Three-dimensional braided composite material pore modeling method, electronic equipment and program product

Abstract

The invention discloses a three-dimensional braided composite material pore modeling method. The method comprises the following steps: establishing a solid model of a three-dimensional braided composite material constructed by a matrix and fiber bundles; establishing and selecting a fiber bundle set or a matrix set inserted into a gap according to needs; establishing a mapping relation between nodes, units and adjacent units in the fiber bundle set or the matrix set and corresponding labels of the nodes, the units and the adjacent units in the finite element analysis file; initializing the total number of deletion units, the maximum number of cycles and the minimum spacing of the pore group; randomly selecting units and surrounding units from the selected target set, and constructing a pore group; judging whether the distance between different pore groups meets the initialized minimum distance between the pores or not, and reserving the pore groups meeting the condition; and establishing a pore set based on the obtained pore group, and completing pore modeling of the three-dimensional braided composite material.

Description

Technical Field

[0001] The present invention belongs to the technical field of material analysis, and in particular relates to a pore modeling method, electronic equipment and program product for three-dimensional woven composite materials. Background Art

[0002] Resin-based woven composites have been widely used in aerospace engineering due to their resistance to delamination and customizable mechanical properties in all directions. Woven composites have the characteristics of multi-level and multi-scale, complex microstructure, and variable stress conditions. At the same time, there are a series of uncertain defects such as pores, wrinkles, and cracks. All of these will bring difficulties to the analysis of mechanical properties. Among them, pores are a common and typical defect in the molding process of woven composites. During the processing and manufacturing of composite materials, due to the irregular flow of resin and the blocking effect of fiber bundles, air and volatile gases in the closed mold are mechanically captured, resulting in pores in the resin-rich area of ​​the material. Due to factors such as the complex curing process and thermal expansion mismatch, the pore defects present the characteristics of complex geometry and random distribution.

[0003] At present, the research on pore defects mainly focuses on two aspects: the mechanism of pore generation during the preform molding process and the evolution law of pore defects during the load application process. The above studies are based on the results of real image processing to model the pores and discuss the influence of pores on the mechanical properties of the structure. In order to accurately calculate the material properties, it is necessary to study the pore defect insertion method that can reflect the real structure of the pores in the process of multi-scale modeling.

[0004] There are already literatures proposing a method of inserting pore defects in the model, that is, directly modifying the inp file and randomly selecting unit numbers to achieve random placement of pores in three-dimensional woven ceramic matrix composites. This method has the function of specifying the model porosity and "crust" thickness. However, the pore size is fixed to one unit, and the pore distribution state is randomly distributed.

[0005] Alternatively, Matlab software is used to randomly select non-repeating random numbers from the grid file exported from Abaqus, and the cells corresponding to the selected numbers are deleted to insert pores. The isolated grids are then identified and deleted through the Flood-fill / Make_consistent consistency function, and the surface grid is generated using the grid check function. A three-dimensional pore structure model that can be used for fluid mechanics software calculations was established. However, this method requires multiple exports of the grid file, which is inconvenient to operate. In addition, the pore size can only be controlled by the size of the discrete grid, which brings about the problem of poor grid quality in large pore structures.

[0006] Others divide the solid model into equal layers, randomly select two points in each layer through the probability distribution function, use these two points as the center of the upper and lower bottom surfaces to construct a cylinder, and stretch this cylinder to finally construct the pores that run through the entire layer. Insert the pore unit on each layer in turn, and then complete the insertion of the pores of the entire model. Although this method can control the pore distribution through the probability distribution function, it cannot control the distribution of pores in the direction perpendicular to the layer, and the pore size must not exceed the height of the layer. Summary of the invention

[0007] One of the embodiments of the present disclosure is a method for modeling pores in a three-dimensional woven fabric composite material with controllable size and distribution, comprising the steps of:

[0008] A1, establish a solid model of a three-dimensional woven composite material constructed of a matrix and fiber bundles;

[0009] A2, establishing and selecting a fiber bundle set or a matrix set to be inserted into the gap as required;

[0010] A3, establishing a mapping relationship between nodes, units, adjacent units in the fiber bundle set or matrix set and their corresponding labels in the finite element analysis file;

[0011] A4, initialize the total number of deleted units, the maximum number of cycles and the minimum spacing of the pore group;

[0012] A5, randomly select cells and their surrounding cells in the selected target set to construct a pore group;

[0013] A6, judging whether the distances between different pore groups meet the minimum distance between pores set by initialization, and retaining the pore groups that meet the conditions;

[0014] A7, establish a pore set based on the obtained pore group to complete the pore modeling of the three-dimensional woven composite material. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The above and other objects, features and advantages of the exemplary embodiments of the present invention will become readily understood by reading the detailed description below with reference to the accompanying drawings. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-limiting manner, in which:

[0016] Figure 1 A schematic diagram of a three-dimensional braided composite material solid model according to one embodiment of the present invention.

[0017] Figure 2 An example diagram of a method for pore modeling of a three-dimensional woven composite material according to one embodiment of the present invention.

[0018] Figure 3An example diagram of a method for pore modeling of a three-dimensional woven composite material according to one embodiment of the present invention.

[0019] Figure 4 An example diagram of a method for pore modeling of a three-dimensional woven composite material according to one embodiment of the present invention.

[0020] Figure 5 A schematic flow chart of a method for pore modeling of a three-dimensional woven composite material according to one embodiment of the present invention. DETAILED DESCRIPTION

[0021] This disclosure analyzes the existing pore defect research methods, which all have some problems, either the distribution law of the pores cannot be controlled, or the size of the pores cannot be adjusted, so it is impossible to establish a model of the real distribution law of the pores of the composite three-dimensional woven composite material. However, the local aggregation of pore defects will cause stress concentration, produce weak points, and affect the mechanical properties of the woven composite material. Therefore, the purpose of this disclosure is to realize a pore insertion method with controllable pore size and distribution.

[0022] According to one or more embodiments, a method for modeling pores in a three-dimensional woven fabric composite material with controllable size and distribution:

[0023] Step 1: Based on the open source software TexGen, a Python script is used to build a 3D woven composite material solid model. Figure 1 The figure shows a three-dimensional woven composite solid model. The principle here is to use nodes to determine the position of important sections, give the sections a specific shape, and connect the sections into yarns, which is the process of point-surface-line. First, define the three main geometric features of the model: main nodes, yarn trajectories, and yarn cross-sectional shapes. In TexGen, the main nodes of the yarn are defined by functions. Subsequently, at each main node, the cross-sectional shape and rotation angle are determined according to the yarn cross-sectional parameters. Assuming that the yarn trajectory between the nodes is a straight line, each section is connected into a yarn by linear interpolation. Use the repeats statement to construct a periodically repeated structure of the yarn. Use the domain statement to select the unit cell range and apply the matrix. The linear reduced integration unit C3D8R is used for discretization. Here, the discrete unit size does not have to be consistent with the pore size, and only the mesh quality and calculation accuracy need to be guaranteed. This step establishes a periodically repeated solid model of a three-dimensional woven composite material.

[0024] The TexGen open source software used here is mainly used for geometric modeling and simulation of textile structures. Its main functions include: textile structure modeling, various simulations and analyses, and exporting the generated models to other tools for further analysis and simulation. It is widely used in the research, design and analysis of textile composite materials.

[0025] Step 2, select the components and collections where pores need to be inserted. Pores are divided into dry spots in fiber bundles and pores in the matrix between fiber bundles, so sets are established for the units in fiber bundles and matrix respectively. To insert dry spots, select the fiber bundle collection, and to insert matrix pores, select the matrix collection. This step can realize the insertion of pores at any position of the 3D woven composite model.

[0026] Step 3, establish the mapping relationship between the nodes, elements, adjacent elements in the selected set and their corresponding labels in the inp file. There are no digital labels on the solid model, so mathematical operations cannot be performed, and naturally random numbers cannot be selected, so it is necessary to give the solid model digital features. In the inp file, each element and node has a corresponding digital label. There is no need to extract the inp file, and you can directly use the Python script to process it. A unit has a unit number, corresponding to 8 node numbers, and shares nodes with its adjacent units to establish a one-to-one mapping relationship between the number and the solid model. This step gives the solid unit digital features, making mathematical processing possible. The inp file here is usually used as an input file for finite element analysis.

[0027] Step 4: Initialize the total number of deleted units, the maximum number of loops, and the minimum spacing between pore groups. Calculate the total number of deleted units based on the porosity and the selected set. When the total number of deleted units is reached, the program stops looping. Set a reasonable maximum number of loops. When the target porosity cannot be achieved, terminate the program in time to avoid wasting computing resources. Set the minimum spacing between pore groups, such as Figure 2 As shown in the figure, the smaller the minimum distance between pore groups, the more likely it is that pores will aggregate in space. By controlling the distance between pore groups, local pore aggregation is achieved. This step does not use a distribution function to control the specific distribution of pores, so while retaining the randomness of pore distribution, the modeling of local aggregation of pores in three-dimensional space is achieved.

[0028] Step 5: Randomly select a unit and its surrounding units in the target set to construct a pore group. First, randomly select a pore unit to ensure the randomness of the pore position distribution. Randomly select a node of this unit, and select the adjacent units of this unit by confirming the shared nodes. This unit and the adjacent units together form a pore group. The pore becomes larger by selecting more adjacent units, thus realizing the regulation of pore size. Figure 3 As shown. This solves the problem of insufficient model calculation accuracy or waste of computing resources when the unit size is equal to the pore size. In addition, multiple pore units constitute a pore group, and regulating the position of adjacent units makes it possible to regulate the pore shape. This step realizes the regulation of pore size and shape.

[0029] Step 6: Determine whether the distance between different pore groups meets the minimum distance between pores set by initialization, and retain the pore groups that meet the conditions. After removing the units of the generated pore groups, update the remaining available units. Continuously generate new pore groups. When the number of units in the generated pore groups meets the total number of deleted units, stop the loop. Figure 4 As shown, the distance between the pore groups is too large. After many attempts, the target porosity cannot be achieved. It is also stopped when the number of cycles reaches the maximum number of cycles. This step is to determine whether the cycle has stopped and terminate the program. Step 7, create a set Set-Voids for the generated pore groups, and assign section attributes to this set. In order to ensure the convergence of the calculation, the attributes of the pore unit are usually assigned a very small positive value, called the "0 stiffness" unit. The reason is that after the unit position is selected, the selected unit needs to be assigned attributes to facilitate subsequent finite element calculations. In the general understanding, pores mean nothing, that is, the unit is completely deleted. However, in order to avoid mesh distortion in finite element calculations, which in turn affects the convergence of the calculation. Choose not to delete the unit, but assign the unit extremely small mechanical parameters, such as assigning the elastic modulus E11 to 10-6MPa, and approximate the unit to a deleted hole, named "0 stiffness unit".

[0030] Through the above steps, the embodiment of the present disclosure realizes parameterized pore modeling with controllable size and distribution.

[0031] According to one or more embodiments, a method for modeling pores in a three-dimensional woven fabric composite material is provided. Figure 1 As shown, a solid model of a three-dimensional woven composite material is shown, which is created by the open source software TexGen and Python script. The solid model contains a matrix and a fiber bundle, describing the structure and composition of the composite material. The matrix (Matrix) is used to surround and support the fiber bundle, providing the overall shape and structure of the composite material. The fiber bundle is a collection of many fibers, which are arranged along a specific path to provide the strength and stiffness of the composite material. The fiber bundles of different colors in the figure may represent different fiber types or directions. The colored structure shown in the figure represents the three-dimensional weaving pattern of the fiber bundles in the matrix. This weaving pattern ensures that the composite material has excellent mechanical properties in different directions. And because the structure is repeated periodically, this means that the entire composite material can be regarded as composed of many identical units (unit cells) repeatedly arranged. At the same time, the model structure is discretized using the C3D8R unit, which is a linear reduced integration unit used to simulate solid models in finite element analysis. The size of the discrete unit does not have to be consistent with the pore size, but the mesh quality and calculation accuracy need to be guaranteed. By, Figure 1A periodically repeating solid model of a 3D woven composite material, in which fiber bundles are arranged in a specific weave pattern in the matrix, is prepared for further analysis, such as mechanical properties, through discretization techniques.

[0032] like Figure 2 As shown in the figure, it shows two different distance settings between pore groups, namely "small pore group distance" and "large pore group distance". Each circle in the figure represents a pore group, and the shaded part inside the circle may represent the specific pore position within the pore group. The distance between the circles represents the spatial relationship between different pore groups. Figure 2 In the left figure, several pore groups are shown, and the distances between them are relatively small. This setting may lead to the local aggregation of pores in space, because the distances between pore groups are small, which increases the possibility of pores being close to each other. Figure 2 In the right figure, the distance between pore groups is significantly increased. This setting helps to reduce the local aggregation of pores because the distance between pore groups is larger and the pore distribution is more dispersed.

[0033] By controlling the distance between pore groups, local aggregation modeling of pores in three-dimensional space can be achieved while retaining the randomness of pore distribution. This means that by adjusting the minimum distance between pore groups, the distribution pattern of pores can be controlled to a certain extent, thereby affecting the physical properties of the material, such as permeability, strength, etc. In addition, the parameters "total number of deleted units", "maximum number of cycles" and "minimum spacing of pore groups" may be used in the simulation or calculation process to ensure that the target value of porosity can be achieved while avoiding unnecessary waste of computing resources. By setting a reasonable maximum number of cycles, the program can be terminated in time when the target porosity cannot be achieved, thereby improving the calculation efficiency.

[0034] like Figure 3 As shown, a series of pore groups composed of basic units are constructed by randomly selecting units and their surrounding units. Figure 3 It explains how to achieve precise control over the pore structure of a material by regulating the size and shape of the pore groups when constructing the pore structure. Figure 3Multiple pore groups are shown, each of which is constructed by randomly selecting a basic unit. This random selection method ensures that the distribution of pore positions is random, thereby simulating the natural randomness of pore distribution in natural materials. By selecting a node of a basic unit and selecting adjacent units by confirming the method of common nodes, pore groups of different sizes can be constructed, which also shows that the pore size can be regulated by selecting more adjacent units. Multiple pore units constitute a pore group. By regulating the positions of adjacent units, the pore shape can be regulated, which shows that the pore shape can be diversified by adjusting the arrangement of adjacent units. The pore group construction method of the embodiment of the present disclosure solves the problem of insufficient model calculation accuracy or waste of computing resources that may occur when the unit size is equal to the pore size. By constructing pore groups of different sizes and shapes, unnecessary consumption of computing resources can be reduced while ensuring the calculation accuracy. At the same time, by constructing pore groups, an effective means is provided for simulating the pore structure of materials. By precisely controlling the size and shape of the pores, the physical and chemical properties of the material can be better simulated and predicted, thereby optimizing the material design and performance.

[0035] like Figure 4 The figure shows a schematic diagram of the simulation pore structure generation process, in which the red circles represent the generated pore groups, each of which consists of one or more units. The patterns contained in the boxes in the figure may represent the central units of the pore groups or specific pore features. The figure shows that when generating pore groups, the minimum distance requirements between pore groups need to be considered. Specifically, the distance between the pore groups in the figure is too large, which means that the predetermined porosity target cannot be achieved under the current pore group configuration. Therefore, it is necessary to adjust the position or size of the pore group, or generate a new pore group, in order to try to meet the porosity requirements. The pore group generation process follows the following steps:

[0036] S401, initialization setting - setting the minimum distance between pores and the target porosity.

[0037] S402, random selection - randomly select a pore unit and ensure the randomness of its position distribution.

[0038] S403, construct pore groups - construct pore groups by selecting adjacent units, and adjust the pore size and shape. S404, distance judgment - judge whether the distance between different pore groups meets the minimum distance between pores set by initialization, and retain the pore groups that meet the conditions.

[0039] S405, update unit - after eliminating the units that have generated pore groups, update the remaining available units.

[0040] S406, loop generation - continuously generating new pore groups until the number of units in the generated pore groups meets the total number of deleted units, or the maximum number of loops is reached.

[0041] According to one or more embodiments, Figure 5 As shown, a pore modeling method for three-dimensional woven composite materials based on TexGen software is provided. The method realizes accurate modeling of pores in composite materials by controlling the size, shape and distribution of pores. The method comprises the following steps:

[0042] S501, build a solid model based on TexGen, define the main geometric features of the model, including main nodes, yarn cross-sections and yarn trajectories, and use TexGen software and Python scripts to build a solid model of a three-dimensional woven composite material.

[0043] S502, obtaining models and sets, obtaining the required model sets from the established models, including unit-to-unit labels, node-to-node labels, and adjacent unit-to-adjacent unit labels.

[0044] S503, establish a mapping, establish a mapping relationship between nodes, units and adjacent units in the model and corresponding labels in the inp file, so as to perform mathematical operations.

[0045] S504, initializing parameters, initializing parameters such as the total number of deleted units, the maximum number of cycles, and the minimum spacing between pore groups.

[0046] S505, randomly select a unit, randomly select a unit from the model as the starting point of the pore, and set the maximum number of cycles.

[0047] S506, selecting n adjacent units to construct a pore group, and selecting n adjacent units of the unit to jointly form a pore group.

[0048] S507: For the pore group distance < the minimum distance between groups, a judgment is made to check whether the distance between the pore groups is less than the minimum distance between groups set initially.

[0049] If yes, then update the available cells and continue to build new pore groups.

[0050] If not, delete the pore group and reselect the element.

[0051] S508, check whether the maximum number of cycles has been reached,

[0052] If yes, check whether the total number of deleted units meets the requirement. If not, subtract 1 from the minimum spacing of the pore group, assign the new minimum spacing of the pore group to step S504, and continue the loop calculation.

[0053] If the maximum number of loops is not reached, the number of loops is increased by 1, and the process proceeds to step S506.

[0054] S509, when the total number of deleted units meets the requirements, a Set-Voids set is created and section attributes are assigned. Usually, the attributes of the void unit are assigned a very small positive value, which is called a "0 stiffness" unit.

[0055] S510, completing the pore modeling process and ending the program.

[0056] Through the above steps, this technical solution realizes the accurate modeling of pores in three-dimensional woven composite materials, and can control the size, shape and distribution of pores to meet the needs of different application scenarios.

[0057] In summary, the technical effects of the present disclosure are further explained as follows:

[0058] 1. In the existing technology, there are many problems in using randomly selected unit sizes to represent pore sizes. On the one hand, the unit size must match the pore size. If the unit size is too large, the calculation result will be rough, and if the unit size is too small, the calculation resources will be wasted. On the other hand, in a three-dimensional woven composite preform, the pore sizes are not the same, and using a single unit to represent the pores cannot reflect the diversity of pore sizes and shapes. In the present disclosure, units clustered together constitute a unit group, and the unit group is used to describe real pores with different sizes and shapes. When the pores are large, more units are used to form a pore group. The pore modeling method of the present disclosure can not only ensure that the appropriate grid size is selected when the overall model is discretized, but also ensure the true establishment of the pore model.

[0059] 2. In the existing technology, there are many problems in using random functions or probability distribution functions to select randomly distributed pores. Although the pore distribution in woven composite materials has certain random characteristics, due to reasons such as fiber interlacing, the pores will still be locally aggregated, and the random function cannot describe the distribution characteristics of local pore aggregation. The solid model is divided into multiple layers, and the probability distribution function is used to insert the pores in each layer. Although this method gives the pores a certain distribution law, it cannot control the distribution of pores in the direction perpendicular to the layer, and cannot achieve the modeling of pore aggregation in three-dimensional space. The present disclosure controls the distribution of pore groups in three-dimensional space by adjusting the minimum distance between pore groups. Because the distribution function is not used to control the specific distribution of the pores, the modeling of local aggregation of pores in three-dimensional space is achieved while retaining the randomness of the pore distribution.

[0060] 3. In the existing technology, random numbers are selected in the exported inp file or grid file. The import and export of data tables is very troublesome, and it is also necessary to manually identify the position of the unit and node numbers in the file. The embodiment of the present disclosure is based on Python scripts, which establish the mapping relationship between nodes, units, adjacent units and their corresponding labels. It can be directly run in ABAQUS to realize the insertion of pore groups, which is convenient and fast.

[0061] It should be understood that in the embodiments of the present invention, the term "and / or" is only a description of the association relationship of the associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0062] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, or it can be an electrical, mechanical or other form of connection.

[0063] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0064] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for pore modeling of a three-dimensional woven composite material, characterized in that: The following steps are involved: A1, establish a solid model of a three-dimensional woven composite material constructed of a matrix and fiber bundles; A2, establishing and selecting a fiber bundle set or a matrix set to be inserted into the gap as required; A3, establishing a mapping relationship between nodes, units, adjacent units in the fiber bundle set or matrix set and their corresponding labels in the finite element analysis file; A4, initialize the total number of deleted units, the maximum number of cycles and the minimum spacing of the pore group; A5, randomly select cells and their surrounding cells in the selected target set to construct a pore group; A6, judging whether the distances between different pore groups meet the minimum distance between pores set by initialization, and retaining the pore groups that meet the conditions; A7, establish a pore set based on the obtained pore group to complete the pore modeling of the three-dimensional woven composite material.

2. The method according to claim 1, characterized in that: In step A1, the definition of the solid model includes main nodes, yarn trajectories, and yarn cross-sectional shapes.

3. The method according to claim 1, characterized in that In step A5, it includes first randomly selecting a pore unit, randomly selecting a node of the pore unit, and selecting the adjacent unit of the unit by confirming the common node. The unit and the adjacent unit together constitute a pore group.

4. The method according to claim 3, characterized in that Repeat the loop step A6 to continuously generate new pore groups until the number of units in the generated pore groups meets the total number of deleted units, or the number of loops reaches the maximum number of loops.

5. The method according to claim 1, characterized in that In step A7, a cross-sectional attribute is assigned to the pore set.

6. The method according to claim 2, characterized in that The main nodes of the yarn are defined by functions. At each main node, the cross-sectional shape and rotation angle are determined according to the yarn cross-sectional parameters. Assuming that the yarn trajectory between the nodes is a straight line, the cross-sections are connected into yarns through linear interpolation.

7. The method according to claim 6, characterized in that The solid model is discretized using a linear reduced integration unit.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: The processor runs the computer program to implement the method according to any one of claims 1 to 7.

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

10. A computer program product, comprising a computer program, characterized in that The computer program is executed by a processor to implement the method according to any one of claims 1 to 7.

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