Porous medium model generation method for micro-fluidic chip

Abstract

The invention relates to the technical field of microfluidics, and discloses a porous medium model generation method for a micro-fluidic chip, which comprises the following steps: firstly setting key parameters for generating a porous medium, then generating random irregular particles, filling particles in a target rectangular area, and finally processing, drawing and counting arranged polygons. The porosity, connectivity and average pore size of the porous medium model can be accurately regulated and controlled by setting the number of particles, particle size distribution, a drawing scale and an expansion coefficient on the basis of random polygon scaling, advancing and retreating approach and a falling arrangement algorithm, and meanwhile, the porosity, connectivity and average pore size of the porous medium model can be accurately regulated and controlled by simulating the deposition forming process of the porous medium. Polygon vertex coordinate expansion and random rotation preprocessing are utilized, a candidate arrangement position list and an overlapping detection mechanism are combined, a random irregular particle filling model is efficiently generated, and on the basis, a parameter-performance mapping relation is constructed to obtain a random irregular particle filling model. The method provided by the invention has the beneficial effects of quickly optimizing the model generation process and realizing model customization.

Description

Technical Field

[0001] The present invention relates to the field of microfluidic technology, and in particular to a method for generating a porous medium model for a microfluidic chip. Background Art

[0002] Porous media are ubiquitous in nature and society, affecting numerous fields such as energy, thermal power, and biology. The study of porous media is particularly crucial in the development of groundwater, oil, and gas resources. With the continuous development of industries like oil and gas, the demand for understanding the distribution and flow characteristics of subsurface fluids is increasing.

[0003] To further investigate the seepage patterns of fluids in porous media, creating microscale porous media models for use in seepage experiments is an effective and widely used method. Currently, common methods for creating microscopic porous media models include real rock core models, artificial filling models, and laser-etched glass models. Laser-etched glass models are widely used in microscopic seepage research due to their excellent visibility and ability to be fabricated directly in the laboratory.

[0004] However, before laser-etching glass models, porous media templates must be prepared. Traditionally, obtaining these templates requires extracting and scanning rock cores, a tedious and costly process. However, using computer technology to generate digital porous media templates effectively eliminates these steps, significantly reducing production costs and time, and greatly facilitating microscopic seepage research.

[0005] Porous media templates need to reflect the connectivity and anisotropy of real porous media. Currently, the commonly used methods for constructing digital two-dimensional porous media templates include circular particle filling, Voronoi diagram method, and random growth method. Circular particles are easy to generate, but their shape is too idealized and does not conform to the shape of real rock particles. The Voronoi diagram method can form particles of different shapes, but the throat size it generates is too uniform. The random growth method controls the basic characteristics of porous media, such as connectivity and porosity, by adjusting four parameters, but this method will produce single-point solids. Summary of the Invention

[0006] (1) Technical problems solved

[0007] In response to the shortcomings of the existing technology, the present invention provides a method for generating porous medium models for microfluidic chips, which has the advantages of high efficiency, convenience, low cost, high degree of visualization and precise control of model parameters. It solves the problem that the traditional production method of obtaining porous medium templates is cumbersome and costly, and it is difficult to accurately control the model characteristics.

[0008] (2) Technical solution

[0009] To achieve the above object, the present invention provides the following technical solution: a method for generating a porous medium model for a microfluidic chip, characterized in that it comprises the following steps:

[0010] Step 1: Set the key parameters for generating porous media, including the target rectangular area of ​​the porous media, the area of ​​the target rectangular area of ​​the porous media, the drawing scale, and the number of particles N to be generated. u and the particle size distribution range, and the unit of the drawing scale is: μm / unit coordinate, where μm represents the length measurement unit of the porous medium in reality, and the coordinate represents the length measurement unit in the computer program;

[0011] Step 2: Generate random irregular particles. There are N irregular particles. u The random polygons are recorded with vertex coordinates in the local coordinate system. The vertex coordinates are recorded in the counterclockwise direction as the positive direction of the random polygon, and each random polygon is randomly assigned a particle size value p. r , and the same particle size value is not reused;

[0012] Step 3: scaling multiple polygons with different particle size values ​​to obtain multiple scaled polygons with different particle size values;

[0013] Step 4: Fill the generated porous medium target rectangular area with multiple scaled polygons of different particle size values ​​to simulate the deposition formation process of the porous medium;

[0014] Step 5: Draw the filling results of multiple scaled polygons with different particle size values ​​in the target rectangular area of ​​the porous medium to obtain a random two-dimensional porous medium for simulating the anisotropy of the porous medium.

[0015] The target rectangular area of ​​the porous medium is: W×Hμm 2 , where: W is the rectangular width of the target rectangular area of ​​the porous medium, and H is the rectangular height of the target rectangular area of ​​the porous medium.

[0016] In step 1, N u The total area of ​​the particles is larger than the target rectangular area of ​​the porous medium.

[0017] The expression for scaling polygons with different particle size values ​​is:

[0018]

[0019] In the formula, P r Indicates that each polygon is randomly assigned a particle size value, C d represents the length of the major axis of each polygon; p cois the scaling factor; p sa is the scale;

[0020] Furthermore, multiple polygons with the same particle size value are scaled to form a polygon group that satisfies the particle size distribution.

[0021] The deposition formation process of the simulated porous medium in step 4 is specifically as follows:

[0022] S4.1. Preprocessing polygons with different particle size values;

[0023] S4.2. Arrange the pretreated polygons of different particle sizes at the bottom of the target rectangular area of ​​the porous medium to form a first row of polygons;

[0024] S4.3. Perform a polygonal drop arrangement of the remaining particles of different sizes within the target rectangular area of ​​the porous medium.

[0025] The polygons with different particle size values ​​are pre-processed as follows in S4.1:

[0026] S4.1.1. Multiply the vertex coordinates of the polygons of different particle sizes by the expansion coefficient a, where a is the coefficient containing N u An array of elements, each element is the same as N u The polygons of different particle sizes correspond one to one, and each element is a random number greater than or equal to 1. The size of the expansion coefficient is controlled by region to control the formation of connected and non-connected areas, as well as the formation of irregular throats;

[0027] S4.1.2. The polygons of different particle sizes are rotated counterclockwise at a random angle α.

[0028] The specific steps for arranging and forming the first row of polygons at the bottom of the target rectangular area of ​​the porous medium in S4.2 are as follows:

[0029] S4.2.1. Take the first polygon of different particle size in the polygon group and place it in the lower left corner of the target rectangular area of ​​the porous medium;

[0030] S4.2.2. Then, take a second polygon of a different particle size from the polygon group, place it to the right of the first polygon of a different particle size, move it to the left so that it touches the first polygon of a different particle size, and then take a polygon of a different particle size from the polygon group and place it to the right of the first polygon of a different particle size so that it touches the first polygon of a different particle size.

[0031] S4.2.3. When placing the i-th polygon of different particle size, if the polygon of different particle size exceeds the right boundary of the rectangle, the placement operation of the i-th polygon is canceled and the i-1 polygons of different particle size that have been arranged are recorded. During the arrangement process, all polygons of different particle size cannot exceed the boundary of the target rectangular area of ​​the porous medium;

[0032] The polygons of different particle sizes are joined using the advance and retreat method, wherein each time the polygons of different particle sizes move, the n nearest to them must be determined and recorded. b polygons of different particle sizes, where n b ≥5, when n b <5, calculate according to the actual number and compare it with the n b Overlap detection is performed on polygons.

[0033] The steps for arranging the remaining polygons of different particle sizes in S4.3 are as follows:

[0034] S4.3.1. Generate a list of candidate arrangement positions for polygons of different particle sizes i;

[0035] S4.3.2. Obtain the upper boundary length S of the total bounding rectangle of the placed polygons, obtain the bounding rectangles of each placed polygon, and record the minimum side length S min , divide the upper boundary length S of the total outer rectangle into n segments with Smin / h as the unit, and obtain a list of candidate polygon arrangement positions with n segmentation points as the i-th different particle size, where n is calculated by the following formula;

[0036]

[0037] Where: h≥1, n represents n segments; Indicates rounding up. To divide the upper boundary length S of the total outer rectangle.

[0038] Steps for placing polygons of different particle sizes in S4.3:

[0039] Move the polygon of the i-th different particle size to the first candidate arrangement position, then move it down to touch the placed polygon, and record the global coordinate position of the polygon of the i-th different particle size and the maximum value of the vertical coordinate y max , perform the above operations on the i-th polygons of different particle sizes in the remaining candidate arrangement positions in turn;

[0040] When the polygon of the i-th different particle size exceeds the boundary of the target rectangular area of ​​the porous medium after the operation at a certain candidate arrangement position, the coordinate information of the polygon of the i-th different particle size after the operation is not recorded. All candidate arrangement positions are traversed, and after the above operation is performed, the minimum value among all the maximum values ​​of the vertical coordinates is obtained. The global coordinate position of the i-th polygon corresponding to the minimum value is selected as the final placement position of the i-th polygon, and the center point C of the outer rectangle of the i-th polygon is recorded as its positioning point;

[0041] Then, the above operations are performed on the remaining polygons of different particle sizes in turn. During the process, an overflow detection parameter u of the number of polygons is set. The detection parameter u is the number of polygons of different particle sizes that cannot be placed in the target rectangular area of ​​the porous medium.

[0042] When there are more than three polygons that cannot be placed, the polygon arrangement process is stopped and the coordinate information of all the polygons that have been arranged is recorded.

[0043] The process of drawing the filling results of multiple scaled polygons with different particle size values ​​in the target rectangular area of ​​the porous medium in step 5 is as follows:

[0044] S5.1. Obtain and record the coordinates of all arranged polygons with the same particle size value;

[0045] S5.2. Divide the coordinates of all arranged polygons with the same particle size by the expansion coefficient a and move them back to their original positions through their respective positioning points;

[0046] S5.3. Draw the target rectangle and all the arranged polygons, calculate the polygon area ratio, and output them as a randomly generated two-dimensional porous medium.

[0047] Compared with the prior art, the present invention provides a method for generating a porous medium model for a microfluidic chip, which has the following beneficial effects:

[0048] 1. The present invention achieves the beneficial effect of precisely controlling the porosity, connectivity, and average pore size of the porous medium model by setting the particle number, particle size distribution, drawing scale, and expansion coefficient, and based on random polygon scaling, advance-retreat docking, and falling arrangement algorithms. This makes the model porosity controllable and the connectivity index flexible, thereby meeting the simulation requirements of different scenarios.

[0049] 2. The present invention achieves the beneficial effect of efficiently generating random irregular particle filling models by simulating the deposition formation process of porous media, adopting polygon vertex coordinate expansion and random rotation preprocessing, and combining the candidate arrangement position list with the overlap detection mechanism, thereby greatly increasing the arrangement efficiency and forming complex connected structures and irregular throats by controlling the expansion coefficient in different regions.

[0050] 3. The present invention systematically analyzes the influence of various parameters on model performance and constructs a parameter-performance mapping relationship, thereby achieving the beneficial effects of rapidly optimizing the model generation process and realizing model customization. It can be used for research and engineering applications such as microfluidic chip fluid penetration simulation and filter material design, and can quickly generate porous media models that meet specific needs, thereby improving modeling efficiency and application adaptability. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 Flow chart of the method of the present invention;

[0052] Figure 2 This is a random two-dimensional porous medium diagram obtained in Example 1 of the present invention. DETAILED DESCRIPTION

[0053] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0054] See also Figure 1-Figure 2 A method for generating a porous medium model for a microfluidic chip, characterized by comprising the following steps:

[0055] Step 1: Set the key parameters for generating porous media, including the target rectangular area of ​​the porous media, the area of ​​the target rectangular area of ​​the porous media, the drawing scale, and the number of particles N to be generated. u and the particle size distribution range, and the unit of the drawing scale is: μm / unit coordinate, where μm represents the length measurement unit of the porous medium in reality, and the coordinate represents the length measurement unit in the computer program;

[0056] Step 2: Generate random irregular particles. There are N irregular particles. u The random polygons are recorded with vertex coordinates in the local coordinate system. The vertex coordinates are recorded in the counterclockwise direction as the positive direction of the random polygon, and each random polygon is randomly assigned a particle size value p. r , and the same particle size value is not reused;

[0057] Step 3: scaling multiple polygons with different particle size values ​​to obtain multiple scaled polygons with different particle size values;

[0058] Step 4: Fill the generated porous medium target rectangular area with multiple scaled polygons of different particle size values ​​to simulate the deposition formation process of the porous medium;

[0059] Step 5: Draw the filling results of multiple scaled polygons with different particle size values ​​in the target rectangular area of ​​the porous medium to obtain a random two-dimensional porous medium for simulating the anisotropy of the porous medium.

[0060] The target rectangular area of ​​the porous medium is: W×Hμm 2 , where: W is the rectangular width of the target rectangular area of ​​the porous medium, and H is the rectangular height of the target rectangular area of ​​the porous medium.

[0061] In step 1, N u The total area of ​​the particles is larger than the target rectangular area of ​​the porous medium.

[0062] The expression for scaling polygons with different particle size values ​​is:

[0063]

[0064] In the formula, P r Indicates that each polygon is randomly assigned a particle size value, C d represents the length of the major axis of each polygon; p co is the scaling factor; p sa is the scale;

[0065] Furthermore, multiple polygons with the same particle size value are scaled to form a polygon group that satisfies the particle size distribution.

[0066] The deposition formation process of the simulated porous medium in step 4 is specifically as follows:

[0067] S4.1. Preprocessing polygons with different particle size values;

[0068] S4.2. Arrange the pretreated polygons of different particle sizes at the bottom of the target rectangular area of ​​the porous medium to form a first row of polygons;

[0069] S4.3. Perform a polygonal drop arrangement of the remaining particles of different sizes within the target rectangular area of ​​the porous medium.

[0070] The polygons with different particle size values ​​are pre-processed as follows in S4.1:

[0071] S4.1.1. Multiply the vertex coordinates of the polygons of different particle sizes by the expansion coefficient a, where a is the coefficient containing N u An array of elements, each element is the same as N u The polygons of different particle sizes correspond one to one, and each element is a random number greater than or equal to 1. The size of the expansion coefficient is controlled by region to control the formation of connected and non-connected areas, as well as the formation of irregular throats;

[0072] S4.1.2. The polygons of different particle sizes are rotated counterclockwise at a random angle α.

[0073] The specific steps for arranging and forming the first row of polygons at the bottom of the target rectangular area of ​​the porous medium in S4.2 are as follows:

[0074] S4.2.1. Take the first polygon of different particle size in the polygon group and place it in the lower left corner of the target rectangular area of ​​the porous medium;

[0075] S4.2.2. Then, take a second polygon of a different particle size from the polygon group, place it to the right of the first polygon of a different particle size, move it to the left so that it touches the first polygon of a different particle size, and then take a polygon of a different particle size from the polygon group and place it to the right of the first polygon of a different particle size so that it touches the first polygon of a different particle size.

[0076] S4.2.3. When placing the i-th polygon of different particle size, if the polygon of different particle size exceeds the right boundary of the rectangle, the placement operation of the i-th polygon is canceled and the i-1 polygons of different particle size that have been arranged are recorded. During the arrangement process, all polygons of different particle size cannot exceed the boundary of the target rectangular area of ​​the porous medium;

[0077] The polygons of different particle sizes are joined using the advance and retreat method, wherein each time the polygons of different particle sizes move, the n nearest to them must be determined and recorded. b polygons of different particle sizes, where n b ≥5, when n b <5, calculate according to the actual number and compare it with the n b Overlap detection is performed on polygons.

[0078] The steps for arranging the remaining polygons of different particle sizes in S4.3 are as follows:

[0079] S4.3.1. Generate a list of candidate arrangement positions for polygons of different particle sizes i;

[0080] S4.3.2. Obtain the upper boundary length S of the total bounding rectangle of the placed polygons, obtain the bounding rectangles of each placed polygon, and record the minimum side length S min , divide the upper boundary length S of the total outer rectangle into n segments with Smin / h as the unit, and obtain a list of candidate polygon arrangement positions with n segmentation points as the i-th different particle size, where n is calculated by the following formula;

[0081]

[0082] Where: h≥1, n represents n segments; Indicates rounding up. To divide the upper boundary length S of the total outer rectangle.

[0083] Steps for placing polygons of different particle sizes in S4.3:

[0084] Move the polygon of the i-th different particle size to the first candidate arrangement position, then move it down to touch the placed polygon, and record the global coordinate position of the polygon of the i-th different particle size and the maximum value of the vertical coordinate y max, perform the above operations on the i-th polygons of different particle sizes in the remaining candidate arrangement positions in turn;

[0085] When the polygon of the i-th different particle size exceeds the boundary of the target rectangular area of ​​the porous medium after the operation at a certain candidate arrangement position, the coordinate information of the polygon of the i-th different particle size after the operation is not recorded. All candidate arrangement positions are traversed, and after the above operation is performed, the minimum value among all the maximum values ​​of the vertical coordinates is obtained. The global coordinate position of the i-th polygon corresponding to the minimum value is selected as the final placement position of the i-th polygon, and the center point C of the outer rectangle of the i-th polygon is recorded as its positioning point;

[0086] Then, the above operations are performed on the remaining polygons of different particle sizes in turn. During the process, an overflow detection parameter u of the number of polygons is set. The detection parameter u is the number of polygons of different particle sizes that cannot be placed in the target rectangular area of ​​the porous medium.

[0087] When there are more than three polygons that cannot be placed, the polygon arrangement process is stopped and the coordinate information of all the polygons that have been arranged is recorded.

[0088] The process of drawing the filling results of multiple scaled polygons with different particle size values ​​in the target rectangular area of ​​the porous medium in step 5 is as follows:

[0089] S5.1. Obtain and record the coordinates of all arranged polygons with the same particle size value;

[0090] S5.2. Divide the coordinates of all arranged polygons with the same particle size by the expansion coefficient a and move them back to their original positions through their respective positioning points;

[0091] S5.3. Draw the target rectangle and all the arranged polygons, calculate the polygon area ratio, and output them as a randomly generated two-dimensional porous medium.

[0092] The advantages are: the present invention achieves the beneficial effect of efficiently generating random irregular particle filling models by simulating the deposition formation process of porous media, adopting polygon vertex coordinate expansion and random rotation preprocessing, and combining the candidate arrangement position list and overlap detection mechanism, thereby greatly increasing the arrangement efficiency and forming complex connected structures and irregular throats by controlling the expansion coefficient in different regions.

[0093] Example 1

[0094] (1) Determine the key parameters for generating porous media

[0095] Set the target rectangular area size for generating porous media to 15×15μm 2 ;Number of particles N u=200; particle size distribution range 1~1.3μm accounts for 40%, 1.3~2μm accounts for 50%, 2~2.3μm accounts for 5%, 2.3~2.5μm accounts for 5%, set the scale to p sa =1 / 50(μm / unit coordinate);

[0096] (2) Generate random irregular particles

[0097] Generate 200 random polygons (length units are coordinates) and calculate the major axis length c of each polygon d (length unit is coordinate), randomly assign a particle size value p r (unit of length is μm), according to the following formula Scaling the polygons to obtain a polygon group that satisfies the particle size distribution;

[0098] (3) Fill the target rectangular area with particles.

[0099] 1. Polygon preprocessing

[0100] S1.1. Multiply the coordinates of each polygon vertex by the expansion coefficient a, where a is the coefficient containing N u An array of elements, each element corresponds to Nu polygons one by one, and each element is a random number greater than or equal to 1;

[0101] S1.2. Each polygon is rotated counterclockwise at a random angle α.

[0102] 2. Arrange the first row of polygons at the bottom of the rectangle: Take the first polygon in the polygon group and place it in the lower left corner of the rectangular area. Then take the second polygon and place it to the right of the first polygon. Then move it to the left and touch it with the first polygon. Take the next polygon and place it to the right of the previous polygon and touch it with the previous polygon. When placing the i-th polygon, if the polygon exceeds the right boundary of the rectangle, cancel the placement operation of the i-th polygon and record the i-1 polygons that have been arranged. During the arrangement process, all polygons cannot exceed the boundary of the rectangle.

[0103] In the above process, polygons are docked using the advance and retreat method, in which each time a polygon moves, it is necessary to determine and record the five polygons closest to it (if there are less than five, calculate according to the actual number), and perform overlap detection with the five polygons.

[0104] 3. Arrange the remaining polygons downwards. The operation is as follows:

[0105] The first step is to generate a list of candidate arrangement positions for polygon i. First, obtain the upper boundary length S of the total enclosing rectangle of the placed polygons, obtain the enclosing rectangles of each placed polygon, and record the minimum side length S. min, divide the upper boundary length S of the total outer rectangle into n segments with Smin / h as the unit, and obtain a list of candidate polygon arrangement positions with n segmentation points as the i-th different particle sizes,

[0106] Where n is given by the formula calculate;

[0107] The second step is the falling arrangement of polygons. Move polygon i to the first candidate arrangement position, then move it down to touch the placed polygons, and record the global coordinate position of polygon i and the maximum vertical coordinate y at this time. max . Repeat the above operation for polygon i at the remaining candidate arrangement positions. If polygon i exceeds the rectangle boundary after the operation at a candidate arrangement position, the coordinate information of polygon i after the operation is not recorded. After traversing all candidate arrangement positions and performing the above operation, obtain the minimum value among all ymax, select the global coordinate position of polygon i corresponding to the minimum value as the final placement position of polygon i, and record the center point C of the outer rectangle of polygon i as its positioning point.

[0108] Repeat the above operation for polygon i+1 and the remaining polygons. During the process, the parameter u is used to check the number of polygons for overflow. If there are more than three polygons that cannot be placed, the polygon arrangement process is stopped and the coordinate information of all the polygons that have been arranged is recorded.

[0109] 4. Divide the coordinates of all arranged polygons by the expansion coefficient a, and move the polygons back to their original positions through their respective positioning points. Draw the target rectangle and all arranged polygons, and calculate the polygon area ratio.

[0110] The execution result of the above process is as follows Figure 2 As shown (the execution result is random two-dimensional porous media).

[0111] Example 2 (Showing the Effect of Different Particle Size Distributions on Porous Media Models)

[0112] Steps:

[0113] S1. Determine the key parameters for generating porous media: The target rectangular area size is set to 15×15μm 2 ; The number of particles is set to 200; the particle size distribution range is 1-1.5 μm accounting for 30%, 1.5-2.5 μm accounting for 40%, 2.5-3 μm accounting for 20%, and 3-3.5 μm accounting for 10%; drawing scale: 1 / 50 (μm / unit coordinate).

[0114] S2. Generate random irregular particles: Generate 200 random polygons (length units are coordinates); calculate the length of the major axis of each polygon (unit is coordinates); randomly assign a particle size value (unit is μm), and scale the polygons according to the following formula to obtain a polygon group that satisfies the particle size distribution;

[0115] S3. Fill the target rectangular area with particles: Polygon preprocessing: Multiply the vertex coordinates of each polygon by the expansion coefficient a, where a is an array containing 200 elements, each element corresponding to the 200 polygons, and each element is a random number greater than or equal to 1; rotate each polygon counterclockwise at a random angle; arrange the first row of polygons at the bottom of the rectangle, use the advance and retreat method to dock them, and record the five closest polygons for overlap detection; perform the drop arrangement of the remaining polygons, generate a list of candidate arrangement positions, and then perform the drop arrangement of the polygons;

[0116] S4. Divide the coordinates of all arranged polygons by the expansion coefficient a, and move the polygons back to their original positions through their respective positioning points. Draw the target rectangle and all arranged polygons, and calculate the polygon area ratio.

[0117] Comparative Example 1 (Showing the Effect of Different Expansion Coefficients on Porous Media Models)

[0118] Steps and procedures: Use the parameters in Example 1, except that the expansion coefficient a is set differently. For example, it can be set to a fixed value instead of a random number, or set to a smaller range to observe the effect of the expansion coefficient on the connectivity of the model;

[0119] The performance of Examples 1-2 and Comparative Example 1 was compared to obtain the following test data:

[0120] Table 1

[0121]

[0122] From the analysis of Table 1, we can get:

[0123] 1. Influence of particle size distribution (Examples 1 and 2): When the number of large-size particles increases, the porosity increases (the particles are not tightly arranged), but the connectivity index decreases, the arrangement efficiency decreases, and the average pore size increases.

[0124] 2. Influence of expansion coefficient (Example 1 and Comparative Example 1): When the expansion coefficient decreases, the porosity decreases but the connectivity index increases, the arrangement efficiency increases, and the average pore size decreases.

[0125] Summary: The comparative data of the embodiments and comparative examples show that the embodiments of the present invention can accurately control the key parameters of the porosity, connectivity and pore size of the porous media model. By adjusting the particle size distribution and expansion coefficient parameters, the influence of various factors on the model performance can be systematically observed: increasing the proportion of large-size particles can increase the porosity but reduce the connectivity; the setting of the expansion coefficient affects the density of particle arrangement and the uniformity of pores. Based on the above rules, the model generation process can be optimized in a targeted manner to meet the customized requirements of porous media models for different studies (such as fluid permeation simulation, material structure analysis) and engineering applications (such as filter material design), providing related fields with an efficient and flexible model construction method.

[0126] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A method for generating a porous medium model for a microfluidic chip, characterized in that: The following steps are involved: Step 1: Set the key parameters for generating porous media, including the target rectangular area of ​​the porous media, the area of ​​the target rectangular area of ​​the porous media, the drawing scale, and the number of particles N to be generated. u and the particle size distribution range, and the unit of the drawing scale is: μm / unit coordinate, where μm represents the length measurement unit of the porous medium in reality, and the coordinate represents the length measurement unit in the computer program; Step 2: Generate random irregular particles. There are N irregular particles. u The random polygons are recorded with vertex coordinates in the local coordinate system. The vertex coordinates are recorded in the counterclockwise direction as the positive direction of the random polygon, and each random polygon is randomly assigned a particle size value p. r , and the same particle size value is not reused; Step 3: scaling multiple polygons with different particle size values ​​to obtain multiple scaled polygons with different particle size values; Step 4: Fill the generated porous medium target rectangular area with multiple scaled polygons of different particle size values ​​to simulate the deposition formation process of the porous medium; Step 5: Draw the filling results of multiple scaled polygons with different particle size values ​​in the target rectangular area of ​​the porous medium to obtain a random two-dimensional porous medium for simulating the anisotropy of the porous medium.

2. The method for generating a porous medium model for a microfluidic chip according to claim 1, wherein: The target rectangular area of ​​the porous medium is: W×Hμm 2 , where: W is the rectangular width of the target rectangular area of ​​the porous medium, and H is the rectangular height of the target rectangular area of ​​the porous medium.

3. The method for generating a porous medium model for a microfluidic chip according to claim 2, wherein: In step 1, N u The total area of ​​the particles is larger than the target rectangular area of ​​the porous medium.

4. The method for generating a porous medium model for a microfluidic chip according to claim 3, wherein: The expression for scaling polygons with different particle size values ​​is: In the formula, P r Indicates that each polygon is randomly assigned a particle size value, C d represents the length of the major axis of each polygon; p co is the scaling factor; p sa is the scale; Furthermore, multiple polygons with the same particle size value are scaled to form a polygon group that satisfies the particle size distribution.

5. The method for generating a porous medium model for a microfluidic chip according to claim 4, characterized in that: The deposition formation process of the simulated porous medium in step 4 is specifically as follows: S4.

1. Preprocessing polygons with different particle size values; S4.

2. Arrange the pretreated polygons of different particle sizes at the bottom of the target rectangular area of ​​the porous medium to form a first row of polygons; S4.

3. Perform a polygonal drop arrangement of the remaining particles of different sizes within the target rectangular area of ​​the porous medium.

6. The method for generating a porous medium model for a microfluidic chip according to claim 5, characterized in that: The polygons with different particle size values ​​are pre-processed as follows in S4.1: S4.1.

1. Multiply the vertex coordinates of the polygons of different particle sizes by the expansion coefficient a, where a is the coefficient containing N u An array of elements, each element is the same as N u The polygons of different particle sizes correspond one to one, and each element is a random number greater than or equal to 1. The size of the expansion coefficient is controlled by region to control the formation of connected and non-connected areas, as well as the formation of irregular throats; S4.1.

2. The polygons of different particle sizes are rotated counterclockwise at a random angle α.

7. The method for generating a porous medium model for a microfluidic chip according to claim 5, wherein: The specific steps for arranging and forming the first row of polygons at the bottom of the target rectangular area of ​​the porous medium in S4.2 are as follows: S4.2.

1. Take the first polygon of different particle size in the polygon group and place it in the lower left corner of the target rectangular area of ​​the porous medium; S4.2.

2. Then, take a second polygon of a different particle size from the polygon group, place it to the right of the first polygon of a different particle size, move it to the left so that it touches the first polygon of a different particle size, and then take a polygon of a different particle size from the polygon group and place it to the right of the first polygon of a different particle size so that it touches the first polygon of a different particle size. S4.2.

3. When placing the i-th polygon of different particle size, if the polygon of different particle size exceeds the right boundary of the rectangle, the placement operation of the i-th polygon is canceled and the i-1 polygons of different particle size that have been arranged are recorded. During the arrangement process, all polygons of different particle size cannot exceed the boundary of the target rectangular area of ​​the porous medium; The polygons of different particle sizes are joined using the advance and retreat method, wherein each time the polygons of different particle sizes move, the n nearest to them must be determined and recorded. b polygons of different particle sizes, where n b ≥5, when n b <5, calculate according to the actual number and compare it with the n b Overlap detection is performed on polygons.

8. The method for generating a porous medium model for a microfluidic chip according to claim 5, wherein: The steps for arranging the remaining polygons of different particle sizes in S4.3 are as follows: S4.3.

1. Generate a list of candidate arrangement positions for polygons of different particle sizes for the i-th particle size; S4.3.

2. Obtain the upper boundary length S of the total bounding rectangle of the placed polygons, obtain the bounding rectangles of each placed polygon, and record the minimum side length S min , divide the upper boundary length S of the total outer rectangle into n segments with Smin / h as the unit, and obtain a list of candidate polygon arrangement positions with n segmentation points as the i-th different particle size, where n is calculated by the following formula; Where: h≥1, n represents n segmentation points; Indicates rounding up. To divide the upper boundary length S of the total outer rectangle.

9. The method for generating a porous medium model for a microfluidic chip according to claim 8, wherein: Steps for placing polygons of different particle sizes in S4.3: Move the polygon of the i-th different particle size to the first candidate arrangement position, then move it down to touch the placed polygon, and record the global coordinate position of the polygon of the i-th different particle size and the maximum value of the vertical coordinate y max , perform the above operations on the i-th polygons of different particle sizes in the remaining candidate arrangement positions in turn; When the polygon of the i-th different particle size exceeds the boundary of the target rectangular area of ​​the porous medium after the operation at a certain candidate arrangement position, the coordinate information of the polygon of the i-th different particle size after the operation is not recorded. All candidate arrangement positions are traversed, and after the above operation is performed, the minimum value among all the maximum values ​​of the vertical coordinates is obtained. The global coordinate position of the i-th polygon corresponding to the minimum value is selected as the final placement position of the i-th polygon, and the center point C of the outer rectangle of the i-th polygon is recorded as its positioning point; Then, the above operations are performed on the remaining polygons of different particle sizes in turn. During the process, an overflow detection parameter u of the number of polygons is set. The detection parameter u is the number of polygons of different particle sizes that cannot be placed in the target rectangular area of ​​the porous medium. When there are more than three polygons that cannot be placed, the polygon arrangement process is stopped and the coordinate information of all the polygons that have been arranged is recorded.

10. The method for generating a porous medium model for a microfluidic chip according to claim 9, characterized in that: The process of drawing the filling results of multiple scaled polygons with different particle size values ​​in the target rectangular area of ​​the porous medium in step 5 is as follows: S5.

1. Obtain and record the coordinates of all arranged polygons with the same particle size value; S5.

2. Divide the coordinates of all arranged polygons with the same particle size by the expansion coefficient a and move them back to their original positions through their respective positioning points; S5.

3. Draw the target rectangle and all the arranged polygons, calculate the polygon area ratio, and output them as a randomly generated two-dimensional porous medium.

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