Heterogeneous concrete automatic modeling method based on topological disordered six-way connection grid

Abstract

The invention relates to the technical field of concrete modeling, in particular to an automatic heterogeneous concrete modeling method based on topological disordered six-way connection grids, which comprises the following steps of: dividing a concrete test piece into a plurality of layers of slices, and establishing a unit cell grid in each layer of slice to form a three-dimensional unit cell network structure; generating random nodes in each unit cell based on a set random degree parameter, and performing minimum distance check on the distance between the nodes to form a random node set; carrying out six-direction connection on the random nodes in each unit cell and the nodes in the adjacent unit cells, and constructing a topological disordered three-dimensional lattice unit network; and generating a material property state matrix according to the two-dimensional numerical value picture of each layer of sheet, and performing material property assignment on the three-dimensional lattice unit network to complete automatic modeling of the concrete model. According to the technical scheme, different structural characteristic requirements of the concrete test piece can be met, and the damage development process of the concrete test piece in any shape can be efficiently simulated and analyzed in batches.

Description

Technical Field

[0001] The present invention relates to the technical field of concrete modeling, and in particular to an automatic modeling method for heterogeneous concrete based on a topologically disordered six-way connected grid. Background Art

[0002] With the development of computer technology, numerical simulation methods have been widely used to analyze the damage and failure process of concrete. Given the significant heterogeneity of concrete, a reasonable modeling approach is key to effectively analyzing the damage and failure process of concrete. Rough macroscopic models often cannot restore the heterogeneous characteristics of concrete, resulting in simulation results that deviate significantly from the actual situation. Fine and microscopic models that can restore the heterogeneous distribution characteristics of concrete often mean a significant increase in modeling complexity, and the simulation results are affected by individual microscopic characteristics and cannot represent the overall general situation of the simulated object. Therefore, in order to better simulate the damage and failure process of concrete, how to balance the restoration of the overall heterogeneous characteristics of concrete and the modeling complexity has become a technical problem that needs to be solved urgently.

[0003] Chinese patent application CN202311061350.4 discloses a modeling method for numerical simulation of tunnel concrete crack damage characteristics. The method establishes a tunnel geometric model, determines the location of the crack damage area in the model and obtains the corresponding geometric set; meshes the tunnel geometric model to obtain mesh models of each area in the tunnel geometric model, and determines the concrete damage unit set in the mesh model based on the geometric set corresponding to the crack damage area; sets the operating parameters of the unit deletion script in the numerical simulation software based on the tunnel geometric model, the tunnel mesh model and the concrete damage unit set, and deletes the corresponding unit when the set mechanical degree is reached. However, this existing technology has the following shortcomings: the location of the crack damage area needs to be manually determined in advance, and the non-homogeneous characteristic distribution of concrete cannot be automatically identified and simulated; the unit deletion method is relatively crude, which may affect the stability and accuracy of the numerical calculation; it is mainly targeted at specific structural forms such as tunnels, and has limited applicability to modeling concrete specimens of arbitrary shapes; the modeling process requires manual setting of many parameters, the degree of automation is not high, and it is difficult to achieve efficient batch simulation analysis. Summary of the Invention

[0004] In view of this, and in response to the shortcomings of existing concrete numerical modeling methods, the present invention proposes an automatic modeling method for heterogeneous concrete based on a topologically disordered six-way connected grid. Through this method, a concrete macro model can be established to quantitatively simulate the heterogeneous characteristics of concrete from the perspective of macroscopic topological disorder. At the same time, it can also meet the different structural characteristics requirements of the specimens and perform efficient batch simulation analysis on the damage and destruction development process of concrete specimens of arbitrary shapes.

[0005] The technical solution of the present invention is achieved as follows: The present invention provides a method for automatically modeling heterogeneous concrete based on a topologically disordered six-way connected grid, comprising the following steps:

[0006] S1. Divide the concrete specimen into several thin slices, establish a unit cell grid in each thin slice, and form a three-dimensional unit cell network structure;

[0007] S2. Based on the set randomness parameter, random nodes are generated in each cell, and the minimum distance between nodes is checked to form a random node set;

[0008] S3, connecting random nodes in each unit cell with nodes in adjacent units in six directions to construct a topologically disordered three-dimensional lattice unit network;

[0009] S4. Generate a material property state matrix based on the two-dimensional numerical images of each layer of thin slices, assign material properties to the three-dimensional lattice unit network, and complete the automatic modeling of the concrete model.

[0010] On the basis of the above technical solution, preferably, in step S1, the unit length x in the X, Y, and Z directions of the single cell grid is selected according to the structural characteristics of the concrete specimen in the X, Y, and Z directions. e 、y e 、z e , the unit length of the unit cell grid is selected to meet the following conditions:

[0011] z between each layer e and x at different plane positions in the same layer e 、y e They may not be exactly the same, but the z of different areas in the same layer e Must be the same, x in the same area between layers e 、y e Must be the same.

[0012] Based on the above technical solution, preferably, step S2 specifically includes:

[0013] S21. Generate a subcell in each cell, establish a local rectangular coordinate system for each subcell, set the randomness, and generate the local coordinates of random nodes in the subcell through a random function;

[0014] S22, converting the random node coordinates in the local coordinate system into coordinate values ​​in the global coordinate system according to the sequential index values ​​of each sub-unit cell in the current thin layer;

[0015] S23. During the node generation process, the minimum distance between the newly generated node and the old node in the X, Y, and Z directions is checked. If the minimum distance requirement is not met, the node coordinates are regenerated.

[0016] S24. Store the generated coordinates of each random node in a coordinate matrix according to the node generation order, and finally form a node set including all random nodes.

[0017] Based on the above technical solution, preferably, the node coordinate conversion calculation method between the local coordinate system and the global coordinate system is as follows:

[0018]

[0019]

[0020] Where x e 、y e 、z e are the unit lengths of the cell grid in the X, Y, and Z directions, respectively; i is the row index, j is the column index, and k is the slice layer index; x0(i,j,k), y0(i,j,k), and z0(i,j,k) are the X, Y, and Z coordinates of the random node corresponding to the current index (i,j,k) in the local coordinate system of the subcell; and x(i,j,k), y(i,j,k), and z(i,j,k) are the X, Y, and Z coordinates of the random node corresponding to the current index (i,j,k) in the global coordinate system; ∑y e (i) is the sum of the lengths of the cells in the Y direction from the 1st row to the i-th row, ∑x e (j) is the sum of the lengths of the cells in the X direction from the 1st column to the jth column, ∑z e (k) is the sum of the lengths of the cells in the Z direction from the 1st layer to the kth layer; rand(1) generates a random number between 0 and 1, and random is the degree of randomness.

[0021] On the basis of the above technical solution, preferably, in step S23, the minimum distance check includes: based on the divided three-dimensional cubic cell network, performing a distance check between the new node generated in each cell and the old nodes in the neighborhood of the cell, wherein the neighborhood is composed of all cells that share edges or corner points with the cell in the X, Y, and Z directions.

[0022] Based on the above technical solution, preferably, step S3 specifically includes:

[0023] Connect a single node in each unit cell with adjacent nodes in three main directions on three main planes to form a six-directional lattice unit local network of a single node, forming a topologically disordered three-dimensional lattice unit network, and store the midpoint coordinates of each unit in each direction in a matrix according to the connection order;

[0024] Three main planes include XY plane, XZ plane and YZ plane, three main directions include horizontal direction, vertical direction and oblique direction, and the six-direction lattice unit local area network of a single node includes XX, YY, ZZ, XY, XZ and YZ six-direction units.

[0025] On the basis of the above technical scheme, preferably, the midpoint coordinates of each unit in each direction are stored in the matrix according to the connection sequence, specifically including: obtaining the index of the other end node according to the current node index and the position relationship with the other end node, obtaining the node coordinates from the random node coordinate matrix according to the index, obtaining the unit midpoint coordinates by taking the average of the two node coordinates, and storing the midpoint coordinates of the units in each direction in the matrix according to the unit generation sequence.

[0026] On the basis of the above technical scheme, preferably, in step S4, the material state matrix is generated according to the two-dimensional numerical picture of each layer of sheet, specifically including: obtaining the two-dimensional numerical picture representing the structural characteristics of each layer of sheet, generating the corresponding node network material state matrix according to the two-dimensional numerical picture, and further generating the three-dimensional lattice unit network material state matrix.

[0027] On the basis of the above technical scheme, preferably, the generation of the node network material state matrix includes:

[0028] The RGB image processing is performed on the two-dimensional numerical picture to make each color threshold clear to correspond to different materials;

[0029] The picture pixel size is set to be equal to the number of cell grids in the current layer, the RGB value array of all pixels is extracted, and the array is assembled into a matrix according to the cell generation sequence index to represent the corresponding RGB value of each cell in the cell network of the current sheet;

[0030] According to the RGB value, the material type corresponding to each node is determined, and the node network material state matrix is generated.

[0031] On the basis of the above technical scheme, preferably, the three-dimensional lattice unit network material state matrix generation method includes:

[0032] For each node in the node network material state matrix, the material value of the node in the node network state matrix in the neighborhood is searched according to the index value corresponding to the position relationship of the node, the material category corresponding to the lattice unit formed by connecting the current node and the adjacent node is determined according to the material state and position relationship of the current node and the adjacent node, and the matrix form is stored.

[0033] The automatic modeling method of heterogeneous concrete based on the topological disordered six-direction connection grid of the application has the following beneficial effects compared with the prior art:

[0034] The present invention is based on discrete element simulation technology and concrete material science, taking into account the modeling and calculation efficiency of concrete heterogeneity, the universality of simulation results in practical applications, irregular shape specimen requirements, composite material (such as reinforced concrete) specimen requirements, and designs an integrated arbitrary shape concrete macro-heterogeneous modeling method. This method can be used to achieve the automatic generation of macro-heterogeneous concrete models, while improving modeling and calculation efficiency while simulating the heterogeneity of macro-concrete interior with the topological disorder determined by randomness. This method can establish a more practical and efficient macro-model for calculation, and also provides convenience for batch numerical simulation. The macro-concrete model established by this method is very suitable for simulating the mechanical response of large concrete specimens. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0036] Figure 1 A flowchart of the method for automatic modeling of heterogeneous concrete based on a topologically disordered six-way connected grid according to the present invention;

[0037] Figure 2 Schematic diagram of establishing a unit cell grid for a plate-shaped concrete specimen of the present invention;

[0038] Figure 3 A schematic diagram of the parameters related to the randomness definition of the present invention;

[0039] Figure 4 This is a minimum distance check flow chart of the present invention;

[0040] Figure 5 A schematic diagram of a random node set and its index according to the present invention;

[0041] Figure 6 Schematic diagram of the construction of the topologically disordered three-dimensional lattice unit network of the present invention;

[0042] Figure 7 A concrete macro-lattice model constructed according to the technical solution of the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0044] like Figure 1 As shown, the present invention provides a method for automatically modeling heterogeneous concrete based on a topologically disordered six-way connected grid, comprising the following steps:

[0045] S1. Divide the concrete specimen into several thin slices, establish a unit cell grid in each thin slice, and form a three-dimensional unit cell network structure;

[0046] S2. Based on the set randomness parameter, random nodes are generated in each cell, and the minimum distance between nodes is checked to form a random node set;

[0047] S3, connecting random nodes in each unit cell with nodes in adjacent units in six directions to construct a topologically disordered three-dimensional lattice unit network;

[0048] S4. Generate a material property state matrix based on the two-dimensional numerical images of each layer of thin slices, assign material properties to the three-dimensional lattice unit network, and complete the automatic modeling of the concrete model.

[0049] The present invention divides the concrete specimen layer by layer into thin unit cell grids, generates random nodes in each unit cell based on a random degree parameter, connects the random nodes in six main directions to form a topologically disordered three-dimensional lattice unit network, and then automatically identifies and assigns the unit material property state through two-dimensional numerical images of each layer of the specimen, thereby realizing an automatic modeling method for quantitatively simulating the heterogeneous characteristics of concrete from macroscopic topological disorder. The entire modeling process uses the sequential index generated by nodes and units to achieve efficient geometric positioning and material property assignment, avoiding the complex search and judgment process in traditional methods. At the same time, the topological disorder controlled by the random degree parameter can simulate the internal heterogeneity of concrete and avoid the influence of individual characteristics in the microscopic model on the overall result, thereby significantly improving the modeling and calculation efficiency while ensuring the modeling accuracy, realizing the automatic generation of concrete macroscopic models, and is particularly suitable for efficient batch simulation analysis of the damage and destruction development process of concrete specimens of arbitrary shapes, providing an effective technical solution for the mechanical response simulation of large concrete specimens.

[0050] Furthermore, in step S1, the unit length z in the Z direction of the unit cell grid is selected according to the structural characteristics of the specimen in the Z direction. e , the specimen is divided into h layers along the Z direction, and the unit length x in the X and Y directions of the unit cell grid is selected according to the structural characteristics of the specimen in the X and Y directions.e 、y e , in each layer of the sheet, the unit cell grid unit length of the layer is divided into m×n three-dimensional cubic unit cell networks, such as Figure 2 As shown, Figure 2 The middle left picture shows the plate-shaped concrete specimen and its z e Schematic diagram. The right figure is a schematic diagram of the unit cell grid details of the k0th layer of thin film.

[0051] In order to meet the needs of irregular specimen shapes, the unit length of the unit cell grid is selected to meet the following conditions: the z between each layer is e and x at different plane positions in the same layer e 、y e They may not be exactly the same, but the z of different areas in the same layer e Must be the same, x in the same area between layers e 、y e must be the same, that is, the cell grids of each layer must correspond to each other. That is, for the cell at index (i, j) in the adjacent k0th and k1th layers, it is allowed But must meet:

[0052] Furthermore, step S2 specifically includes:

[0053] S21. Generate a sub-cell in each cell, establish a local rectangular coordinate system for each sub-cell, set the randomness, and generate the local coordinates of random nodes in the sub-cell through a random function.

[0054] S22. According to the sequential index values ​​of each sub-unit cell in the current thin layer, the random node coordinates in the local coordinate system are converted into coordinate values ​​in the global coordinate system.

[0055] Specifically, if Figure 3 As shown, Figure 3 The figure shows the parameters related to the definition of randomness. The randomness is the ratio of the sub-cell side length to the cell side length in the X, Y, and Z directions, indicating the maximum range of random distribution of nodes within the cell. The randomness is calculated as follows:

[0056]

[0057] In the formula, random is the degree of randomness, L sub-cell,x 、L sub-cell,y 、L sub-cell,z are the X, Y, and Z side lengths of the subcell, L cell,x 、L cell,y 、L cell,z are the X, Y, and Z side lengths of the unit cell, respectively.

[0058] The random node coordinate generation method is: establish a local rectangular coordinate system O'x'y'z' for each sub-unit cell, such as Figure 2 As shown in the figure on the right, under a specific degree of randomness, the coordinates of the random nodes in the sub-unit cell at the i-th row and j-th column in the k-th thin layer are generated by the rand function in MATLAB software. The coordinates of the random nodes in the local coordinate system are:

[0059]

[0060] Establish the overall rectangular coordinate system Oxyz at the lower left corner of the specimen, such as Figure 2 As shown in the left figure, the random node coordinates in the local coordinate system are converted into coordinate values ​​in the global coordinate system according to their sequential index values ​​in the current thin layer:

[0061]

[0062] Where x e 、y e 、z e are the unit lengths of the cell grid in the X, Y, and Z directions, respectively; i is the row index, j is the column index, and k is the slice layer index; x0(i,j,k), y0(i,j,k), and z0(i,j,k) are the X, Y, and Z coordinates of the random node corresponding to the current index (i,j,k) in the local coordinate system of the subcell; x(i,j,k), y(i,j,k), and z(i,j,k) are the X, Y, and Z coordinates of the random node corresponding to the current index (i,j,k) in the global coordinate system; ∑y e (i) is the sum of the lengths of the cells in the Y direction from the 1st row to the i-th row, ∑x e (j) is the sum of the lengths of the cells in the X direction from the 1st column to the jth column, ∑z e (k) is the sum of the lengths of the cells in the Z direction from the 1st layer to the kth layer; rand(1) generates a random number between 0 and 1, and random is the degree of randomness.

[0063] The coordinates of each random node are stored in a matrix according to the node generation order, and each matrix element is the three-dimensional coordinate (x, y, z) of a node.

[0064] S23. During the node generation process, the minimum distance between the newly generated node and the old node in the X, Y, and Z directions is checked. If the minimum distance requirement is not met, the node coordinates are regenerated.

[0065] Each time a new node with an index value of (i, j, k) is generated, the neighborhood index value is obtained according to the position relationship, the coordinates of the old node in the positioning matrix are located, and the distance between the new and old nodes is checked. If the minimum distance requirement is not met, the new node is regenerated. If it is met, the next new node is generated.

[0066] The minimum distance check includes: based on the divided three-dimensional cubic cell network, a distance check is performed between the new nodes generated in each cell and the old nodes in the neighborhood of the cell, where the neighborhood consists of all cells that share edges or corners with the cell in the X, Y, and Z directions.

[0067] The minimum distance check method can determine the number and coordinate information of old nodes in its neighborhood based on the node index value. If the new node does not meet the requirements, it only needs to adjust the coordinates of the new node, eliminating a large amount of repeated search and check work. For example, for the cell in the i-th row and j-th column of the k-th layer, the old nodes in its neighborhood cells can be searched and located based on the sequential index value (i, j, k) of the cell. Therefore, for each new node, the number of searches for the minimum distance check is determined by its index value. The maximum complexity of the algorithm is O(26) based on the generated sequential index to locate the neighborhood node information, avoiding the more expensive old domain search (complexity of O(i×j×k-1)), that is, searching and checking the minimum distance of all old nodes generated before the new node, and avoiding the more expensive full domain search (complexity of O(m×n×h-1)), that is, checking the minimum distance of all remaining nodes.

[0068] Specifically, if Figure 4As shown, the minimum distance check process of this embodiment adopts a three-layer nested loop structure, and the inspection order is j=1:n (number of columns), i=1:m (number of rows), k=1:h (number of slice layers), and each cell position is processed one by one. For the current index (i, j, k) position, a new cell and the corresponding random node coordinates (x, y, z) are first generated. Next, it is determined whether the current cell is located at the boundary position, that is, i=1 or m, j=1 or n, k=1 or h. The adjacent cell search range is determined based on the judgment result: if it is a boundary cell, the search number S is determined according to its specific position; if it is an internal cell, all 26 neighboring cells around it are searched (that is, S=26). Then, the adjacent search loop is entered, and the adjacent indexes are calculated one by one according to the corresponding relationship between the cell position and the index, the corresponding node coordinates are obtained from the coordinate matrix, the distance between the current newly generated node and each adjacent node is calculated, and it is determined whether the distance is ≥ the set minimum distance. If yes, the next neighbor node is checked; if not, a new random node corresponding to the current index is generated and the minimum distance check process for that location is restarted. When the distance checks for all neighboring nodes pass, the coordinates of the current random node are stored in the coordinate matrix according to the index, and the process proceeds to the next unit cell position until the minimum distance check for all units is completed.

[0069] S24. Store the generated random node coordinates in the coordinate matrix in the order of node generation, and finally form a node set containing all random nodes (i.e., m×n×h points) and their coordinate matrix. The matrix index corresponds to the node position, such as Figure 5 shown.

[0070] Furthermore, step S3 specifically includes:

[0071] The single node in each unit cell is connected with the adjacent nodes in the three main directions on the three main planes to form a six-directional lattice unit local network of the single node, and then a topologically disordered three-dimensional lattice unit network is formed. The midpoint coordinates of each unit in each direction are stored in the matrix according to the connection order.

[0072] Among them, the three main planes include XY plane, XZ plane, and YZ plane, the three main directions include horizontal, vertical, and oblique directions, and the six-directional lattice unit local network of a single node includes six directional units: XX, YY, ZZ, XY, XZ, and YZ.

[0073] Specifically, the midpoint coordinates of each unit in each direction are stored in a matrix according to the connection order, specifically including: obtaining the index of the other end node according to the current node index and its positional relationship with the other end node, obtaining the node coordinates from the random node coordinate matrix according to the index, taking the mean of the two node coordinates to obtain the unit midpoint coordinates, and storing the midpoint coordinates of the units in each direction in the matrix according to the unit generation order.

[0074] According to the node generation order from left to right and from bottom to top, the node is connected with up to six adjacent nodes to form a unit, including XX-direction unit, XY-direction unit, XZ-direction unit, YY-direction unit, YZ-direction unit, and ZZ-direction unit, forming a six-directional lattice unit local area network of the node, such as Figure 6 As shown in (a), Figure 6 (a) is a six-way lattice unit local network with nodes indexed (i, j, k0); when all nodes are connected, a topologically disordered three-dimensional lattice unit network is formed, as shown in Figure 6 As shown in (b), Figure 6 (b) A topologically disordered three-dimensional lattice unit network formed by connecting multiple nodes.

[0075] Furthermore, in step S4, generating a material property state matrix based on the two-dimensional numerical images of each layer of thin slices specifically includes: first obtaining a two-dimensional numerical image representing the structural characteristics of each layer of thin slices, generating a corresponding node network material property state matrix based on the two-dimensional numerical image, and then generating a three-dimensional lattice unit network material property state matrix.

[0076] The method for generating a node network material property matrix involves obtaining a two-dimensional numerical image that visually represents the structural characteristics of each layer through color, converting it into RGB images to ensure that each color threshold clearly corresponds to a different material, even if each color represents only one material. The image pixel size is set to m×n, corresponding to the unit cell grid size of each layer, so that each pixel grid corresponds to a unit cell. The image is converted into RGB images to ensure that the color threshold clearly corresponds to each material type.

[0077] MATLAB software is used to extract the RGB value arrays of all pixels and assemble them into a matrix according to the order of unit cell generation index. This can represent the RGB value corresponding to each unit cell in the unit cell network of the current thin layer. The material type corresponding to each node is determined based on the RGB value, and the node network material property state matrix is ​​generated.

[0078] A method for generating a material property state matrix for a three-dimensional lattice unit network includes searching, for each node, the material property values ​​of its adjacent nodes in the node network state matrix based on the index value corresponding to the positional relationship. Based on the material property state and positional relationship between the current node and its adjacent nodes, the material property category corresponding to the connected lattice unit is determined and stored in the form of a state matrix.

[0079] Specifically, the material properties of the unit are determined by the material properties of the two end nodes. According to the index relationship between the two end nodes of the unit in different directions, such as the indexes of the two end nodes of the XX-direction unit are (i, j, k) and (i+1, j, k), the material types corresponding to the two end nodes are located in the node network material state matrix to determine the material property category corresponding to the connected unit. If the material types of the two nodes are the same, the unit material property is also the material type. If the material types of the two nodes are different, the unit material property is the interface between the two. The material property categories of all units in the six directions are determined in sequence according to the unit connection order, and the determination results are expressed in matrix form (M xx 、M xy 、M xz 、M yy 、M yz 、M zz )storage.

[0080] The implementation method for assigning material properties to units is as follows: the sequential index values ​​of the material property state matrix of the three-dimensional lattice unit network strictly correspond to the element index of the unit midpoint coordinate matrix. The unit can be directly located according to the matrix element index value, and then, the matrix index is used to implement the algorithm to efficiently assign unit material properties.

[0081] The heterogeneous concrete macrostructure model of the topologically disordered six-way connection network is established using an integrated modeling program. Figure 7 As shown, the degree of topological disorder of the model is determined by the randomness, where Figure 7 The middle left picture is a lattice model with a random degree of 0. Figure 7 The middle right picture shows a lattice model with a randomness of 0.5.

[0082] The present invention provides an automatic modeling method for heterogeneous concrete based on a topologically disordered six-way connected grid. The topologically disordered grid model determined by randomness is used to simulate the internal heterogeneity of concrete. During the modeling process, efficient and automatic construction is achieved according to the sequential index of node and unit generation, thereby solving the problem in the original macro-modeling technology of concrete specimens that it is difficult to simultaneously ensure the restoration of concrete heterogeneity and modeling efficiency.

[0083] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for automatic modeling of heterogeneous concrete based on a topologically disordered six-way connected grid, characterized in that: The following steps are involved: S1. Divide the concrete specimen into several thin slices, establish a unit cell grid in each thin slice, and form a three-dimensional unit cell network structure; S2. Based on the set randomness parameter, random nodes are generated in each cell, and the minimum distance between nodes is checked to form a random node set; S3, connecting random nodes in each unit cell with nodes in adjacent units in six directions to construct a topologically disordered three-dimensional lattice unit network; S4. Generate a material property state matrix based on the two-dimensional numerical images of each layer of thin slices, assign material properties to the three-dimensional lattice unit network, and complete the automatic modeling of the concrete model.

2. The method for automatically modeling heterogeneous concrete based on a topologically disordered six-way connected grid according to claim 1, characterized in that: In step S1, the unit length x in the X, Y, and Z directions of the unit cell grid is selected according to the structural characteristics of the concrete specimen in the X, Y, and Z directions. e 、y e 、z e , the unit length of the unit cell grid is selected to meet the following conditions: z between each layer e and x at different plane positions in the same layer e 、y e They may not be exactly the same, but the z of different areas in the same layer e Must be the same, x in the same area between layers e 、y e Must be the same.

3. The method for automatically modeling heterogeneous concrete based on a topologically disordered six-way connected grid according to claim 1, characterized in that: Step S2 specifically includes: S21. Generate a subcell in each cell, establish a local rectangular coordinate system for each subcell, set the randomness, and generate the local coordinates of random nodes in the subcell through a random function; S22, converting the random node coordinates in the local coordinate system into coordinate values ​​in the global coordinate system according to the sequential index values ​​of each sub-unit cell in the current thin layer; S23. During the node generation process, the minimum distance between the newly generated node and the old node in the X, Y, and Z directions is checked. If the minimum distance requirement is not met, the node coordinates are regenerated. S24. Store the generated coordinates of each random node in a coordinate matrix according to the node generation order, and finally form a node set including all random nodes.

4. The method for automatically modeling heterogeneous concrete based on a topologically disordered six-way connected grid according to claim 3, wherein: The calculation method for node coordinate transformation between the local coordinate system and the global coordinate system is as follows: Where x e 、y e 、z e are the unit lengths of the cell grid in the X, Y, and Z directions, respectively; i is the row index, j is the column index, and k is the slice layer index; x0(i,j,k), y0(i,j,k), and z0(i,j,k) are the X, Y, and Z coordinates of the random node corresponding to the current index (i,j,k) in the local coordinate system of the subcell; and x(i,j,k), y(i,j,k), and z(i,j,k) are the X, Y, and Z coordinates of the random node corresponding to the current index (i,j,k) in the global coordinate system; ∑y e (i) is the sum of the lengths of the cells in the Y direction from the 1st row to the i-th row, ∑x e (j) is the sum of the lengths of the cells in the X direction from the 1st column to the jth column, ∑z e (k) is the sum of the lengths of the cells in the Z direction from the 1st layer to the kth layer; rand(1) generates a random number between 0 and 1, and random is the degree of randomness.

5. The method for automatically modeling heterogeneous concrete based on a topologically disordered six-way connected grid according to claim 3, characterized in that: In step S23, the minimum distance check includes: based on the divided three-dimensional cubic cell network, performing a distance check between the new nodes generated in each cell and the old nodes in the neighborhood of the cell, where the neighborhood consists of all cells that share edges or corners with the cell in the X, Y, and Z directions.

6. The method for automatically modeling heterogeneous concrete based on a topologically disordered six-way connected grid according to claim 1, characterized in that: Step S3 specifically includes: Connect a single node in each unit cell with adjacent nodes in three main directions on three main planes to form a six-directional lattice unit local network of a single node, forming a topologically disordered three-dimensional lattice unit network, and store the midpoint coordinates of each unit in each direction in a matrix according to the connection order; Among them, the three main planes include XY plane, XZ plane, and YZ plane, the three main directions include horizontal, vertical, and oblique directions, and the six-directional lattice unit local network of a single node includes six directional units: XX, YY, ZZ, XY, XZ, and YZ.

7. The method for automatically modeling heterogeneous concrete based on a topologically disordered six-way connected grid according to claim 6, characterized in that: The midpoint coordinates of each unit in each direction are stored in the matrix according to the connection order, specifically including: obtaining the index of the other end node according to the current node index and its positional relationship with the other end node, obtaining the node coordinates from the random node coordinate matrix according to the index, taking the mean of the two node coordinates to obtain the unit midpoint coordinates, and storing the midpoint coordinates of the units in each direction in the matrix according to the unit generation order.

8. The method for automatically modeling heterogeneous concrete based on a topologically disordered six-way connected grid according to claim 1, wherein: In step S4, generating a material property state matrix based on the two-dimensional numerical images of each layer of thin slices specifically includes: obtaining a two-dimensional numerical image representing the structural characteristics of each layer of thin slices, generating a corresponding node network material property state matrix based on the two-dimensional numerical image, and then generating a three-dimensional lattice unit network material property state matrix.

9. The method for automatically modeling heterogeneous concrete based on a topologically disordered six-way connected grid according to claim 8, characterized in that: The generation of the node network material state matrix includes: Perform RGB image processing on the two-dimensional numerical image to make each color threshold clear to correspond to different materials; Set the image pixel size to the number of unit cell grids in the current layer, extract all pixel RGB value arrays, and assemble them into a matrix according to the order in which the unit cells are generated, representing the RGB value corresponding to each unit cell in the unit cell network of the current thin layer; The material type corresponding to each node is determined according to the RGB value, and the node network material property state matrix is ​​generated.

10. The method for automatically modeling heterogeneous concrete based on a topologically disordered six-way connected grid according to claim 9, characterized in that: The method for generating the material property state matrix of a three-dimensional lattice unit network includes: For each node in the node network material property status matrix, the material property value of its adjacent node in the node network status matrix is ​​searched according to the index value corresponding to the node's position relationship. According to the material property status and position relationship between the current node and the adjacent nodes, the material property category corresponding to the connected lattice unit is determined and stored in the form of a matrix.

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