Electrolytic cell electrode pore model generation method

Abstract

The invention discloses an electrolytic cell electrode pore model generation method which comprises the following steps: S1, acquiring volume parameters of an electrode material, determining the thickness of each layer, determining the total number of layers, and acquiring the target porosity of each layer; s2, acquiring pore section shape parameters and pore size parameters of each layer; s3, setting a modeling base plane, randomly generating a pore structure in the nth layer, and automatically modeling the (n + 1) th layer after ensuring that the difference value between the accumulated porosity of the nth layer and the target porosity is less than or equal to a preset threshold value; s4, after modeling of the (n + 1) th layer is completed, the connectivity of adjacent upper-layer and lower-layer pore network flow channels is ensured through a pore surface matching algorithm; and S5, the steps S3 and S4 are repeated until the total thickness of the multi-layer pore structure reaches the target thickness of the electrode material, and an electrode pore model meeting the porosity requirement is formed. According to the electrolytic cell electrode pore model generation method provided by the invention, the difficulty of model generation and numerical calculation is further simplified while the characteristics of random distribution, different sizes and the like of pores are reserved.

Description

Technical Field

[0001] The present invention relates to the technical field of electrolytic cells, and in particular to a method for generating an electrolytic cell electrode pore model. Background Art

[0002] In water electrolyzers (such as proton exchange membrane electrolyzers and alkaline electrolyzers), porous electrodes undertake key functions such as reactant transport, product discharge, electron conduction, and mechanical support. The gas-liquid two-phase flow transport process inside the porous medium is a key factor affecting the electrolysis efficiency and dynamic response. During the electrolysis process, liquid water needs to penetrate through the porous diffusion layer or transport layer to the catalyst surface to participate in the reaction. At the same time, the generated hydrogen / oxygen needs to be reversely desorbed and discharged from the system. In this process, the capillary force and viscous resistance in the pores interact with the gas nucleation behavior, which can easily cause problems such as local bubble blockage and uneven distribution of reactants.

[0003] Simulation methods based on high-precision pore network models or three-dimensional reconstructed structures can study the local two-phase flow mechanism and predict key phenomena such as bubble coalescence paths and liquid phase permeation thresholds. However, traditional homogenization models ignore the heterogeneous characteristics of the pore scale, making it difficult to truly reflect the competitive transport mechanism of gas and liquid phases in complex pores. In particular, they are unable to quantify the impact of pore topology (such as connectivity and pore size gradient distribution) on the dynamic evolution of the two-phase interface and mass transfer efficiency. In addition, existing pore-level modeling methods rely on high-resolution microscopic imaging or random statistical reconstruction, and face bottlenecks such as high thresholds for experimental equipment and exponential growth in computational complexity. Therefore, there is an urgent need to develop porous media modeling technology that takes into account both microstructural fidelity and computational efficiency in order to optimize the two-phase transport dynamics and improve the performance of electrolyzers.

[0004] The statements herein merely provide background information related to the present invention and do not necessarily constitute prior art. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for generating a pore model of an electrolytic cell electrode, which further simplifies the difficulty of model generation and numerical calculation while retaining the characteristics of random distribution and different sizes of pores.

[0006] In order to achieve the above objectives, the present invention provides a method for generating an electrolytic cell electrode pore model, comprising the following steps: S1, obtaining volume parameters of the electrode material, determining the thickness of each layer and the total number of layers, and obtaining the target porosity of each layer; S2, obtaining the pore cross-sectional shape parameters and pore size parameters of each layer to determine the pore structure in each layer; S3, setting a modeling base surface, and performing three-dimensional pore structure construction layer by layer, that is, randomly generating a pore structure in the nth layer, and automatically performing modeling of the n+1th layer after ensuring that the difference between the cumulative porosity of the nth layer and the target porosity is ≤ a preset threshold; S4, when constructing the three-dimensional pore structure of the n+1th layer, repeating step S3, and after the n+1th layer modeling is completed, ensuring the connectivity of the pore network flow channels of adjacent upper and lower layers through a pore surface matching algorithm; S5, repeating steps S3 and S4 until the total thickness of the multi-layer pore structure reaches the target thickness of the electrode material, thereby forming an electrode pore model that meets the porosity requirements.

[0007] The volume parameters of the electrode material include the length, width and thickness of the electrode material.

[0008] The target porosity of each layer is determined according to the actual porosity distribution of the actual electrode material, or the target porosity is set according to demand.

[0009] The pore cross-sectional shape parameters include a basic geometric type constraint library, which includes at least one of a circle, a polygon and an irregular biological form.

[0010] Furthermore, the step S3 specifically includes the following steps: S3.1, setting the layer variable to n, n≥1, and randomly generating a pore cross-sectional graphic that matches the pore size parameters of the current layer in the modeling base surface of the nth layer; S3.2, stretching the two-dimensional pore cross-sectional graphic to the thickness of the layer along the thickness direction to generate a three-dimensional pore structure; S3.3, calculating the cumulative porosity of the nth layer in real time; S3.4, comparing the real-time cumulative porosity of the nth layer with the target porosity of the layer. When the difference between the cumulative porosity and the target porosity is ≤ the preset threshold, the modeling of the nth layer is ended, and the modeling of the n+1th layer is automatically performed.

[0011] Furthermore, the step S3.1 is specifically as follows: randomly generating points on the modeling base surface of the nth layer, connecting them according to the pore cross-sectional shape parameters obtained in step S2 to form cross-sectional pores with geometric shapes, and then automatically identifying whether the randomly generated cross-sectional pores are within the range of the pore size parameters according to the pore size parameters obtained in step S2, deleting the cross-sectional pores outside the size range, and retaining the cross-sectional pores within the size range to form a pore cross-sectional graph.

[0012] The positions and sizes of the cross-sectional pores are randomly generated, or the cross-sectional pores are generated at specific positions or uniformly in specific sizes as required.

[0013] Further, the specific step S3.3 is as follows: Set the initial porosity P0 of each layer to 0. For the nth layer, the target porosity of this layer is P n , and each time a pore structure is generated, the cumulative porosity P p is updated. The calculation formula for the cumulative porosity P p is as follows:

[0014]

[0015] In the formula, V sum is the cumulative volume of the pore structure of this layer, and V total is the initial total volume of this layer.

[0016] Further, the specific step S3.4 is as follows: Judge whether the cumulative porosity P p satisfies P n -P p <e, where e is a preset error threshold. If the cumulative porosity does not meet this condition, repeat steps S3.1 - S3.4 to generate a pore structure once more, thereby adding more pore structures on the basis of the pore structure generated last time; if the cumulative porosity meets this condition, end the generation of the pore structure of this layer and prepare to generate the pore structure of the next layer.

[0017] Further, the specific step S4 is as follows: After building the pore model of the (n + 1)th layer, automatically identify and calculate the contact area between the lower surface of the pore structure of this layer and the upper surface of the pore structure of the nth layer, and it can be determined whether there is contact. If there is no contact on the surfaces of the pore structures of the upper and lower layers or the contact area is lower than the preset threshold, it means that the pores of the upper and lower layers are not connected, then call the pore surface matching algorithm to readjust the pore structure of the (n + 1)th layer; if the contact area between the surfaces of the pore structures of the upper and lower layers meets the preset threshold, it means that the pores of the upper and lower layers are connected, then continue to construct the three-dimensional pore structure of the (n + 2)th layer.

[0018] Compared with the prior art, the electrolytic cell electrode pore model generated by the present invention has the characteristics of random pore distribution and unequal pore sizes, which is closer to the actual situation; the present invention ensures the connectivity between the pores of the upper and lower layers, can be effectively coupled with the large-area flow field structure, and improves the accuracy and authenticity of the model; the present invention directly generates the pore structure, avoiding the complex steps of generating the solid framework, while weakening the local sharp features of the pores, effectively improving the generation efficiency of the porous medium, greatly simplifying the numerical calculation difficulty, and effectively improving the research efficiency of two-phase flow in the porous electrode of the electrolytic cell. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a schematic flow chart of the method for generating the electrolytic cell electrode pore model of the present invention;

[0020] Figure 2 The pore cross-sectional graph generated by the present invention when the cross-sectional pore shape is circular;

[0021] Figure 3 A three-dimensional pore model generated for the present invention;

[0022] Figure 4 Schematic diagram of the coupling between the pore model generated for the present invention and the full-scale flow channel model. DETAILED DESCRIPTION

[0023] The following is a further detailed description of a method for generating an electrolytic cell electrode pore model proposed by the present invention in conjunction with the accompanying drawings and specific embodiments. According to the following description, the advantages and features of the present invention will become clearer. It should be noted that the drawings are in a very simplified form and use non-precise proportions, which are only used to conveniently and clearly assist in explaining the purpose of the embodiments of the present invention. In order to make the purposes, features and advantages of the present invention more obvious and easy to understand, please refer to the accompanying drawings. It should be noted that the structures, proportions, sizes, etc. illustrated in the drawings of this specification are only used to match the contents disclosed in the specification for people familiar with this technology to understand and read, and are not used to limit the implementation conditions of the present invention, so they have no technical substantive significance. Any structural modification, change in proportional relationship or adjustment of size, without affecting the efficacy and purpose that can be achieved by the present invention, should still fall within the scope of the technical content disclosed by the present invention.

[0024] The electrode material of a water electrolyzer is a multilayer structure, which usually includes the following functional layers: substrate layer, catalytic layer, diffusion layer, ion conduction layer, interface modification layer, etc. These functional layers are generally designed to be porous. The present invention provides a method for generating a pore model of an electrolytic cell electrode, such as Figure 1 As shown, the following steps are included:

[0025] S1. Obtain the volume parameters of the electrode material, determine the thickness of each layer and the total number of layers, and obtain the target porosity of each layer.

[0026] The volume parameters of the electrode material include the length, width and thickness of the electrode material.

[0027] The target porosity of each layer may be determined according to the actual porosity distribution of the actual electrode material, or a specific target porosity may be set according to demand.

[0028] S2. Obtain the pore cross-sectional shape parameters and pore size parameters of each layer to determine the pore structure in each layer.

[0029] The pore cross-sectional shape parameters include a basic geometric type constraint library, which includes at least one of a circle, a polygon and an irregular biological form.

[0030] The pore size parameters include parameters that determine the sizes of various geometric types and the specific value ranges of the parameters.

[0031] S3. Set the modeling base surface and perform three-dimensional pore structure construction layer by layer, specifically including the following steps:

[0032] S3.1. Set the layer variable to n, where n≥1, and randomly generate a pore cross-section graph in the modeling base of the nth layer that matches the pore size parameters of the current layer;

[0033] Specifically, points are randomly generated on the modeling base surface of the nth layer, and are connected according to the pore cross-sectional shape parameters obtained in step S2 to form cross-sectional pores with a geometric shape, wherein the positions and sizes of the cross-sectional pores are random, and then, according to the pore size parameters obtained in step S2, it is automatically identified whether the randomly generated cross-sectional pores are within the range of the pore size parameters, and the cross-sectional pores outside the size range are deleted, while the cross-sectional pores within the size range are retained, thereby forming a pore cross-sectional graph;

[0034] Optionally, in addition to generating randomly distributed and unevenly sized cross-sectional pores, you can also specify cross-sectional pores to be generated at specific locations or uniformly generated according to specific sizes as required;

[0035] S3.2. stretching the two-dimensional pore cross-section pattern along the thickness direction to the thickness of the layer to generate a three-dimensional pore structure;

[0036] The thickness of the three-dimensional pore structure is consistent with the thickness of the layer;

[0037] S3.3, calculate the cumulative porosity of the nth layer in real time;

[0038] Specifically, the initial porosity of each layer is set to P0 = 0, and for the nth layer, the target porosity of the layer is P n , each time the pore structure is generated, the cumulative porosity P is updated p , cumulative porosity P p The calculation formula is:

[0039]

[0040] Where V sum is the cumulative volume of the pore structure of this layer, V total is the initial total volume of the layer;

[0041] S3.4. Compare the cumulative porosity of the nth layer in real time with the target porosity of this layer. When the difference between the cumulative porosity and the target porosity ≤ the preset threshold, the modeling of the nth layer is ended, and the modeling of the (n + 1)th layer is automatically carried out;

[0042] Specifically, judge the cumulative porosity P p whether it satisfies P n - P p <e, where e is the preset error threshold. If the cumulative porosity does not meet this condition, repeat steps S3.1 - S3.4 to generate the pore structure once again, so as to add more pore structures on the basis of the pore structure generated last time, and then update the cumulative porosity P p ; If the cumulative porosity meets this condition, end the generation of the pore structure of this layer and prepare to generate the pore structure of the next layer.

[0043] S4. When constructing the three-dimensional pore structure of the (n + 1)th layer, repeat step S3, and ensure the connectivity of the pore network channels of adjacent upper and lower layers through the pore surface matching algorithm after the modeling of the (n + 1)th layer is completed.

[0044] Specifically, after building the pore model of the (n + 1)th layer, automatically identify and calculate the contact area between the lower surface of the pore structure of this layer and the upper surface of the pore structure of the nth layer, and it can be determined whether there is contact. If there is no contact on the surfaces of the upper and lower layer pore structures or the contact area is lower than the preset threshold, it means that the upper and lower layer pores are not connected, then call the pore surface matching algorithm to readjust the pore structure of the (n + 1)th layer; if the contact area on the surfaces of the upper and lower layer pore structures meets the preset threshold, it means that the upper and lower layer pores are connected, and then continue to construct the three-dimensional pore structure of the (n + 2)th layer.

[0045] Among them, when calling the pore surface matching algorithm to readjust the pore structure of the (n + 1)th layer, all the pore structures can be regenerated; or the part of the pores with no contact or too small contact area can be identified for local adjustment. For example, only delete the part of the pores in the (n + 1)th layer that have no contact or too small contact area with the upper surface of the pore structure of the nth layer, and read the position parameters of the pore structure generated in the nth layer to generate new pores in the non-contact area.

[0046] S5. Repeat steps S3 and S4 until the total thickness of the multi-layer pore structure reaches the target thickness of the electrode material, forming an electrode pore model that meets the porosity requirements.

[0047] S6. Optionally, verify the overall porosity of the electrode pore model, obtain the actual value and the target value of the overall porosity of the electrode pore model, and compare the two for verification to further ensure the accuracy of the model.

[0048] In a specific embodiment, the electrode material is set to a single-layer structure, the target porosity is set to 0.6, the pore shape parameter is a circular constraint library in this embodiment, and the pore size parameter is the diameter of the circle, which ranges from 0.1mm to 0.5mm. Determine the modeling base, such as Figure 2 As shown in the figure, within the specified electrode length and width range, circular pores with sizes between 0.1 mm and 0.5 mm are randomly generated. According to the description in S3.1, circular pores with sizes outside 0.1 mm to 0.5 mm have been deleted. It can be seen that within this size range, the circular pores are uneven in size and the position coordinates of the circular pores are also randomly distributed.

[0049] like Figure 3 As shown, the pore cross-section graph is stretched along the thickness direction of the layer to further generate a three-dimensional single-layer pore model.

[0050] Further, if Figure 4 As shown, the generated 3D pore model can be coupled with the full-scale flow channel model, thus resembling the actual electrolyzer structure and effectively improving computational efficiency. In subsequent fluid simulations, simply setting the interface between the 3D pore model and the full-scale flow channel model as an internal surface allows the sharing of physical field data, including fluid flow and heat transfer.

[0051] In summary, the electrolytic cell electrode pore model generation method provided by the present invention retains the characteristics of random distribution and uneven size of pores, while ensuring the connectivity between the upper and lower pore structures, greatly improving the authenticity and accuracy of the pore model; the generated pore model has a simple structure, improves the convenience of modeling, and reduces the difficulty of large-area flow field simulation.

[0052] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0053] In the description of the present invention, it should be understood that the terms "center," "height," "thickness," "up," "down," "vertical," "horizontal," "top," "bottom," "inside," "outside," "axial," "radial," "circumferential," and the like, indicating positions or location relationships, are based on the positions or location relationships shown in the accompanying drawings and are intended only to facilitate the description of the present invention and simplify the description. They do not indicate or imply that the devices or elements referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limiting the present invention. In the description of the present invention, unless otherwise specified, "plurality" means two or more.

[0054] In the description of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," "connected," and "fixed" should be understood in a broad sense. For example, they may refer to fixed or detachable connections, or integration; mechanical or electrical connections; direct or indirect connections through an intermediate medium; and internal communication between two components or interaction between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0055] In the present invention, unless otherwise expressly specified or limited, a first feature being "above" or "below" a second feature may include the first and second features being in direct contact, or may include the first and second features being in contact not directly but through another feature between them. Furthermore, a first feature being "above," "above," and "above" a second feature may include the first feature being directly above or obliquely above the second feature, or may simply mean that the first feature is higher in level than the second feature. A first feature being "below," "below," and "below" a second feature may include the first feature being directly below or obliquely below the second feature, or may simply mean that the first feature is lower in level than the second feature.

[0056] Although the present invention has been described in detail through the above preferred embodiments, it should be understood that the above description is not intended to limit the present invention. After reading the above description, various modifications and substitutions of the present invention will become apparent to those skilled in the art. Therefore, the scope of protection of the present invention should be defined by the appended claims.

Claims

1. A method for generating an electrolytic cell electrode pore model, characterized in that: The following steps are involved: S1. Obtaining the volume parameters of the electrode material, determining the thickness of each layer and the total number of layers, and obtaining the target porosity of each layer; S2. Obtaining the pore cross-sectional shape parameters and pore size parameters of each layer to determine the pore structure in each layer; S3, setting the modeling base surface, and performing three-dimensional pore structure construction layer by layer, that is, randomly generating a pore structure in the nth layer, and automatically performing modeling of the n+1th layer after ensuring that the difference between the cumulative porosity of the nth layer and the target porosity is ≤ a preset threshold; S4. When constructing the three-dimensional pore structure of the n+1th layer, repeat step S3, and after the n+1th layer modeling is completed, use the pore surface matching algorithm to ensure the connectivity of the pore network flow channels of adjacent upper and lower layers; S5. Repeat steps S3 and S4 until the total thickness of the multilayer porous structure reaches the target thickness of the electrode material, forming an electrode pore model that meets the porosity requirements.

2. The method for generating an electrolytic cell electrode pore model according to claim 1, wherein: The volume parameters of the electrode material include the length, width and thickness of the electrode material.

3. The method for generating an electrolytic cell electrode pore model according to claim 1, wherein: The target porosity of each layer is determined according to the actual porosity distribution of the actual electrode material, or the target porosity is set according to demand.

4. The method for generating an electrolytic cell electrode pore model according to claim 1, wherein: The pore cross-sectional shape parameters include a basic geometric type constraint library, which includes at least one of a circle, a polygon and an irregular biological form.

5. The method for generating an electrolytic cell electrode pore model according to claim 1, wherein: The step S3 specifically includes the following steps: S3.

1. Set the layer variable to n, where n≥1, and randomly generate a pore cross-section graph in the modeling base of the nth layer that matches the pore size parameters of the current layer; S3.

2. stretching the two-dimensional pore cross-section pattern along the thickness direction to the thickness of the layer to generate a three-dimensional pore structure; S3.3, calculate the cumulative porosity of the nth layer in real time; S3.

4. Compare the real-time cumulative porosity of the nth layer with the target porosity of the layer. When the difference between the cumulative porosity and the target porosity is less than or equal to a preset threshold, the modeling of the nth layer is terminated and the modeling of the n+1th layer is automatically performed.

6. The method for generating an electrolytic cell electrode pore model according to claim 5, wherein: The step S3.1 is specifically as follows: Points are randomly generated on the modeling base surface of the nth layer, and are connected to form cross-sectional pores with geometric shapes according to the pore cross-sectional shape parameters obtained in step S2. Then, according to the pore size parameters obtained in step S2, it is automatically identified whether the randomly generated cross-sectional pores are within the range of the pore size parameters, and the cross-sectional pores outside the size range are deleted, and the cross-sectional pores within the size range are retained to form a pore cross-sectional graph.

7. The method for generating an electrolytic cell electrode pore model according to claim 6, wherein: The positions and sizes of the cross-sectional pores are randomly generated, or the cross-sectional pores are generated at specific positions or uniformly in specific sizes as required.

8. The method for generating an electrolytic cell electrode pore model according to claim 5, wherein: The step S3.3 is specifically as follows: Set the initial porosity of each layer to P0 = 0. For the nth layer, the target porosity of the layer is P n , each time the pore structure is generated, the cumulative porosity P is updated p , cumulative porosity P p The calculation formula is: Where V sum is the cumulative volume of the pore structure of this layer, V total is the initial total volume of the layer.

9. The method for generating an electrolytic cell electrode pore model according to claim 8, wherein: The step S3.4 is specifically as follows: Judge the cumulative porosity P p Whether it satisfies P n -P p <e, where e is a preset error threshold. If the cumulative porosity does not meet this condition, repeat steps S3.1 - S3.4 to generate the pore structure one more time, thereby adding more pore structures based on the previously generated pore structure; if the cumulative porosity meets this condition, end the generation of the pore structure for this layer and prepare for the generation of the pore structure for the next layer.

10. The method for generating an electrolytic cell electrode pore model according to claim 1, wherein: The step S4 is specifically as follows: After the pore model of the n+1th layer is built, the contact area between the lower surface of the pore structure of this layer and the upper surface of the pore structure of the nth layer is automatically identified and calculated to determine whether there is contact. If the surfaces of the upper and lower pore structures have no contact or the contact area is lower than the preset threshold, it means that the upper and lower pores are not connected, and the pore surface matching algorithm is called to readjust the pore structure of the n+1th layer; if the contact area of ​​the upper and lower pore structure surfaces meets the preset threshold, it means that the upper and lower pores are connected, and the three-dimensional pore structure of the n+2th layer is constructed.

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