A method for generating a porous medium model for a microfluidic chip

Abstract

The application relates to the technical field of microfluidics, and discloses a porous medium model generation method for a microfluidic chip. First, key parameters for generating a porous medium are set, then random irregular particles are generated, the particles are filled in a target rectangular area, finally, the arranged polygons are processed, drawn and counted, and through setting the particle quantity, the particle size distribution, a drawing scale and an expansion coefficient, based on a random polygon zooming, a forward and backward method abutting and a falling arrangement algorithm, the porosity, the connectivity and the average pore diameter of the porous medium model can be accurately controlled, meanwhile, through simulating a porous medium deposition forming process, using polygon vertex coordinate expansion and random rotation preprocessing, combining a candidate arrangement position list and an overlap detection mechanism, a random irregular particle filling model can be efficiently generated, and on this basis, through constructing a parameter-performance mapping relationship, the method reaches the beneficial effects of quickly optimizing a model generation process and realizing model customization.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of microfluidic technology, and particularly to a method for generating a porous medium model for a microfluidic chip. BACKGROUND

[0002] Porous media exist widely in nature and social life, involving many fields such as energy, heat and biology. In particular, the study of porous media is crucial in the development of groundwater and oil and gas resources. With the continuous development of the oil and gas industries, the recognition of the occurrence characteristics and flow characteristics of underground fluids is becoming increasingly demanding.

[0003] In order to more deeply study the seepage law of fluids in porous media, it is an effective method and has been widely used to make a micro-scale porous medium model and use it for seepage experiments. Currently, common methods for making micro porous medium models include real core models, artificial filling models and laser etching glass models. Among them, the laser etching glass model is widely used in the field of micro seepage research because of its good visibility and the ability to be directly made in the laboratory.

[0004] However, before making a laser etching glass model, a porous medium template needs to be prepared. Traditionally, obtaining a porous medium template often requires extracting and scanning a core, which is not only tedious, but also costly. Using computer technology to generate a digital porous medium template effectively eliminates these steps, greatly reducing the cost and time cost, and providing great convenience for micro seepage related research.

[0005] The porous medium template needs to reflect the connectivity and anisotropy of the real porous medium. Among the commonly used methods for constructing digital two-dimensional porous medium templates, there are 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 generated by it is too uniform. The random growth method controls the basic characteristics of the porous medium, such as connectivity and porosity, by adjusting four parameters, but this method produces single-point solids. SUMMARY

[0006] (I) Technical problems solved

[0007] In view of the deficiencies of the prior art, the present application provides a method for generating a porous medium model for a microfluidic chip, which has the advantages of high efficiency, convenience, low cost, high visualization and accurate control of model parameters, and solves the problems of tedious steps, high cost and difficulty in accurately controlling model characteristics in traditional production methods.

[0008] (II) Technical solutions

[0009] To achieve the above object, the application provides the following technical scheme: a porous medium model generation method for a microfluidic chip, characterized by comprising the following steps:

[0010] Step one, setting key parameters for generating a porous medium, the key parameters including a generated porous medium target rectangular area, a porous medium target rectangular area area, a drawing scale, a generated filled particle number N u and a particle size distribution range, and the unit of the drawing scale is: μm / unit coordinate, wherein μm represents the length measurement unit of the porous medium in reality, and coordinate represents the length measurement unit of the porous medium in the computer program;

[0011] Step two, generating random irregular particles, the irregular particles being N u and being random polygons, the random polygons being recorded in vertex coordinates in a local coordinate system, the vertex coordinate record being clockwise as the positive direction of the random polygon, and each random polygon being randomly assigned a particle size value p r , and the same particle size value not being repeatedly used;

[0012] Step three, scaling a plurality of polygons of different particle size values to obtain a plurality of scaled polygons of different particle size values;

[0013] Step four, filling the plurality of scaled polygons of different particle size values in the generated porous medium target rectangular area, for simulating the deposition formation process of the porous medium;

[0014] Step five, drawing the filling result of the plurality of scaled polygons of different particle size values in the porous medium target rectangular area to obtain a random two-dimensional porous medium, for simulating the anisotropy of the porous medium.

[0015] The generated porous medium target rectangular area area is: W×H μm 2 , wherein W is the rectangular width of the porous medium target rectangular area, and H is the rectangular height of the porous medium target rectangular area.

[0016] The total area of the N u particles in step one is greater than the porous medium target rectangular area area.

[0017] The expression for scaling the polygons of different particle size values is:

[0018]

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

[0020] and the polygons of the plurality of same size values are scaled to form a polygon group satisfying the particle size distribution.

[0021] The step four of simulating the deposition process of the porous medium is specifically as follows:

[0022] S4.1, pre-processing the polygons of different particle size values;

[0023] S4.2, arranging and forming the first row of polygons of different particle sizes at the bottom of the target rectangular region of the porous medium;

[0024] S4.3, arranging the remaining polygons of different particle sizes to fall within the target rectangular region of the porous medium.

[0025] The pre-processing of the polygons of different particle size values in S4.1 is as follows:

[0026] S4.1.1, multiplying the vertex coordinates of each polygon of different particle size by an expansion coefficient a, a is an array containing N u elements, each element corresponds to a polygon of N u different particle sizes, and each element is a random number greater than or equal to 1, and the size of the expansion coefficient is controlled by region to control the formation of connected and unconnected regions, as well as irregular throats;

[0027] S4.1.2, each polygon of different particle size is rotated counterclockwise at a random angle a.

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

[0029] S4.2.1, taking the first polygon of different particle size from the polygon group and placing it at the lower left corner of the target rectangular region of the porous medium;

[0030] S4.2.2, then taking the second polygon of different particle size from the polygon group and placing it to the right of the first polygon of different particle size, moving it to the left to abut the first polygon of different particle size, and sequentially taking the next polygon of different particle size from the polygon group and placing it to the right of the previous polygon of different particle size, and abutting the previous polygon of 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, cancel the placement operation of the i-th polygon, record the i-1 polygons of different particle sizes that have been arranged, and all the polygons of different particle sizes in the arrangement process cannot exceed the boundary of the target rectangular region of the porous medium.

[0032] The abutment of polygons of different sizes uses the advance and retreat method, wherein the movement of polygons of different sizes each time needs to judge and record the n b different sizes of polygons closest to it, wherein n b ≥5, and when n b <5, the actual number is calculated, and overlap detection is performed with the n b polygons.

[0033] The falling arrangement step of the remaining polygons of different sizes in S4.3 is as follows:

[0034] S4.3.1, generate a candidate arrangement position list of the i-th polygon of different sizes;

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

[0036]

[0037] wherein: h≥1, n represents n segments; represents the upward rounding, Smin is the segmentation of the upper boundary length S of the total bounding rectangle.

[0038] The placement step of the polygons of different sizes in S4.3 is as follows:

[0039] Move the i-th polygon of different sizes to the first candidate arrangement position, then move it downward to abut the placed polygons, record the global coordinate position of the i-th polygon of different sizes at this time and the maximum longitudinal coordinate y max , and sequentially perform the above operation on the i-th polygon of different sizes at the remaining candidate arrangement positions;

[0040] When the i-th polygon of different sizes exceeds the boundary of the target rectangular region of the porous medium after operation at a certain candidate arrangement position, the coordinate information of the i-th polygon of different sizes after operation at this time is not recorded, after traversing all candidate arrangement positions and performing the above operation, the minimum value of all longitudinal coordinate maximum values 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 bounding rectangle of the i-th polygon is recorded as its positioning point;

[0041] Subsequently, the above operation is sequentially performed on the remaining polygons of different particle sizes, and an overflow detection parameter u of the number of polygons is set during the process, and 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 the number of polygons that cannot be placed is more than three, the polygon arrangement process is stopped, and the coordinate information of all the arranged polygons is recorded.

[0043] The step five draws the filling results of the polygons of different particle sizes after scaling in the target rectangular area of the porous medium, and the process is as follows:

[0044] S5.1, obtaining and recording the coordinates of all the arranged polygons of the same particle size;

[0045] S5.2, dividing the coordinates of all the arranged polygons of the same particle size by the expansion coefficient a, and moving back to the original position through the respective positioning points of the polygons;

[0046] S5.3, drawing the target rectangle and all the arranged polygons, and counting the area ratio of the polygons, as a two-dimensional porous medium generated randomly and output.

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

[0048] 1. The present application sets the particle number, particle size distribution, drawing scale and expansion coefficient, and achieves the beneficial effects of accurately controlling the porosity, connectivity and average pore diameter of the porous medium model through the random polygon scaling, advancing and retreating method and the falling arrangement algorithm, so that the model porosity is controllable and the connectivity index can be flexibly adjusted, thereby meeting the simulation needs of different scenes.

[0049] 2. The present application simulates the deposition formation process of the porous medium, adopts polygon vertex coordinate expansion and random rotation preprocessing, combines the candidate arrangement position list and the overlap detection mechanism, and achieves the beneficial effects of efficiently generating a random irregular particle filling model, greatly increases the arrangement efficiency, and can form a complex connected structure and an irregular throat through regional control of the expansion coefficient.

[0050] 3. The present application systematically analyzes the influence law of each parameter on the model performance, constructs a parameter-performance mapping relationship, achieves the beneficial effects of quickly optimizing the model generation process and realizing model customization, and can be applied to research and engineering applications such as microfluidic chip fluid permeation simulation and filter material design, quickly generate a porous medium model that meets specific needs, and improve the modeling efficiency and application adaptability. BRIEF DESCRIPTION OF DRAWINGS

[0051] Fig. 1 The method flowchart of the present application;

[0052] Fig. 2 A random two-dimensional porous medium map obtained by the embodiment 1 of the present application. DETAILED DESCRIPTION

[0053] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0054] Please refer to Figs. 1-2 A porous medium model generation method for a microfluidic chip, characterized in that it comprises the following steps:

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

[0056] Step 2: Generate random irregular particles, which are N u and are random polygons, the random polygons are recorded in the vertex coordinates in the local coordinate system, the vertex coordinate record takes counterclockwise 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 repeated;

[0057] Step 3: Scale the polygons of different particle size values to obtain polygons of different particle size values after scaling;

[0058] Step 4: Fill the polygons of different particle size values after scaling in the generated porous medium target rectangular area, for simulating the deposition formation process of the porous medium;

[0059] Step 5: Draw the filling result of the polygons of different particle size values after scaling in the porous medium target rectangular area to obtain a random two-dimensional porous medium, for simulating the anisotropy of the porous medium.

[0060] The generated porous medium target rectangular area area is: W×H μm 2 , wherein: W is the rectangular width of the porous medium target rectangular area, and H is the rectangular height of the porous medium target rectangular area.

[0061] The total area of the N u particles in step one is greater than the area of the target rectangular region of the porous medium.

[0062] The expression for scaling the polygons of different particle size values is:

[0063]

[0064] In the formula, P r represents 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; and p sa is the scale.

[0065] and the scaled polygons of the same particle size value form a polygon group that satisfies the particle size distribution.

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

[0067] S4.1, pre-processing the polygons of different particle size values;

[0068] S4.2, arranging and forming the first row of polygons of different particle sizes at the bottom of the target rectangular region of the porous medium;

[0069] S4.3, arranging the remaining polygons of different particle sizes to fall within the target rectangular region of the porous medium.

[0070] The pre-processing of the polygons of different particle size values in S4.1 is as follows:

[0071] S4.1.1, multiplying the vertex coordinates of each polygon of different particle size by an expansion coefficient a, a is an array containing N u elements, each element corresponds to one of the N u different particle size polygons, and each element is a random number greater than or equal to 1. The size of the expansion coefficient is controlled by dividing the area to control the formation of connected and unconnected regions, as well as irregular throats.

[0072] S4.1.2, each polygon of different particle size is rotated counterclockwise at a random angle a.

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

[0074] S4.2.1, taking the first polygon of different particle size from the polygon group and placing it at the lower left corner of the target rectangular region of the porous medium;

[0075] S4.2.2, then take the second different size polygon in the polygon group, place it on the right side of the first different size polygon, move it to the left to abut the first different size polygon, and sequentially take the next different size polygon in the polygon group and place it on the right side of the previous different size polygon, and abut the previous different size polygon;

[0076] S4.2.3, when placing the i-th different size polygon, if the different size polygon exceeds the right boundary of the rectangle, cancel the placement operation of the i-th polygon, record the i-1 different size polygons that have been arranged, and all different size polygons during the arrangement process cannot exceed the boundary of the target rectangular region of the porous medium;

[0077] The abutting of the different size polygons uses a forward and backward method, wherein the different size polygons need to be judged and recorded each time they move, and the n b different size polygons closest to them are recorded, wherein n b ≥ 5, and when n b < 5, the actual number is calculated, and overlap detection is performed with the n b polygons.

[0078] The falling arrangement step of the remaining different size polygons in S4.3 is as follows:

[0079] S4.3.1, generate a candidate arrangement position list of the i-th different size polygon;

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

[0081]

[0082] wherein: h ≥ 1, n represents n segments; represents rounding up, and Smin / h is the segmentation of the upper boundary length S of the total bounding rectangle.

[0083] The placement step of the different size polygons in S4.3 is as follows:

[0084] Move the i-th different size polygon to the first candidate arrangement position, then move it downward to abut the placed polygon, record the global coordinate position of the i-th different size polygon at this time and the maximum longitudinal coordinate y max, the i-th polygon of the different particle size is operated in the remaining candidate arrangement position in turn;

[0085] When the i-th polygon of the different particle size after operation exceeds the boundary of the target rectangular region of the porous medium at a certain candidate arrangement position, the coordinate information of the i-th polygon of the different particle size after operation is not recorded, all candidate arrangement positions are traversed, and after operation as above, the minimum value in all maximum vertical coordinate values 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 package rectangle of the i-th polygon is recorded as the positioning point of the i-th polygon;

[0086] Subsequently, the above operation is sequentially performed on the remaining polygons of different particle sizes, and an overflow detection parameter u of the number of polygons is set during the operation, and the detection parameter u is the number of polygons of different particle sizes that cannot be placed in the target rectangular region of the porous medium;

[0087] When the number of polygons that cannot be placed exceeds three, the polygon arrangement process is stopped, and the coordinate information of all arranged polygons is recorded.

[0088] The flow of the step five of drawing the filling result of the plurality of scaled polygons of different particle sizes in the target rectangular region of the porous medium is:

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

[0090] S5.2, divide the coordinates of all arranged polygons of the same particle size value by the expansion coefficient a, and move back to the original position through the positioning point of each polygon;

[0091] S5.3, draw the target rectangle and all arranged polygons, and count the area ratio of the polygons, as a randomly generated two-dimensional porous medium and output.

[0092] Advantages are: the present application simulates the deposition formation process of the porous medium, adopts polygon vertex coordinate expansion and random rotation pretreatment, combines the candidate arrangement position list and the overlap detection mechanism, achieves the beneficial effect of efficiently generating a random irregular particle filling model, greatly increases the arrangement efficiency, and can form a complex connected structure and an irregular throat through regional control of the expansion coefficient.

[0093] Example 1

[0094] (1) Determine the key parameters of generating the porous medium

[0095] The size of the target rectangular region of the generated porous medium is set to 15*15 μm 2 ; the number of particles N u= 200; particle size distribution range 1-1.3 pm accounted for 40%, 1.3-2 pm accounted for 50%, 2-2.3 pm accounted for 5%, 2.3-2.5 pm accounted for 5%, set the scale p sa = 1 / 50 (pm / unit coordinate);

[0096] (2) generating random irregular particles

[0097] Generate 200 random polygons (length unit is coordinate), calculate the length of the long axis of each polygon c d (length unit is coordinate), randomly assign a particle size value p r (length unit is pm), according to the following formula Scale the polygon to get a polygon group that meets the particle size distribution;

[0098] (3) fill the particles in the target rectangular area.

[0099] 1. Polygon preprocessing

[0100] S1.1, multiply the coordinates of each polygon vertex by the expansion coefficient a, a is an array containing N u elements, each element corresponds to one of the Nu polygons, 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 a.

[0102] 2. Arrange the first row of polygons at the bottom of the rectangle: take the first polygon from the polygon group and place it at 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 left to abut the first polygon, and so on. Take the next polygon and place it to the right of the previous polygon, and abut the previous polygon. When placing the ith polygon, if the polygon exceeds the right boundary of the rectangle, cancel the placement of the ith polygon, record the i-1 polygons that have been arranged, and all polygons during the arrangement process cannot exceed the boundary of the rectangle.

[0103] In the above process, the abutment of the polygon uses the advance and retreat method, in which the polygon needs to be judged and recorded each time it moves to the nearest 5 polygons (if there are less than 5, calculate according to the actual number), and overlap detection is performed with the 5 polygons.

[0104] 3. Perform the falling arrangement of the remaining polygons, which is:

[0105] First, generate a list of candidate arrangement positions for polygon i. First, get the upper boundary length S of the total bounding rectangle of the placed polygons, get the bounding rectangle of each placed polygon, and record the minimum side length S minSmin / h as a unit, the length S of the upper boundary of the total bounding rectangle is divided into n segments, and n segmentation points are obtained as the candidate arrangement position list of the polygon of the ith different particle size,

[0106] where n is calculated by the formula .

[0107] Second step, the falling arrangement of the polygon. Move the polygon i to the first candidate arrangement position, then move it downward to abut the placed polygon, record the global coordinate position of the polygon i at this time and the maximum value y max max of the vertical coordinate. Perform the above operation on the polygon i in the remaining candidate arrangement positions. If the polygon i exceeds the rectangular boundary after the operation at a candidate arrangement position, do not record the coordinate information of the polygon i after the operation. After traversing all candidate arrangement positions and performing the above operation, obtain the minimum value of all ymax, select the global coordinate position of the polygon i corresponding to the minimum value as the final placement position of the polygon i, and record the bounding rectangle center point C of the polygon i as its positioning point.

[0108] Perform the above operation on the polygon i+1 and the remaining polygons in turn. Overflow detection of the number of polygons is performed through the parameter u during the process, and when the number of polygons without a place to put exceeds three, stop the polygon arrangement process and record the coordinate information of all the arranged polygons.

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

[0110] The execution result of the above process is shown in Fig. 2 .

[0111] Example 2 (showing the effect of different particle size distribution on the porous medium model)

[0112] Step flow:

[0113] S1, determine the key parameters for generating the porous medium: the target rectangular area size is set to 15x15μm 2 ; the number of particles is set to 200; the particle size distribution range is 1-1.5μm accounting for 30%, 1.5-2.5μm accounting for 40%, 2.5-3μm accounting for 20%, and 3-3.5μm accounting for 10%; the drawing scale is 1 / 50(μm / unit coordinate).

[0114] S2, generating random irregular particles: generating 200 random polygons (length unit: coordinates); calculating the length of the long axis of each polygon (unit: coordinates); randomly assigning a particle size value (unit: pm); scaling the polygon according to the following formula to obtain a polygon group that meets the particle size distribution;

[0115] S3, filling particles in the target rectangular area: polygon pretreatment: multiply the coordinates of each polygon vertex by the expansion coefficient a, a is an array containing 200 elements, each element corresponds to one of the 200 polygons, and each element is a random number greater than or equal to 1; each polygon is rotated counterclockwise at a random angle; arrange the first row of polygons at the bottom of the rectangle, use the advance and retreat method to abut, and record the five polygons closest to it for overlap detection; perform the falling arrangement of the remaining polygons to generate a list of candidate arrangement positions, and perform the falling arrangement of the polygons;

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

[0117] Comparative Example 1 (showing the effect of different expansion coefficients on the porous medium model)

[0118] Step flow: 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 to a smaller range, to observe the effect of the expansion coefficient on the connectivity of the model;

[0119] Compare the performance of Examples 1-2 with Comparative Example 1 to obtain the following test data:

[0120] Table 1

[0121]

[0122] From Table 1, we can conclude that:

[0123] 1. The effect of particle size distribution (Example 1 and Example 2): When the particle size of the large particles increases, the porosity increases (the particles are not closely arranged) but the connectivity index decreases, the arrangement efficiency decreases, and the average pore size increases.

[0124] 2. The effect of the 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: Through the comparison data of examples and comparative examples, it is shown that the examples of the present application can accurately regulate the key parameters of porosity, connectivity and pore size of the porous medium model, and by adjusting the particle size distribution and expansion coefficient parameters, the influence law of each factor on the model performance can be systematically observed: increasing the proportion of large particle size can increase the porosity but reduce the connectivity; the setting of the expansion coefficient affects the close arrangement of particles and the uniformity of pores, based on the above law, the model generation process can be optimized accordingly to meet the customized needs of different researches (such as fluid permeation simulation, material structure analysis) and engineering applications (such as filter material design) for porous medium models, and to provide an efficient and flexible model construction method for related fields.

[0126] Although embodiments of the present application have been shown and described, it is to be understood that various modifications, substitutions, replacements and changes can be made to these embodiments without departing from the principles and spirit of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for generating porous media models for microfluidic chips, characterized in that, Includes the following steps: Step 1: Set the key parameters for generating the porous medium. These parameters include the target rectangular region of the porous medium, the area of ​​the target rectangular region, 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 its length measurement unit in the computer program; Step 2: Generate random irregular particles. There are N irregular particles. u Each polygon is a random polygon, recorded using vertex coordinates in a local coordinate system. The positive direction of the vertex coordinates is counterclockwise. Each random polygon is randomly assigned a particle size value p. r Furthermore, the same particle size value should not be reused; Step 3: Scale the polygons with different particle size values ​​to obtain multiple scaled polygons with different particle size values. Step 4: Fill the generated porous media target rectangular area with multiple scaled polygons of different particle size values ​​to simulate the deposition and formation process of porous media. Step 5: Draw multiple scaled polygons with different particle size values ​​to fill the target rectangular area of ​​the porous medium, and obtain a random two-dimensional porous medium to simulate the anisotropy of the porous medium.

2. The method for generating a porous medium model for a microfluidic chip according to claim 1, characterized in that: The area of ​​the target rectangular region for generating porous media is: W × H μm 2 Where: W is the width of the target rectangular region of the porous medium, and H is the height of the target rectangular region of the porous medium.

3. The method for generating a porous medium model for a microfluidic chip according to claim 2, characterized in that: In step one, N u The total area of ​​each particle is greater than the area of ​​the target rectangular region of the porous medium.

4. The method for generating a porous medium model for a microfluidic chip according to claim 3, characterized in that: The expression for scaling the polygons with different particle size values ​​is: In the formula, P r This means that each polygon is randomly assigned a grain size value, C. d p represents the length of the major axis of each polygon; co p is the scaling factor; sa For 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 simulated deposition process of porous media in step four is as follows: S4.1 Preprocessing of polygons with different particle size values; S4.2 Arrange the pre-treated polygons of different particle sizes at the bottom of the target rectangular region of the porous medium to form the first row of polygons; S4.

3. Arrange the remaining polygonal particles of different sizes in a rectangular area within the target porous medium.

6. The method for generating a porous medium model for a microfluidic chip according to claim 5, characterized in that: The preprocessing of polygons with different particle size values ​​in S4.1 is as follows: S4.1.1 Multiply the vertex coordinates of polygons with different particle sizes by the expansion coefficient 'a', where 'a' is the number of polygons containing N. u An array of n elements, each element and N u Each polygon with a different particle size corresponds one-to-one, and each element is a random number greater than or equal to 1. The expansion coefficient is controlled by dividing the region to control the formation of connected and disconnected regions, as well as irregular throats. S4.1.

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

7. The method for generating a porous medium model for a microfluidic chip according to claim 5, characterized in that: The specific steps in S4.2 to arrange and form the first row of polygons at the bottom of the target rectangular region of the porous medium are as follows: S4.2.1 Take the first polygon with a different particle size from 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 the second polygon with a different grain size from the polygon group, place it to the right of the first polygon with a different grain size, move it to the left to make it close to the first polygon with a different grain size, and then take the next polygon with a different grain size from the polygon group and place it to the right of the previous polygon with a different grain size, and make it close to the previous polygon with a different grain size. S4.2.3 When placing the i-th polygon with different particle size, if the polygon with different particle size exceeds the right boundary of the rectangle, the placement operation of the i-th polygon is cancelled, and the i-1 polygons with different particle size that have been arranged are recorded. During the arrangement process, all polygons with different particle size cannot exceed the boundary of the porous medium target rectangular area. The approach and contact of the polygons with different particle sizes is achieved using a forward and backward method. Each time a polygon with a different particle size moves, the nearest neighbor (n) must be determined and recorded. b A polygon with different particle sizes, where n b ≥5, when n b When the number is less than 5, calculate based on the actual number and combine it with the n value. b Overlap detection is performed on the polygons.

8. A method for generating a porous medium model for a microfluidic chip according to claim 5, characterized in that: The remaining polygonal arrangement steps with different particle sizes in S4.3 are as follows: S4.3.1 Generate a list of candidate permutation positions for the i-th polygon with different particle sizes; S4.3.

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

9. A method for generating a porous medium model for a microfluidic chip according to claim 8, characterized in that: The placement steps of polygons with different particle sizes in S4.3 are as follows: Move the i-th polygon with different particle sizes to the first candidate arrangement position, then move it down to be adjacent to the already placed polygons. Record the global coordinate position and the maximum value of the ordinate y of the i-th polygon with different particle sizes at this time. max The above operation is then performed sequentially on the i-th polygon with different particle sizes at the remaining candidate arrangement positions; If, after an operation at a candidate arrangement position, the i-th polygon with a different particle size exceeds the boundary of the target rectangular region of the porous medium, then the coordinate information of the i-th polygon with a different particle size after the operation is not recorded. After traversing all candidate arrangement positions and performing the above operation, 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. The above operation was then performed on the remaining polygons of different particle sizes in sequence. During the process, an overflow detection parameter u for the number of polygons was set. The detection parameter u is the number of polygons of different particle sizes that cannot be placed within the target rectangular area of ​​the porous medium. If there are more than three polygons that cannot be placed, the polygon arrangement process is stopped, and the coordinate information of all polygons that have been arranged is recorded.

10. A method for generating a porous medium model for a microfluidic chip according to claim 9, characterized in that: The process for step five, drawing multiple scaled polygons with different particle size values ​​to fill the target rectangular area of ​​the porous medium, is as follows: S5.1 Obtain and record the coordinates of all polygons with the same particle size after arrangement; S5.2 Divide the coordinates of all polygons with the same particle size after arrangement 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 polygons arranged in it, calculate the area ratio of the polygons, and output it as a randomly generated two-dimensional porous medium.

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