability according to claim 1, characterized in that: In step 1, the basic parameters include: calculation domain length L X 、Width L Y 、Height L Z , fiber diameter d f As well as the material porosity ε, record the computational domain volume V c =L X L Y L Z , establish the system coordinate system XYZ along the length, width and height directions at the vertices of the computational domain, and the origin of the coordinate system is O.

3. The method for generating pore structure of anisotropic fiber material and predicting permeability according to claim 1, characterized in that: In step 3, the probability density function of the von Mises distribution is in the form of f(θ|λ,κ)=e κcos(θ-λ) / 2πI0(κ), where θ∈[0,2π), λ represents the average value of the zenith angle θ, I0(κ) represents the modified Bessel function of order 0, κ is the characteristic value that measures the concentration of the zenith angle θ, when κ approaches 0, the probability density function approaches a uniform distribution; when κ approaches ∞, the distribution of the probability density function is close to a Gaussian distribution with a mean of λ and a variance of 1 / κ; The expression of the zenith angle θ is: θ=arccos(1-2R θ );where R θ is a uniform random distribution function of the zenith angle, ranging from 0 to 1.

4. The method for generating pore structure of anisotropic fiber material and predicting permeability according to claim 1, characterized in that: In step 4, the circumferential angle Generate a circular angle in the XY plane: In the formula, is a uniform random distribution function of the circular angle, with a value between 0 and 1.

5. The method for generating pore structure of anisotropic fiber material and predicting permeability according to claim 1, characterized in that: In step 5, the zenith angle of the straight line is θ, that is, the angle between the straight line and the Z axis; the circumferential angle is That is, the angle between the projection of the straight line on the XY plane and the X axis; establish the straight line equation X / m=Y / n=Z / k of the straight line l0 in the XYZ coordinate system; randomly generate a point P(X P ,Y P ,Z P ), the equation of the straight line l is (XX P ) / m=(YY P ) / n=(ZZ P ) / k.

6. The method for generating pore structure of anisotropic fiber material and predicting permeability according to claim 1, characterized in that: The minimum distance d between the fiber rods in step 7 i Calculated by the following formula: Where P i P j The vector representing the line between the point on the current fiber centerline and the point on the generated fiber centerline, D i is the direction vector of the current fiber centerline, D j is the direction vector of the center line of the generated fiber.

7. The method for generating pore structure of anisotropic fiber material and predicting permeability according to claim 1, characterized in that: The smoothing post-processing in step 9 adopts the Laplace smoothing algorithm; the meshing adopts the open source meshing tool SnappyHexMesh to perform adaptive meshing on the structure.

8. The method for generating pore structure of anisotropic fiber material and predicting permeability according to claim 1, characterized in that: The specific steps of step 10 are as follows: first, import the generated grid file into the finite volume simulation program; then, select the discrete format and set the calculation parameters, the convection term in the momentum equation is discretized using the first-order upwind format; based on the Gaussian theory, the diffusion term is discretized, the central difference interpolation format is used, and the grid non-orthogonality correction is performed; the smoothing solver is used for momentum prediction, and the multi-grid solver is used to solve the pressure Poisson equation; finally, the inlet and outlet pressures are set to p respectively. inlet With p outlet , perform simulation calculations, and obtain the material thickness direction, i.e., the component velocity U in the Z-axis direction based on the simulation results Z , according to Darcy's law, solve the permeability K in the material thickness direction ZZ =μU Z / (p inlet -p outlet ), where μ is the dynamic viscosity of the fluid.

9. The method for generating pore structure of anisotropic fiber material and predicting permeability according to claim 8, characterized in that: In the process of solving the pressure Poisson equation, the relaxation factors of solution speed and pressure were set to 0.7, and the convergence residuals were set to 1×10 -6 .

10. The method for generating pore structure of anisotropic fiber material and predicting permeability according to claim 8, characterized in that: Set inlet pressure p inlet Greater than outlet pressure p outlet .

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