Method, device and equipment for constructing geometric model of porous medium and medium

Abstract

The invention provides a porous medium geometric model construction method, device and equipment and a medium. The method comprises the following steps: uniformly and randomly distributing seeds in a calculation space; according to the Voronoi polygon theory, the calculation space is divided into a limited number of polygons; a merging diameter is set, polygon vertexes smaller than the merging diameter range are merged, and the connection probability of adjacent unit cells is set to manufacture a negative curvature; generating a communication channel according to a given width on the basis of the polygon; and negative curvature manufacturing and smoothing processing are carried out on the communication channel, and a porous medium geometric model is obtained. The method is used for generating a porous medium geometric model composed of large-scale multi-diameter communicating channels, it is guaranteed that the porous medium geometric model has a topological network with good connectivity and randomness, and the diameters of the multiple channels and the proportions of the multiple channels can be specified.

Description

Technical Field

[0001] The invention belongs to the field of porous medium construction, and relates to a porous medium geometric model construction method, device, equipment and medium. Background Art

[0002] Porous media are composed of a solid particle skeleton and pores, and the pores can allow fluids such as liquid or gaseous substances to flow. Paper, fiber, soil, concrete, biological tissues, etc. in daily life are all common porous media, and the study of the internal structure of porous media is also a focus of attention in various fields. In the field of catalytic hydrogenation, the reconstruction of the internal pore structure of catalyst particles is the basis for conducting three-transmission and one-reverse research in catalytic hydrogenation reactors. The pore structure and pore channel morphology of porous media have an important influence on multiphase mixing, component migration and reaction processes, so reconstruction and porous media modeling inside catalyst particles are very critical.

[0003] At present, although conventional physical imaging methods can restore the porous media characteristics of catalyst particles, they are costly and difficult to operate, and can only obtain models of smaller sizes. The commonly used pore structure models for numerical method reconstruction are divided into three types: pore structure reconstruction model, pore network model and equivalent pore network model. The pore reconstruction model reconstructs the pore structure inside the real porous medium and directly solves the transfer and reaction control equations; the pore network model distinguishes the pores and pore throat units in the pore structure based on the pore reconstruction model; the equivalent pore network model further arranges the pores on a regular grid grid on the basis of the pore network model, and establishes a simplified equivalent model based on the statistical parameters of the pore characteristics of the porous medium. The reconstruction model has too many simplifications and assumptions. The porous media model particles generated by the existing numerical methods are less random and arranged regularly, and the morphological idealization is not conducive to reflecting the complex pore channel characteristics.

[0004] Commonly used pore generation methods include the four-parameter method and Gaussian random noise function, but these methods cannot specify the channel diameter. The pore channels of real catalyst particles do not have a single diameter, so it is a challenge to construct a random porous media geometry model with specified diameter connecting channels. Summary of the invention

[0005] In order to solve the technical problems existing in the prior art, the present invention provides a method, device, equipment and medium for constructing a porous medium geometric model, which is used to realize the generation of a porous medium geometric model composed of large-scale connected channels of various diameters, which not only ensures a topological network with good connectivity and randomness, but also can specify multiple channel diameters and their proportions.

[0006] In order to achieve the above technical effects, the present invention adopts the following technical solutions:

[0007] One of the purposes of the present invention is to provide a method for constructing a porous medium geometric model, the method comprising:

[0008] Distribute the seeds evenly and randomly in the computational space;

[0009] According to the Voronoi polygon theory, the computational space is divided into a finite number of polygons;

[0010] Set the merge diameter to merge polygon vertices that are smaller than the merge diameter.

[0011] Generate connected channels with given width based on polygons;

[0012] The connected channels are subjected to negative curvature manufacturing and smoothing to obtain a porous media geometric model.

[0013] As a preferred technical solution of the present invention, the seed generation method includes a Halton sequence quasi-random method.

[0014] As a preferred technical solution of the present invention, the calculation space is set to N x ×N y Grid, seeds in N x ×N y The number of computational spaces is N, and the distribution density of seeds is

[0015] As a preferred technical solution of the present invention, the number of polygons is not less than the number of seeds.

[0016] As a preferred technical solution of the present invention, each merged vertex is connected to at least three other vertices.

[0017] As a preferred technical solution of the present invention, adjacent unit cells in the connecting channel are merged, and the merging probability is limited to perform negative curvature manufacturing.

[0018] As a preferred technical solution of the present invention, the smoothing process is to perform Bezier spline smoothing method according to the set smoothing intensity.

[0019] A second object of the present invention is to provide a device for constructing a porous medium geometric model, the device comprising:

[0020] The first building block is used to evenly and randomly distribute seeds in the computational space;

[0021] The second building module is used to divide the calculation space into a finite number of polygons according to the Voronoi polygon theory;

[0022] The third construction module is used to set a merging diameter and merge polygon vertices that are smaller than the merging diameter.

[0023] A fourth building module is used to generate a connected channel according to a given width based on the polygon;

[0024] An optimization module for making negative curvature and smoothing the connecting channel;

[0025] The output module is used to output the obtained porous media geometric model.

[0026] A third object of the present invention is to provide an electronic device, the electronic device comprising:

[0027] at least one processor; and

[0028] a memory communicatively connected to at least one processor; wherein,

[0029] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to implement a porous medium geometric model building method provided in one of the objectives.

[0030] A fourth object of the present invention is to provide a computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable a processor to implement the porous medium geometric model construction method provided in one of the objects when executed.

[0031] Compared with the prior art, the present invention has at least the following beneficial effects:

[0032] The present invention provides a method, device, equipment and medium for constructing a porous medium geometric model, which are used to realize the generation of a porous medium geometric model composed of large-scale connected channels of various diameters, which not only ensures a topological network with good connectivity and randomness, but also can specify various channel diameters and their proportions. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A distribution diagram of randomly generated seeds in a computing space in a specific embodiment of the present invention;

[0034] Figure 2 To generate a Voronoi polygon diagram by dividing the space based on the Voronoi polygon theory in a specific implementation manner of the present invention;

[0035] Figure 3 A schematic diagram of vertex merging in a specific implementation manner of the present invention;

[0036] Figure 4 A connected channel diagram generated according to a given width in a specific implementation manner of the present invention;

[0037] Figure 5 It is a schematic diagram of the principle of merging unit cells to produce negative curvature in a specific embodiment of the present invention;

[0038] Figure 6 It is a schematic diagram of the principle of photochemical treatment in a specific embodiment of the present invention;

[0039] Figure 7 A schematic flow chart of a method for constructing a porous medium geometric model provided in Example 1 of the present invention;

[0040] Figure 8a and b are schematic diagrams of uniform distribution and random distribution of seeds in the calculation space in step (1) of the method for constructing a porous medium geometric model provided in Example 1 of the present invention;

[0041] Figure 9a -c is a connected channel diagram (a:d) generated according to a given width in step (4) of the porous medium geometric model construction method provided in Example 1 of the present invention p,m =5, b:d p,m =10, c:d p,m =15);

[0042] Fig.10a and b are the connected channel diagrams after the adjacent unit cells are merged in step (5) of the porous medium geometric model construction method provided in Example 1 of the present invention (a:P -cur =0.1, b:P -cur =0.5);

[0043] Fig.11a and b are the porous medium geometric model diagrams after smoothing in step (6) of the porous medium geometric model construction method provided in Example 1 of the present invention (a:k B =0.6, b:k B =1.0);

[0044] Fig.12 A diagram of the connected channels of the porous medium geometric model provided in Example 2;

[0045] Fig.13a A diagram of the connected channels of the porous medium geometric model provided in Example 3;

[0046] Fig.13b A diagram of the connected channels of the porous medium geometric model provided in Example 4;

[0047] Fig.14a A diagram of the connected channels of the porous medium geometric model provided in Example 5;

[0048] Fig.14b A diagram of the connected channels of the porous medium geometric model provided in Example 6;

[0049] Fig.15 This is a schematic diagram of the structure of an electronic device for the method for constructing a porous medium geometric model provided in Example 8.

[0050] The present invention is further described in detail below. However, the following examples are only simplified examples of the present invention and do not represent or limit the scope of protection of the present invention. The scope of protection of the present invention shall be subject to the claims. DETAILED DESCRIPTION

[0051] The technical solution of the present application is further described below through specific implementation methods.

[0052] A specific embodiment of the present invention provides a method for constructing a porous medium geometric model, the method comprising:

[0053] Distribute the seeds evenly and randomly in the computational space;

[0054] According to the Voronoi polygon theory, the computational space is divided into a finite number of polygons;

[0055] Set the merge diameter to merge polygon vertices that are smaller than the merge diameter.

[0056] Generate connected channels based on polygons according to given diameters;

[0057] The connected channels are subjected to negative curvature manufacturing and smoothing to obtain a porous media geometric model.

[0058] In one specific embodiment of the present invention, the seeds are uniformly and randomly distributed in the computational space using the Halton sequence quasi-random method. For example, Figure 1 As shown, N s =50 seeds are randomly distributed in the computational space (400×400, unit μm).

[0059] In a specific implementation of the present invention, the calculation space is N x ×N y When the grid is x ×N y The value of and the value of the seed N can be selected according to the needs of constructing the porous medium geometric model and are not specifically limited here.

[0060] In a specific embodiment of the present invention, the Voronoi polygon theory refers to Thiessen polygons, which are a set of continuous polygons composed of perpendicular bisectors connecting two adjacent points (seeds). Any position in a Thiessen polygon is closest to the sample point (seed) of the polygon, far away from the sample point in the adjacent polygon, and each polygon contains and only contains one sample point. As an example, the Voronoi polygon constructed in the computational space (400×400, unit μm) is as follows: Figure 2 As shown,

[0061] In one embodiment of the present invention, the combined diameter d cluster The choice of can be made according to the distribution of Voronoi polygons in the calculation space, and no further restrictions are made here. cluster For example, it can be 0 μm, 5 μm or 10 μm, etc. As an example, the combined diameter d is set to cluster = 10 μm, the vertices that can be merged are as follows Figure 3 shown.

[0062] In one specific embodiment of the present invention, given width d p,m It can be selected according to the needs of constructing the porous media geometric model, such as 5μm, 10μm and 15μm. p,m , such as d p,1 , d p,2 , ..., d p,M , you can set different proportions, such as r p,1 , r p,2 ,……,r p,M , control the proportion of each diameter, where Generate a porous media geometry model consisting of interconnected channels of different diameters according to a given ratio. For example, the top width d is set p,m = 10 μm, the generated connecting channels are as follows Figure 4 shown.

[0063] In a specific embodiment of the present invention, before merging adjacent cells, it is determined whether a negative volume cell exists. If so, the negative volume cell is eliminated first. The negative volume cell can be eliminated by merging the surrounding vertices in the negative volume cell to form a positive volume cell, such as Figure 3 .

[0064] In a specific embodiment of the present invention, since the solid unit cells in the generated connecting channel are all circular in shape, there is no negative curvature, and the randomness is poor, a method of merging adjacent unit cells is proposed to produce negative curvature. By controlling the merging probability P -cur The proportion of the zigzag boundary is controlled to improve the randomness of the pore structure. The principle diagram is as follows Figure 5shown.

[0065] In a specific embodiment of the present invention, the method for merging adjacent unit cells may be to set a circle based on the vertices and merge the vertices within the set range.

[0066] In a specific embodiment of the present invention, the connected channels are smoothed by using a Bezier spline smoothing method, and the smoothing strength k is controlled. B , to effectively control the breadth of the pore size distribution. As an example, k B = 0.5 and 1. The results after smoothing are as follows Figure 6 shown.

[0067] In a specific implementation of the present invention, the smoothing method is not limited to the Bezier spline smoothing method, and a suitable interpolation method can be selected according to the calculation requirements, which is not further limited here.

[0068] In a specific implementation of the present invention, a path-finding method is used to determine discrete fluid points after smoothing.

[0069] In a specific implementation of the present invention, before outputting the porous medium geometric model, it is determined whether there is a boundary crossing. If there is a boundary crossing phenomenon, the intersection area is eliminated by using an expansion and corrosion algorithm.

[0070] To better illustrate the present invention and facilitate understanding of the technical solution of the present invention, typical but non-limiting embodiments of the present invention are as follows:

[0071] Example 1

[0072] This embodiment provides a method for constructing a porous medium geometric model, and its structure is as follows: Figure 7 As shown, the method includes:

[0073] (1) Using the Halton sequence quasi-random method, 100 seeds with uniform and Gaussian random distributions are generated in a 400×400 computing space;

[0074] (2) According to the Voronoi polygon theory, the calculation space is divided into a finite number of polygons, as shown in FIG8 ;

[0075] (3) Set the combined diameter d cluster =10, will be smaller than the combined diameter d cluster The polygon vertices within the range are merged;

[0076] (4) Set the given width d p,m = 5, 10 and 15, generate connected channels according to the given width, such as Figure 9a -c as shown;

[0077] (5) Set the merging probability P-cur = 0.1 and 0.5, for the connecting channel (d p,m = 10) are merged to create negative curvature, and the result is Fig.10a and 10b As shown;

[0078] (6) Set the smoothing strength k B = 0.6 and 1.0, and the connected channels (d p,m =10,P -cur = 0.5) for photochemical treatment, and the results are as follows Fig.11a and 11b shown.

[0079] Example 2

[0080] In this embodiment, steps (1) and (2) are the same as those in the embodiment, and step (3) is cluster = 0, that is, no vertex merging is performed, and step (4) sets the given width d p,m = 10, a connecting channel is generated according to the given width, such as Fig.12 shown.

[0081] Example 3

[0082] In this embodiment, steps (1) to (3) are the same as those in the embodiment, and step (4) sets a given width d p,m =5 and 20, accounting for r p,1 = 0.5 and r p,2 = 0.5, a connecting channel with two different diameters is generated according to the given width and proportion, such as Fig.13a shown.

[0083] Example 4

[0084] In this embodiment, steps (1) to (3) are the same as those in the embodiment, and step (4) sets a given width d p,m =10 and 20, accounting for r p,1 = 0.5 and r p,2 = 0.5, a connecting channel with two different diameters is generated according to the given width and proportion, such as Fig.13b shown.

[0085] Example 5

[0086] In this embodiment, steps (1) to (3) are the same as those in the embodiment, and step (4) sets a given width d p,m =5 and 20, accounting for r p,1 = 0.8 and r p,2 = 0.2, a connecting channel with two different diameters is generated according to the given width and proportion, such as Fig.14a shown.

[0087] Example 6

[0088] In this embodiment, steps (1) to (3) are the same as those in the embodiment, and step (4) sets a given width d p,m =5 and 20, accounting for r p,1 = 0.3 and r p,2 = 0.7, a connecting channel with two different diameters is generated according to the given width and proportion, such as Fig.14b shown.

[0089] It can be seen from Examples 1-6 that the present invention can randomly generate porous media geometric models with a single diameter, two diameters and their different proportions, different smoothness strengths, and different unit cell curvatures. Of course, by saving data such as seed positions, channel diameters and their proportions, and smoothness strengths, it is also possible to realize the construction of porous media geometric models randomly generated in different links or inheriting the characteristics of a certain link.

[0090] Example 7

[0091] This embodiment provides a porous medium geometric model construction device, the device comprising:

[0092] The first building block is used to evenly and randomly distribute seeds in the computational space;

[0093] A second building module is used to divide the calculation space into a finite number of polygons according to the Voronoi polygon theory;

[0094] A third construction module is used to set a merging diameter and merge polygon vertices that are smaller than the merging diameter.

[0095] A fourth construction module is used to generate a connecting channel according to a given width based on the polygon;

[0096] An optimization module, used for performing negative curvature manufacturing and smoothing on the communication channel;

[0097] The output module is used to output the obtained porous media geometric model.

[0098] The device provided in this embodiment can execute the porous medium geometric model construction method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0099] Example 8

[0100] This embodiment provides an electronic device for a method for constructing a porous medium geometric model, such as Figure 4As shown, the electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or required herein.

[0101] like Fig.15 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0102] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a second storage area, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0103] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the generator set pipeline optimization method.

[0104] In some embodiments, the generator set pipeline optimization method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the generator set pipeline optimization method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to execute the generator set pipeline optimization method in any other suitable manner (for example, by means of firmware).

[0105] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0106] Computer programs for implementing the methods of the present application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable target determination device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0107] In the context of the present application, a computer readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device or equipment. A computer readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer readable storage medium may be a machine readable signal medium. A more specific example of a machine readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0108] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0109] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0110] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0111] The applicant declares that the present invention illustrates the detailed structural features of the present invention through the above-mentioned embodiments, but the present invention is not limited to the above-mentioned detailed structural features, that is, it does not mean that the present invention must rely on the above-mentioned detailed structural features to be implemented. Those skilled in the art should understand that any improvement of the present invention, equivalent replacement of the components selected by the present invention, addition of auxiliary components, selection of specific methods, etc., all fall within the protection scope and disclosure scope of the present invention.

[0112] The preferred embodiments of the present invention are described in detail above. However, the present invention is not limited to the specific details in the above embodiments. Within the technical concept of the present invention, a variety of simple modifications can be made to the technical solution of the present invention, and these simple modifications all belong to the protection scope of the present invention.

[0113] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present invention will not further describe various possible combinations.

[0114] In addition, various embodiments of the present invention may be arbitrarily combined, and as long as they do not violate the concept of the present invention, they should also be regarded as the contents disclosed by the present invention.

Claims

1. A method for constructing a porous medium geometric model, characterized in that: The method comprises: Distribute the seeds evenly and randomly in the computational space; According to the Voronoi polygon theory, the calculation space is divided into a finite number of polygons; Set the merge diameter, and merge the polygon vertices that are smaller than the merge diameter range; generating a connecting channel according to a given width based on the polygon; The connecting channel is subjected to negative curvature manufacturing and smoothing processing to obtain the porous medium geometric model.

2. The method for constructing a porous medium geometric model according to claim 1, characterized in that: The seed generation method includes a Halton sequence quasi-random method.

3. The method for constructing a porous medium geometric model according to claim 1, characterized in that: Set the calculation space to N x ×N y grid, the seeds are in N x ×N y The number of computational spaces is N, and the distribution density of the seeds is 4. The method for constructing a porous medium geometric model according to claim 1, characterized in that: The number of the polygons is not less than the number of the seeds.

5. The method for constructing a porous medium geometric model according to claim 1, characterized in that: The merged vertices are all connected to at least three other vertices.

6. The method for constructing a porous medium geometric model according to claim 1, characterized in that: Adjacent unit cells in the connecting channel are merged, and the merging probability is limited to perform negative curvature manufacturing.

7. The method for constructing a porous medium geometric model according to claim 1, characterized in that: The smoothing process is to perform Bezier spline smoothing according to the set smoothing intensity.

8. A porous medium geometric model construction device, characterized in that: The device comprises: The first building block is used to evenly and randomly distribute seeds in the computational space; A second building module is used to divide the calculation space into a finite number of polygons according to the Voronoi polygon theory; A third construction module is used to set a merging diameter and merge polygon vertices that are smaller than the merging diameter. A fourth construction module is used to generate a connecting channel according to a given width based on the polygon; An optimization module, used for performing negative curvature manufacturing and smoothing on the communication channel; The output module is used to output the obtained porous media geometric model.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the porous medium geometric model construction method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to implement the porous medium geometric model construction method according to any one of claims 1 to 7 when executed by a processor.

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