Method, device, equipment and medium for obtaining microstructure parameters of a porous material

Abstract

The present invention provides a method, device, equipment and medium for obtaining the microstructure parameters of a porous material. A method for obtaining the microstructure parameters of a porous material provided by the present invention includes: obtaining the three-dimensional morphology of a porous medium; based on the three-dimensional morphology of the porous medium, obtaining the pore distribution and solid distribution information thereof; based on the pore distribution and the solid distribution information, obtaining the computational domain of the porous medium; the computational domain of the porous medium includes the centroid and radius information of the pores in the porous medium; performing Voronoi space segmentation based on the computational domain, and obtaining the local connectivity information of the porous medium based on the space segmentation information, where the local connectivity information includes the position and size of the throats and the connection relationship between the pores and the throats. This application can obtain the microstructure parameters of the porous material and can obtain the local connectivity information, so as to efficiently describe the internal energy and mass transport of the porous medium.

Description

Technical Field

[0001] The present invention relates to the technical field of porous materials, and particularly to a method, device, equipment and medium for obtaining microstructural parameters of porous materials. Background Art

[0002] As one of the key common basic researches, multiphase flow in porous media has important applications in the fields of energy and environment, such as fresh water extraction from aquifers, resource exploitation in oil and gas reservoirs, drug transport, and microfluidics in food processing.

[0003] Currently, with the increasingly serious problem of global climate change, carbon neutrality and sustainable development have become the world consensus. The research on multiphase flow in porous media is also gradually expanding from the traditional research direction mainly focused on improving the resource recovery rate of oil and gas reservoirs to directions such as geological sequestration of carbon dioxide and hydrogen, electrochemical energy storage and conversion technologies, etc.

[0004] In the past few years, resolution X-ray imaging and analysis and simulation technologies based on image processing have developed rapidly, changing people's understanding of fluid flow in pores and promoting the research on multiphase flow mechanisms in porous media and engineering applications. At the same time, numerical simulation research on heat and mass transfer processes in porous media has also been greatly developed. The traditional macroscopic continuity model relying on grid division, physical field discretization and basic conservation laws can obtain some macroscopic parameters of heat and mass transfer processes in porous media, but this method focuses on macroscopic processes and cannot describe the details of local spatial structures. In recent years, micro-mesoscopic scale models capable of efficiently describing microstructural details have emerged. Pore network simulation regards porous media as composed of connected pores and solids, and the pores are connected by throats, which is used for the transport of substances and chemical reaction processes in porous media. Compared with the lattice Boltzmann method, the pore network model has a faster calculation speed and is regarded as the most efficient mesoscopic scale model.

[0005] The pore structure of porous media has an important influence on the accuracy of pore network simulation. The most commonly used pore network construction methods in the literature are regular pore network and random distribution method to construct pore networks, but these two methods only have the same macroscopic parameters (porosity, gas diffusion coefficient, liquid phase permeability, etc.) as carbon paper and carbon felt, and cannot obtain the real microstructures of porous media (pore distribution, pore size distribution, local connectivity, etc.). The pore network model capable of efficiently describing the internal energy and mass transport in porous media still has limitations. In addition, most of the current pore network extraction methods ignore the solid structure information, resulting in little knowledge of the transport phenomena in the solids of porous media.

[0006] Therefore, it is necessary to provide a method, device, equipment and medium for obtaining microstructural parameters of porous materials to effectively solve the above problems. Summary of the Invention

[0007] The present invention provides a method, apparatus, device and medium for obtaining the microstructure parameters of a porous material.

[0008] An embodiment of the present invention provides a method for obtaining the microstructure parameters of a porous material, including:

[0009] Obtaining the three-dimensional morphology of a porous medium;

[0010] Based on the three-dimensional morphology of the porous medium, obtaining its pore distribution and solid distribution information;

[0011] Based on the pore distribution and the solid distribution information, obtaining the computational domain of the porous medium;

[0012] Performing root Voronoi space segmentation based on the computational domain, and obtaining the local connectivity information of the porous medium based on the space segmentation information; the local connectivity information includes the position and size of the throat and the connection relationship between the pore and the throat.

[0013] Preferably, obtaining the three-dimensional morphology of the porous medium includes: performing three-dimensional scanning on the porous medium to obtain its three-dimensional morphology; or

[0014] Performing two-dimensional scanning on the cross-section of the porous medium along a preset direction to obtain a plurality of two-dimensional graphics; and

[0015] Performing three-dimensional reconstruction based on the plurality of two-dimensional graphics to obtain the three-dimensional morphology of the porous medium.

[0016] Preferably, performing three-dimensional reconstruction based on the plurality of two-dimensional graphics to obtain the three-dimensional morphology of the porous medium includes:

[0017] Performing graphic preprocessing on the two-dimensional graphics, where the graphic preprocessing includes adjusting the two-dimensional graphics to the optimal angle and removing the background area;

[0018] Distinguishing the solid area and the pore area in the two-dimensional graphics;

[0019] Overlaying the processed two-dimensional graphics to form the three-dimensional morphology of the porous medium.

[0020] Preferably, obtaining the pore distribution information based on the three-dimensional morphology of the porous medium includes:

[0021] Based on the three-dimensional morphology of the porous medium, obtaining the size of its three-dimensional matrix, and based on the size of the three-dimensional matrix, obtaining the cross-sectional area of each section of the porous medium, and based on the cross-sectional area, obtaining the number of pixels on the cross-section;

[0022] Obtain the number of pore pixels in each cross-section of the porous medium in a certain direction, and take the ratio of the number of pore pixels in the cross-section to the number of pixels in the cross-section as the porosity of the cross-section;

[0023] Based on the porosities of the corresponding cross-sections of the porous medium in each direction, obtain the porosity distribution in each direction.

[0024] Preferably, based on the three-dimensional morphology of the porous medium, obtain its solid distribution information, including:

[0025] Remove the noise on the cross-section of the three-dimensional morphology of the porous medium based on the noise conditions;

[0026] Based on the solid pixel distribution on the cross-section, obtain the solid distribution information of the porous medium.

[0027] Preferably, the obtaining of the computational domain of the porous medium based on the pore distribution and the solid distribution information includes:

[0028] Obtain the initial boundary of sphere growth;

[0029] Based on the pore distribution and the solid distribution information, obtain the distance assignment of each pixel point within the initial boundary of sphere growth; the distance assignment is the distance value between the pixel point and the nearest pore;

[0030] Based on the distance assignment of each pixel point within the initial boundary of sphere growth, obtain the centroid and radius of the largest sphere; the information of the computational domain includes the centroid and radius information of the largest sphere;

[0031] Based on all the pixel points occupied by the largest sphere, obtain a new boundary of sphere growth until the radius of the largest sphere reaches the set value.

[0032] Preferably, the performing of root Voronoi space partitioning based on the computational domain includes:

[0033] Perform root Voronoi space partitioning on the computational domain based on a preset number of partitions to obtain cell information; the space partitioning information includes the cell information;

[0034] Based on the cell information, obtain the overall computational porosity of the porous medium;

[0035] Based on the pore distribution and the solid distribution information, obtain the overall detected porosity of the porous medium;

[0036] Optimize the root Voronoi space partitioning based on the comparison result between the overall computational porosity and the overall detected porosity to update the cell information.

[0037] Preferably, obtaining the local connectivity information of the porous medium based on the space segmentation information includes:

[0038] Obtaining the area of the polygon corresponding to each cell in the cell information;

[0039] Based on the cell information, obtaining the weighted radius of the side length of the solid corresponding to the side of the polygon;

[0040] Based on the weighted radius of the side length of the solid corresponding to the side of the polygon, obtaining the length of the corresponding throat;

[0041] Based on the area of the polygon corresponding to each cell in the cell information and the length of the corresponding throat, obtaining the extrusion volume of each polygon;

[0042] Based on the extrusion volume of each polygon and the length of the corresponding throat, obtaining the volume and equivalent radius of the throat, and the volume and equivalent radius of the pore; and

[0043] Based on the label information of each cell and its adjacent cells in the cell information, obtaining the connection relationship between the pores and the throats.

[0044] This application also provides a device for obtaining the microstructure parameters of a porous material, and the device includes:

[0045] An acquisition module, configured to acquire the three-dimensional morphology of the porous medium;

[0046] A first calculation module, configured to obtain the pore distribution and solid distribution information thereof based on the three-dimensional morphology of the porous medium;

[0047] A second calculation module, configured to obtain the computational domain of the porous medium based on the pore distribution and the solid distribution information;

[0048] A third calculation module, configured to perform Voronoi space segmentation based on the computational domain, and obtain the local connectivity information of the porous medium based on the space segmentation information; the local connectivity information includes the position and size of the throat and the connection relationship between the pores and the throats.

[0049] This application also provides a computer device, including a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, the steps of the method described in any one of the above are implemented.

[0050] This application also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method described in any one of the above are implemented.

[0051] Compared with the prior art, the technical solution of the embodiment of the present invention has the following beneficial effects:

[0052] A method for obtaining microstructure parameters of a porous material provided by an embodiment of the present invention can obtain pore distribution and solid distribution information in the microstructure of the porous material, showing more real microstructure characteristics of the porous medium compared with traditional methods, which is of great significance for understanding heat and mass transfer inside the porous medium (such as the transport of substances and charges in the gas diffusion layer of a proton exchange membrane fuel cell). It can also obtain local connectivity information of the porous medium, that is, extract the connection relationship between the solid structure and the solid network, so as to obtain the transport phenomenon of electrons and the like in the solid network. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for description in the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention, rather than all embodiments. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0054] Figure 1 Schematic flow chart of the method for obtaining microstructure parameters of a porous material provided by an embodiment of the present invention;

[0055] Figures 2a to 2d Schematic two-dimensional graph of X-ray microtomography provided by an embodiment of the present invention;

[0056] Figure 3 Schematic diagram of three-dimensional morphology reconstruction of X-ray microtomography and carbon paper / carbon felt provided by an embodiment of the present invention;

[0057] Figure 4 Schematic diagram of porosity distribution of carbon paper / carbon felt in different directions provided by an embodiment of the present invention;

[0058] Figure 5 Schematic diagram of carbon fiber diameter distribution provided by an embodiment of the present invention;

[0059] Figure 6 Schematic diagram of sphere growth in carbon paper / carbon felt provided by an embodiment of the present invention;

[0060] Figure 7 Schematic diagram of pore network obtained by sphere growth model and root Voronoi space partitioning algorithm provided by an embodiment of the present invention;

[0061] Figure 8 Schematic diagram of pore network obtained by random distribution method and root Voronoi space partitioning provided by an embodiment of the present invention;

[0062] Figure 9Schematic diagram of root Voronoi space partitioning for the computational domain of a porous medium provided by an embodiment of the present invention;

[0063] Figure 10 Distribution diagram of pore network pore size and throat diameter obtained by the sphere growth model and the root Voronoi space partitioning method provided by an embodiment of the present invention;

[0064] Figure 11 Distribution diagram of pore network pore size and throat diameter obtained by the random distribution method and the root Voronoi space partitioning provided by an embodiment of the present invention.

[0065] Figure 12 Effect of liquid phase coverage rate on the unilateral interface of the gas diffusion layer on the effective diffusion coefficient of oxygen provided by an embodiment of the present invention. Detailed implementation manners

[0066] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0067] The technical solutions of the present invention will be described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.

[0068] Based on the problems existing in the prior art, an embodiment of the present invention provides a method, device, equipment, and medium for obtaining the microstructure parameters of a porous material.

[0069] Figure 1 Flow schematic diagram of a method for obtaining the microstructure parameters of a porous material provided by an embodiment of the present invention. Now refer to Figure 1 , an embodiment of the present invention provides a method for obtaining the microstructure parameters of a porous material, including:

[0070] Step S11, obtaining the three-dimensional morphology of the porous medium.

[0071] Step S12, based on the three-dimensional morphology of the porous medium, obtaining its pore distribution and solid distribution information.

[0072] Step S13, based on the pore distribution and solid distribution information, obtaining the computational domain of the porous medium.

[0073] Step S14: Perform root Voronoi space segmentation based on the computational domain, and obtain the local connectivity information of the porous medium based on the space segmentation information; the local connectivity information includes the positions, sizes of the pore throats, and the connection relationships between the pores and the throats.

[0074] The porous materials protected by this application may include microporous materials, mesoporous materials, and macroporous materials. Taking carbon paper and carbon felt as the porous medium in this application as an example, multiple carbon fibers may be included in the carbon paper and carbon felt. Each carbon fiber may be arranged substantially in the same direction, that is, their axes may be substantially in the same direction, and irregular pores are formed between the carbon fibers. It should be noted that the porous medium described in this application is not limited to carbon paper and carbon felt, and may also include porous silicon, nitrides, borides, etc.

[0075] In some embodiments, step S11 directly obtains the three-dimensional morphology of the porous medium by performing three-dimensional scanning on the porous medium. In other embodiments, step S11 may also perform two-dimensional scanning on the porous medium to obtain multiple two-dimensional graphics, and perform three-dimensional reconstruction based on the multiple two-dimensional graphics to obtain the three-dimensional morphology of the porous medium.

[0076] Specifically, in the method of reconstructing the three-dimensional morphology using two-dimensional graphics, taking GP-H-090 carbon paper and carbon felt as an example to obtain the two-dimensional graphics, cut the carbon paper and carbon felt to the required size. As Figure 3 shown, using X-ray microtomography technology, layer by layer scan the y-z cross-section of the carbon paper and carbon felt (the radial cross-section of the carbon fiber can be obtained) to obtain the two-dimensional image of the carbon paper and carbon felt. The step length of the scan can be set according to actual needs. The shorter the step length, the more accurate the finally reconstructed three-dimensional morphology. In other embodiments, various two- or three-dimensional modern imaging technologies such as transmission electron microscopy (TEM) and scanning electron microscopy (SEM) can also be used.

[0077] In some embodiments, performing three-dimensional reconstruction based on multiple two-dimensional graphics to obtain the three-dimensional morphology of the porous medium includes: performing graphic preprocessing on the two-dimensional graphics, and the graphic preprocessing includes adjusting the two-dimensional graphics to the best angle and removing the background area. Distinguish between the solid area and the pore area in the two-dimensional graphics. Stack the processed two-dimensional graphics to form the three-dimensional morphology of the porous medium.

[0078] Specifically, as Figure 2a and 2bAs shown, rotate the two-dimensional graph of the carbon paper carbon felt to make the angle of the image easier to process (at this time, the matrix size corresponding to the two-dimensional graph will change accordingly). In this embodiment, the optimal angle of the two-dimensional graph can be such that the length direction of the effective graph in the two-dimensional graph is the vertical direction and the width direction is the horizontal direction. In other embodiments, it can also be set such that the length direction of the effective graph in the two-dimensional graph is the horizontal direction and the length direction is the vertical direction.

[0079] As Figure 2b and 2c shown, the background area in the two-dimensional graph is other areas except the effective graph. The effective graph in this embodiment can include the pore graph area and the solid fiber graph area in the carbon paper carbon felt, and the boundary between the effective graph and the background area can be the outer contour of the carbon paper carbon felt at this cross-section.

[0080] The step of distinguishing the solid area and the pore area in the two-dimensional graph can use methods such as binarization or MASK-RCNN to perform pixel distinction on the solid area and the pore area in the cropped two-dimensional graph. The solid area in this embodiment can be the area occupied by carbon fibers in the carbon paper carbon felt, and the pore area can be the pore area formed between carbon fibers. In this embodiment, the solid in the two-dimensional graph of the carbon paper carbon felt is represented as pixel 0, and the pore is represented as pixel 1. In other embodiments, the solid in the two-dimensional graph of the carbon paper carbon felt can also be represented as pixel 1, and the pore is represented as pixel 0.

[0081] Specifically, binarization methods such as the fixed threshold method, Otsu's method, and adaptive threshold method can be used to set the pixel points greater than a certain value in the two-dimensional graph as 1 pixel points, and the pixel points less than a certain value as 0 pixel points, so as to distinguish the solid and pore areas in the two-dimensional graph of the carbon paper carbon felt.

[0082] Specifically, the MASK-R-CNN method is also used. First, manually label the solid area in the image (the rest is the pore area) to provide samples for machine learning. Then, train and verify the model of the convolutional neural network through the obtained samples, so as to identify the solid and pore areas of each two-dimensional graph.

[0083] As Figure 3 shown, when the solid and pore areas of each two-dimensional graph are identified, all the two-dimensional graphs in part b) are superimposed to accurately reconstruct the three-dimensional morphology of the carbon paper carbon felt to obtain part a). The thickness of the carbon paper carbon felt provided in this embodiment, that is, the superimposed length, is 280 microns, but the superimposed thickness of the two-dimensional graphs in the embodiments of this application is not limited to this length. Constructing the three-dimensional morphology using the two-dimensional graph in this embodiment is beneficial to reducing costs and has a wider adaptability.

[0084] In some embodiments, obtaining the pore distribution information based on the three-dimensional morphology of the porous medium in step S12 includes:

[0085] Step S121: Based on the three-dimensional morphology of the porous medium, obtain the size of its three-dimensional matrix, and based on the size of the three-dimensional matrix, obtain the cross-sectional area of the porous medium, and based on the cross-sectional area, obtain the number of pixels on the cross-section.

[0086] Step S122: Obtain the number of pore pixels in each cross-section of the porous medium in one direction, and use the ratio of the number of pore pixels on the cross-section to the number of pixels on the cross-section as the porosity of the cross-section.

[0087] Step S123: Based on the porosities of the corresponding cross-sections of the porous medium in each direction, obtain the porosity distribution in each direction.

[0088] Specifically, determine the size of the three-dimensional matrix of the porous medium. In this embodiment, the porous medium is taken as a cuboid as an example.

[0089] Taking the x-direction as an example, the porosity at a certain x value (for example: a0) is:

[0090] poro_x_a0 = (A0) / (b*c)

[0091] where A0 is the number of pore pixels (1 pixel) of the numerical matrix corresponding to the y-z plane when x is a0, and (b*c) is the number of pixels of the corresponding cross-section. The obtained value is shown in Figure 4 . By taking x values from 1 to a, the porosity distribution in the x-direction can be obtained. Similarly, the porosity distributions of the porous medium in the y-direction (x-z plane) and z-direction (x-y plane) can be obtained.

[0092] In some embodiments, obtaining the solid distribution information based on the three-dimensional morphology of the porous medium in step S12 includes:

[0093] Step S124: Remove the noise on the cross-section of the three-dimensional morphology of the porous medium based on the noise condition.

[0094] Step S125: Based on the solid pixel distribution on the cross-section, obtain the solid distribution information of the porous medium.

[0095] Specifically, as Figure 5As shown, the noise on the cross-section of the three-dimensional morphology of the carbon paper and carbon felt can include areas that do not conform to the cross-sectional area size of real fibers, fiber stacking areas, and fiber inclination areas. The carbon paper and carbon felt area is used for screening, and areas that significantly do not conform to the cross-sectional area size of real fibers are screened out. For example, areas with an area less than 20 and greater than 500 can be determined as noise that significantly does not conform to the cross-sectional area of real fibers and removed. The influence of noise, fiber stacking, and fiber inclination can also be filtered out using the aspect ratio of the area. For example, the aspect ratio range of the fiber is set to [r min , r max , r min = 0.8, r max = 1.2. Fibers with an aspect ratio range exceeding this range can be determined as noise and removed. In this embodiment, the regionprops function in MATLAB can be used.

[0096] Specifically, based on the solid pixel distribution on the cross-section, including the number of pixels occupied by the fiber cross-section or the number of pixels occupied by the fiber diameter, the fiber diameter is determined. In this embodiment, the side length of each pixel can be correspondingly set to 0.9 microns.

[0097] In this embodiment, the vast majority of the obtained carbon fiber diameter distributions are between 5 microns and 10 microns, and the extreme value appears at 7 microns. The porosity in the y-z cross-section is relatively stable, while the porosity in the x-y and x-z cross-sections fluctuates greatly within 0.65 to 0.95, and the fluctuation amplitude in the x-y cross-section is larger. The average porosity (the ratio of the number of 1-pixel in the entire three-dimensional matrix to the total number of pixels) is 0.76.

[0098] In some embodiments, step S13 obtains the computational domain of the porous medium based on the pore distribution and solid distribution information, including:

[0099] Step S131, obtaining the initial boundary of sphere growth.

[0100] Specifically, the initial boundary of sphere growth is the solid and physical boundary of the carbon paper and carbon felt. Specifically, it refers to the six outer surfaces of the cuboid carbon paper and carbon felt.

[0101] Step S132, based on the pore distribution and solid distribution information, obtaining the distance assignment of each pixel point within the initial boundary of sphere growth; the distance assignment is the distance value between the pixel point and the pore closest to it.

[0102] Specifically, the Euclidean distance transform is calculated, and a value is assigned to each pixel point, and this value is equal to the distance of the pixel to the nearest non-zero pixel:

[0103] w(i) = min y∈Ω ||x(i) - x(`i)||

[0104] Among them, x(i) represents the position of any pixel i in the image, x(`i) is the position of another non-i pixel in the image, and Ω is the domain of the image.

[0105] Step S133: Based on the distance assignment of each pixel point within the initial boundary of sphere growth, obtain the centroid and radius of the largest sphere; the information of the computational domain includes the centroid and radius information of the largest sphere.

[0106] Specifically, calculate the centroid x of the largest sphere i (the coordinates of the pixel point corresponding to the maximum value in the three-dimensional numerical matrix obtained by Euclidean distance transformation) and the radius w i (weight value, that is, the value assigned to this pixel point). The centroid and weight value of the pores within the computational domain of the carbon paper carbon felt obtained by the sphere growth model are as Figure 6 shown.

[0107] Step S134: Based on all the pixel points occupied by the largest sphere, obtain a new sphere growth boundary until the radius of the largest sphere reaches the set value.

[0108] Specifically, add all the pixel points occupied by this largest sphere as the new sphere growth boundary. Repeat steps S132 to S134 until the sphere radius reaches the set value. For example, it is considered to reach the set value when the sphere radius is less than the average fiber radius in the solid distribution information obtained from the three-dimensional morphology of the porous medium. Specifically, the average fiber radius in the two-dimensional graph measured by X-ray microtomography technology can be used as the judgment criterion.

[0109] In this embodiment, the sphere growth model is used to calculate the computational domain of the porous medium. In other embodiments, algorithms such as the watershed algorithm and the medial axis transformation can also be used to calculate the computational domain of the porous medium.

[0110] The Voronoi space segmentation based on the computational domain in step S14 includes:

[0111] Step S141: Based on the preset number of segments, perform Voronoi space segmentation on the computational domain to obtain cell information; the space segmentation information includes cell information.

[0112] Step S142: Based on the cell information, obtain the overall porosity of the porous medium.

[0113] Step S143: Based on the pore distribution and solid distribution of the porous medium, obtain the detected overall porosity of the porous medium.

[0114] Step S144: Optimize the Voronoi space segmentation based on the comparison result of the calculated overall porosity and the detected overall porosity to update the cell information.

[0115] Specifically, the root Voronoi space division of the carbon paper carbon felt calculation domain is established, and each space of the root Voronoi division can be expressed as:

[0116]

[0117] where the weighted space point (x i , w i ) is extracted from the reconstructed three-dimensional space matrix using the sphere growth model. This formula indicates that the weighted distance from the space point x to the space point x i is less than the weighted distance to any other point x j . Then, the region composed of the space points x is determined as cell i (actually a polyhedron).

[0118] In step S141, the number of spheres N p , that is, the number of cells, is set, and the root Voronoi space division is calculated. The information of all cells can be stored in a cell array, including the volume V i of the cell, the coordinates of all vertices, the lengths of the edges and the two connected vertices, the directions of the polygons surrounding the cell, and the labels of adjacent cells, etc.

[0119] Exemplarily, this embodiment provides an example of a vfn cell array. A blank cell array vfn is established, and the size of vfn is 3N p , where N p is the number of cells. The first column of the i-th row of vfn contains the coordinate information of the vertices of the i-th cell. For example, the first cell polyhedron contains 26 vertices. The second column of the i-th row of vfn contains the face information of the i-th cell (the three columns are the vertex indices of the enclosing face, the area, and the normal vector of the face). For example, the first cell is composed of 15 faces. The first face is enclosed by four vertices 2, 24, 23, and 4 (the vertices are arranged in the connected order. The first edge connects vertices 24 and 2, the second edge connects vertices 24 and 23, the third edge connects vertices 23 and 4, and the fourth edge connects vertices 4 and 2), the area is 65.65, and the direction is [0.651 - 0.75]. The third column of the i-th row of vfn contains the information of the adjacent cells of the i-th cell. For example, the first cell is adjacent to 15 cells such as 750, 1022, and 18.

[0120] In step S142, each vertex is assigned a label (ID), and each vertex has one and only one ID. The vertex is a fiber node (i.e., the node of the solid network). Based on the vertex ID and the fiber nodes connected by all the edges (fibers) of the polygons, the connection relationships between all fibers are obtained.

[0121] Then, through the cell array, obtain the side length L of the k-th side of the j-th polygon of the i-th cell ijk is the fiber length, and the random cylindrical fiber radius r ijk , calculate the fiber volume as:

[0122]

[0123] Preferably, the randomly set fiber radius follows the radius distribution of the fibers obtained from the three-dimensional topography of the porous medium.

[0124] Then, calculate the total fiber volume ∑(k ijk V ijk )(assuming the fiber is a cylinder and considering the boundary effect). Preferably, correct the solid volume according to the reciprocal k ijk of the number of cells to which the fiber belongs to avoid double counting.

[0125] In other embodiments, the total fiber volume can be ∑(V ijk ) by assigning a label (ID) to each side of the polygon, and each side has and only has the same label.

[0126] Then, calculate the overall porosity of the carbon paper and carbon felt based on the total fiber volume. The calculated overall porosity is the overall porosity calculated based on the space segmentation information. In step S143, the detected overall porosity of the porous medium is obtained based on the pore distribution and solid distribution information of the porous medium. That is, the detected overall porosity is the overall porosity calculated based on the data detected by two-dimensional scanning or three-dimensional scanning. Compare these two overall porosities. If they are inconsistent, repeat steps S141 to S143 until the comparison result shows that the calculated overall porosity and the detected overall porosity are consistent, so as to optimize the Voronoi space segmentation to update the cell information.

[0127] As Figure 7 shown, when the number of pores increases from 100 to 800, the porosity of the network decreases from 0.94 to 0.78. To achieve the same porosity as the scanning result of the carbon paper and carbon felt, the ball growth model and the Voronoi space segmentation method take 900 pores.

[0128] In some embodiments, the local connectivity information of the porous medium obtained based on the space segmentation information in step S14 includes:

[0129] Step S145, obtain the area of each polygon corresponding to the cells in the cell information.

[0130] Step S146, based on the cell information, obtain the weighted radius of the side length of the solid corresponding to the side of the polygon.

[0131] Step S147: Obtain the length of the corresponding throat based on the side length weighted radius of the polygon corresponding to the side length of the solid.

[0132] Step S148: Obtain the extrusion volume of each polygon based on the area of the polygon corresponding to each cell in the cell information and the length of the corresponding throat.

[0133] Step S149: Obtain the volume and equivalent radius of the throat, and the volume and equivalent radius of the pore based on the extrusion volume of each polygon and the length of the corresponding throat.

[0134] Step S150: Obtain the connection relationship between the pores and the throats based on the label information of each cell and its adjacent cells in the cell information.

[0135] Specifically, in this embodiment, the position and size information of the pore throats are obtained based on each face of the polyhedron obtained by Voronoi space division and the fiber information on the face.

[0136] Extract the area A of the j-th polygon of the i-th pore in step S145 ij (which can be directly obtained from the cell array), and calculate the side length weighted radius r of the solid corresponding to the side of the polygon in step S146 wm,ij :

[0137] r wm,ij =(∑(r ijk 2 L ijk ) / ∑L ijk ) 1 / 2

[0138] Obtain the corresponding throat length L in step S147 ij =2r wm,ij .

[0139] Calculate the extrusion volume V of the j-th polygon of the i-th pore in step S148 f,ij (A ij L ij ), and calculate the corresponding throat volume V t,ij and the equivalent radius r of the throat t,ij respectively as:

[0140] V t,ij =V f,ij -∑k ijk V ijk

[0141]

[0142] Preferably, as Figure 9 shown, k ijk is the reciprocal of the number of repetitions of the solid throat (i.e., the number of connected cells).

[0143] In step S149, calculate the volume V of the i-th pore p,i and the equivalent pore radius r t,ij which are respectively as follows:

[0144] V p,i = V i - ∑0.5V f,ij

[0145]

[0146] As Figure 10 shown, the pore radius distribution obtained by the sphere growth model and the root Voronoi space partitioning method ranges from 15 to 45 microns, the vast majority of which are distributed from 15 to 35 microns, and the peak of the pore radius distribution is near 23 microns. The throat radius distribution ranges from 0 to 40 microns, and the radius within 25 microns covers more than 90% of the throat quantity.

[0147] In step S150, based on the labels of the adjacent cells of all cells in the cell array vfn, determine all the faces on the polyhedron and the information of the polyhedrons connected by all the faces within the global definition, so as to obtain the connection relationship between the pores and the throats.

[0148] In some embodiments, a method for obtaining the microstructure parameters of a porous material includes: obtaining a two-dimensional image of a porous medium based on X-ray microtomography technology, and performing three-dimensional reconstruction on the two-dimensional image to obtain the three-dimensional morphology of the porous medium. Based on the three-dimensional morphology of the porous medium, obtain its pore distribution and solid distribution information; based on the pore distribution and solid distribution information, use the sphere growth model to obtain the computational domain of the porous medium. Perform root Voronoi space partitioning based on the computational domain, and obtain the local connectivity information of the porous medium based on the space partitioning information; the local connectivity information includes the position and size of the throats and the connection relationship between the pores and the throats. In this embodiment, it is creatively proposed to combine X-ray microtomography technology, the sphere growth model and root Voronoi space partitioning to extract more real pore structure information of the porous medium, and at the same time, the connection relationship between the solid structure and the solid network can be extracted, so as to obtain the transmission phenomenon of electrons and the like in the solid network.

[0149] In order to compare with the pore structure constructed by the random distribution method, a pore network obtained by combining the pore random distribution method and root Voronoi space partitioning is also constructed here. As Figure 8 shown, when the number of pores increases from 100 to 800, the porosity of this network drops from 0.94 to 0.76. In order to achieve the same porosity as the scanning result of carbon paper and carbon felt, the random distribution method and root Voronoi space partitioning take 900 pores. As Figure 11As shown, the pore radius distribution of the network constructed by the random distribution method and the Voronoi space partition ranges from 5 to 40 microns, with a concentrated distribution from 15 to 35 microns, and the peak of the pore radius distribution is near 25 microns; the throat radius distribution ranges from 0 to 40 microns, among which, those with a radius within 25 microns also cover more than 90% of the throat numbers.

[0150] To more vividly illustrate the beneficial effects of the pore network (sphere growth model and Voronoi space partition method) constructed by the present invention on analyzing the material transport process in carbon paper and carbon felt, taking the oxygen transport in the cathode gas diffusion layer of a high-temperature proton exchange membrane fuel cell as an example, the effectiveness of the pore network constructed by the present invention was first verified, and then the effective gas diffusion coefficients of oxygen in the pore network constructed by the present invention, the regular network, and the network constructed by the random distribution method under different unilateral boundary liquid phase coverage rates were analyzed (as Figure 12 shown). Among them, liquid phase intrusion is due to the loss of phosphoric acid in the high-temperature proton exchange membrane fuel cell and intrudes into the gas diffusion layer due to capillary force. The results show that the results of the pore network constructed by the present invention are between the experimental results of TGP-060 and TGP-120 carbon papers, which emphasizes the effectiveness of the model because it is consistent with the uniformly microstructured carbon papers of the same series generally accepted in the literature. In addition, when S < 0.4, the pore network constructed by the present invention exhibits significant anisotropy. In addition, the networks constructed by the regular network and the random distribution method both underestimate the effective gas diffusion coefficient of oxygen, indicating that the networks constructed by traditional methods cannot effectively analyze the material transport process in carbon paper and carbon felt.

[0151] A method for obtaining the microstructure parameters of a porous material provided by an embodiment of the present invention can obtain the pore distribution and solid distribution information in the microstructure of the porous material, shows more real porous medium microstructure characteristics compared with traditional methods, and is of great significance for understanding heat and mass transfer inside the porous medium (such as the transport of substances and charges in the gas diffusion layer of a proton exchange membrane fuel cell). It can also obtain the local connectivity information of the porous medium, that is, extract the connection relationship between the solid structure and the solid network, so as to obtain the transport phenomenon of electrons and the like in the solid network.

[0152] Further, the present application also provides an apparatus for obtaining the microstructure parameters of a porous material, including: an acquisition module for acquiring the three-dimensional morphology of a porous medium; a first calculation module for obtaining the pore distribution and solid distribution information based on the three-dimensional morphology of the porous medium; a second calculation module for obtaining the computational domain of the porous medium based on the pore distribution and solid distribution information; and a third calculation module for performing Voronoi space segmentation based on the computational domain and obtaining the local connectivity information of the porous medium based on the space segmentation information. The local connectivity information includes the positions and sizes of the throats and the connection relationships between the pores and the throats. The method for obtaining the microstructure parameters of the porous material implemented by each module in the apparatus for obtaining the microstructure parameters of the porous material may adopt the implementation method in any of the above embodiments, which will not be elaborated herein.

[0153] Further, the present application also provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the method in any of the above embodiments are implemented.

[0154] Further, the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method in any of the above embodiments are implemented.

[0155] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some or all of the technical features. However, such modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for obtaining microstructure parameters of porous materials, characterized in that: include: Obtain the three-dimensional morphology of porous media; Based on the three-dimensional morphology of the porous medium, obtaining its pore distribution and solid distribution information; Based on the pore distribution and the solid distribution information, the calculation domain of the porous medium is calculated using a spherical growth model; including: obtaining an initial spherical growth boundary; obtaining a distance assignment for each pixel point within the initial spherical growth boundary based on the pore distribution and the solid distribution information; the distance assignment is the distance value between the pixel point and the nearest pore; obtaining the center of mass and radius of the largest sphere based on the distance assignment for each pixel point within the initial spherical growth boundary; the information of the calculation domain includes the center of mass and radius information of the largest sphere; obtaining a new spherical growth boundary based on all pixel points occupied by the largest sphere until the radius of the largest sphere reaches a set value; A root Voronoi space segmentation is performed based on the computational domain, and local connectivity information of the porous medium is obtained based on the space segmentation information; the local connectivity information includes the position and size of the throat and the connection relationship between the pore and the throat; wherein each space of the root Voronoi segmentation is represented as: Among them, the weighted spatial point (xi, wi) is extracted from the reconstructed three-dimensional space matrix using the ball growth model. The formula indicates that if the weighted distance from spatial point x to spatial point xi is less than the weighted distance to any other point xj, then the region composed of spatial point x is determined to be a cell. i , cell i It is a polyhedron.

2. The method for obtaining microstructure parameters of porous materials according to claim 1, characterized in that: The obtaining of the three-dimensional morphology of the porous medium comprises: performing three-dimensional scanning on the porous medium to obtain its three-dimensional morphology; or Performing a two-dimensional scan on the cross section of the porous medium along a preset direction to obtain a plurality of two-dimensional graphs; and A three-dimensional reconstruction is performed based on the multiple two-dimensional images to obtain the three-dimensional morphology of the porous medium.

3. The method for obtaining microstructure parameters of porous materials according to claim 2, characterized in that: The three-dimensional reconstruction based on the multiple two-dimensional graphics to obtain the three-dimensional morphology of the porous medium includes: Performing graphic preprocessing on the two-dimensional graphic, wherein the graphic preprocessing includes adjusting the two-dimensional graphic to an optimal angle and removing a background area; Distinguishing between solid areas and pore areas in the two-dimensional graph; The two-dimensional graphics after each division process are superimposed to form the three-dimensional morphology of the porous medium.

4. The method for obtaining microstructure parameters of porous materials according to claim 1, characterized in that: The pore distribution information of the porous medium is obtained based on the three-dimensional morphology thereof, including: Based on the three-dimensional morphology of the porous medium, the size of the three-dimensional matrix is ​​obtained, and based on the size of the three-dimensional matrix, each cross-sectional area of ​​the porous medium is obtained, and based on the cross-sectional area, the number of pixels on the cross-sectional area is obtained; Obtaining the number of pore pixels in each cross section of the porous medium along a direction, and taking the ratio of the number of pore pixels on a cross section to the number of pixels on the cross section as the porosity of the cross section; Based on the porosity of the corresponding cross-section of the porous medium along each direction, the porosity distribution in each direction is obtained.

5. The method for obtaining microstructure parameters of porous materials according to claim 1, characterized in that: The solid distribution information of the porous medium is obtained based on the three-dimensional morphology thereof, including: removing noise on a cross section of the three-dimensional morphology of the porous medium based on a noise condition; Based on the solid pixel distribution on the cross section, solid distribution information of the porous medium is obtained.

6. The method for obtaining microstructure parameters of porous materials according to claim 1, characterized in that: The root Voronoi space segmentation based on the computational domain comprises: Performing root Voronoi space segmentation on the computational domain based on a preset number of segmentations to obtain cell information; the space segmentation information includes the cell information; Based on the cell information, obtaining a calculated overall porosity of the porous medium; Based on the pore distribution and the solid distribution information, the overall porosity of the porous medium is obtained; The root Voronoi space segmentation is optimized based on the comparison result of the calculated overall porosity and the detected overall porosity to update the cell information.

7. The method for obtaining microstructure parameters of porous materials according to claim 6, characterized in that: The obtaining of the local connectivity information of the porous medium based on the spatial segmentation information includes: Obtaining the area of ​​the polygon corresponding to each cell in the cell information; Based on the cell information, a weighted radius of the side length of the solid corresponding to the side of the polygon is obtained; The length of the corresponding throat is obtained based on the weighted radius of the side length of the solid corresponding to the side of the polygon; Based on the area of ​​the polygon corresponding to each cell in the cell information and the length of the corresponding throat, obtaining the extrusion volume of each polygon; Based on the extrusion volume of each polygon and the length of the corresponding throat, the volume and equivalent radius of the throat, and the volume and equivalent radius of the hole are obtained; and Based on the label information of each cell and the adjacent cells in the cell information, the connection relationship between the hole and the throat is obtained.

8. A device for acquiring microstructure parameters of porous materials, characterized in that: The device comprises: An acquisition module, used for acquiring the three-dimensional morphology of the porous medium; A first calculation module is used to obtain pore distribution and solid distribution information of the porous medium based on the three-dimensional morphology of the porous medium; A second calculation module is used to calculate the calculation domain of the porous medium using a spherical growth model based on the pore distribution and the solid distribution information; The third calculation module is used to perform root Voronoi space segmentation based on the calculation domain, and obtain local connectivity information of the porous medium based on the space segmentation information; the local connectivity information includes the position and size of the throat and the connection relationship between the hole and the throat; wherein each space of the root Voronoi segmentation is represented as: Among them, the weighted spatial point (xi, wi) is extracted from the reconstructed three-dimensional space matrix using the ball growth model. The formula indicates that if the weighted distance from spatial point x to spatial point xi is less than the weighted distance to any other point xj, then the region composed of spatial point x is determined to be a cell. i , cell i It is a polyhedron.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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