Anisotropy analysis method for mechanical properties of multi-component materials

Abstract

This invention provides an anisotropy analysis method for the mechanical properties of multi-component materials. First, the microstructural geometric features of the multi-component material are scattered based on micro-CT voxel coordinates. A representative cylindrical computational domain is established, ensuring that each direction within the domain contains at least five microstructural feature cells. Multiple random search points are set within the computational domain, and multiple directional vectors are established starting from each search point. A quantization radius is set for the distribution density of voxel points of the main component structures. The distribution density of voxel points in different directions is used as the criterion for determining the main directions of the material. The degree of anisotropy is then normalized and defined. This invention can effectively analyze the main directions and degree of anisotropy of multi-component materials, offering accurate, convenient, flexible, and widely applicable calculations with low sensitivity to image noise, providing a basis for the study of the mechanical properties of multi-component materials.

Description

Technical Field

[0001] This invention belongs to the technical field of basic physical property evaluation of materials, and specifically relates to an anisotropic analysis method for the mechanical properties of multi-component materials. Background Technology

[0002] For multi-component materials, the mechanical properties often exhibit anisotropic characteristics due to the presence of their internal microstructures. When studying the mechanical behavior of materials containing solid-phase structures, volume fraction is generally considered a necessary geometric measure of local structure, as seen in materials such as aluminum foam, geological materials, porous glass, sintered materials, and cancellous bone. However, most multi-component materials exhibit directional characteristics in their microstructure distribution, necessitating a more comprehensive description of the directional behavior of local microstructures.

[0003] Previous studies on the quantification of anisotropy in multi-component materials have mostly employed destructive methods, such as continuously cutting asphalt mixtures and observing the cross-sectional morphology of the slices, or comparing the material properties of rocks in different directions through experiments to infer the anisotropy. However, establishing the correspondence between microstructure and macroscopic mechanical properties requires both describing the microstructure and conducting experimental studies on the macroscopic mechanical properties of the same sample. Therefore, non-destructive methods for quantifying material anisotropy are crucial. In the study of anisotropy in cancellous bone, some researchers have developed a method for quantifying cancellous bone anisotropy using mean intercept length (MIL) based on the microstructural characteristics acquired from micro-CT images. However, this method requires clear microstructural boundaries, demands high image quality, is highly sensitive to image noise, and has relatively high computational costs, making it unsuitable for all multi-component materials.

[0004] In conclusion, it is necessary to further innovate existing technologies. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art and provide an anisotropy analysis method for the mechanical properties of multi-component materials. This method can effectively analyze the principal direction and degree of anisotropy of multi-component materials. It is accurate, convenient, flexible, and widely applicable, and has low sensitivity to image noise. It can provide a basis for the study of the mechanical properties of multi-component materials.

[0006] To address the aforementioned technical problems, this invention provides an anisotropic analysis method for the mechanical properties of multi-component materials. Based on micro-CT images, the internal microstructure of the multi-component material is processed into a scatter plot, and the main orientation and degree of anisotropy of the multi-component material are determined based on the scatter plot model of the microstructure.

[0007] The anisotropic analysis method for the mechanical properties of multi-component materials, wherein: the scattering of the internal microstructure of the multi-component materials is mainly to scatter the geometric features of the microstructure of the multi-component materials based on the micro-CT voxel coordinates.

[0008] The anisotropic analysis method for the mechanical properties of multi-component materials, wherein the specific steps for the scatter plot processing of the internal microstructure of the multi-component materials are as follows:

[0009] (1.1) First, micro-CT scanning was used to obtain the internal microstructure of the multi-component material;

[0010] (1.2) Perform image segmentation on the micro-CT data, set gray value thresholds, separate the main components of the material, and create separate gray value masks;

[0011] (1.3) Extract the coordinate information of all voxel points contained in the gray value mask of the main components of the material and generate a coordinate data file.

[0012] The anisotropic analysis method for the mechanical properties of multi-component materials, wherein the method for determining the principal direction of the multi-component material is as follows: setting a representative cylindrical computational domain, and ensuring that each direction within the computational domain contains at least 5 microstructural feature cells; setting any number of random search points within the computational domain, and setting any number of direction vectors starting from each search point; setting the quantization radius of the voxel distribution density of the principal component structure; and using the voxel distribution density within the same radius in different directions as the criterion for determining the principal direction of the material.

[0013] The anisotropy analysis method for the mechanical properties of multi-component materials, wherein the specific steps for determining the principal orientation of the multi-component material are as follows:

[0014] (2.1) Select a representative cylinder inside the material as the computational domain. When selecting the size of the representative cylinder, it should be ensured that the representative cylinder contains at least 5 characteristic cells of the microstructure of the main components in each direction.

[0015] (2.2) Randomly arrange Pn points in the computational domain as random search points, and set N×N uniformly distributed vectors as the search vectors for the first principal direction of the material, with each search point as the starting point;

[0016] (2.3) Count the voxel coordinates that are less than r away from the line where each search vector is located, and use them as the number of voxel points in that direction of the search point. The search radius r should be determined according to: r = Th + Sp / 2, where Th is the geometric feature size of the main component and Sp is the geometric feature size of other components.

[0017] (2.4) Divide the number of voxels by the length of the line intercepted by the representative cylinder to obtain the voxel density at the search point in that direction;

[0018] (2.5) Determine the direction e1 with the largest voxel point density. This direction is the first principal direction of the material. The point density ρ1 at this time is the voxel point density in this direction. The search point at this time is determined as the unique search point for subsequent calculations.

[0019] (2.6) With the above-mentioned unique search point as the center, arrange M uniformly distributed vectors in a plane perpendicular to the first principal direction e1 of the material as the search vectors for the second principal direction of the material.

[0020] (2.7) Repeat steps (2.3)-(2.4) to determine the direction with the largest voxel point density, which is the second principal direction e2 of the material. The point density ρ2 at this time is the voxel point density in this direction.

[0021] (2.8) Cross product the first principal direction e1 and the second principal direction e2 of the material to obtain the third principal direction e3 of the material. Use the third principal direction e3 of the material as the search vector and repeat steps (2.3)-(2.4) to obtain the voxel density ρ3 in this direction.

[0022] The anisotropy analysis method for the mechanical properties of multi-component materials, wherein determining the degree of anisotropy of the multi-component material mainly involves a quantitative analysis of the degree of anisotropy, the main method being: defining the degree of anisotropy DA of the multi-component material as follows:

[0023] DA = 1 - ρ3 / ρ1;

[0024] Where ρ1 is the bulk density of the principal component in the first principal direction, and ρ3 is the bulk density of the principal component in the third principal direction; the degree of anisotropy at this time is the normalized result (0≤DA<1); when DA is 0, it indicates that the material is completely isotropic.

[0025] By adopting the above technical solution, the present invention has the following beneficial effects:

[0026] The anisotropy analysis method for the mechanical properties of multi-component materials in this invention is rationally conceived. It uses the geometric characteristics of the material's internal microstructure as the main factor causing anisotropy to perform quantitative analysis of anisotropy, including the determination of the material's principal orientation and the quantification of the degree of anisotropy. It is not only non-destructive, fast, and accurate, but also applicable to a variety of materials. It has low sensitivity to image noise, and is accurate, convenient, flexible, and widely applicable, providing a basis for the study of the mechanical properties of multi-component materials. Attached Figure Description

[0027] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0028] Figure 1 This is a schematic diagram of the scattering treatment of microstructure in the anisotropic analysis method of the mechanical properties of multi-component materials of the present invention;

[0029] Figure 2 This is a schematic diagram of the search vector for the anisotropic analysis method of the mechanical properties of multi-component materials according to the present invention;

[0030] Figure 3 This is a schematic diagram illustrating the direction determination of the anisotropy analysis method for the mechanical properties of multi-component materials according to the present invention.

[0031] Figure 4 The second principal direction search plane for the material is the material search plane for the anisotropic analysis method of the mechanical properties of multi-component materials in this invention.

[0032] Figure 5 This is a schematic diagram showing the results of judging the three principal directions of the material in the anisotropic analysis method for the mechanical properties of multi-component materials according to the present invention.

[0033] Notes: 1-Main components of the material, 2-Other components of the material, 3-Scattered microstructure pixel model, 4-Random search point, 5-N×N search vectors passing through a certain search point, 6-Search radius, 7-Vector of a certain direction, 8-Thickness of microstructure cell, 9-Microstructure spacing, 10-The determined first principal direction, 11-Search vector of the second principal direction. Detailed Implementation

[0034] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0035] The present invention will be further explained below with reference to specific embodiments.

[0036] The anisotropy analysis method for the mechanical properties of multi-component materials provided in this embodiment is based on micro-CT images to perform scattering processing on the internal microstructure of multi-component materials, and uses the scatter model of the microstructure as a basis to determine the main orientation and degree of anisotropy of multi-component materials.

[0037] The above-mentioned scattering process of the internal microstructure of multi-component materials based on micro-CT images mainly involves scattering the geometric features of the microstructure of multi-component materials according to the coordinates of micro-CT voxel points.

[0038] The specific steps for the scattered point processing of the internal microstructure of multi-component materials are as follows:

[0039] (1.1) First, micro-CT scanning was used to obtain the internal microstructure of the multi-component material;

[0040] (1.2) Perform image segmentation on micro-CT data, set gray value threshold (the gray value threshold should be set according to the different main component materials, such as: the gray value range of aluminum foam is CT≥1500Hu, and the gray value range of trabecular bone is CT≥660Hu), separate the main components of the material, and create separate gray value masks;

[0041] (1.3) Extract the coordinate information of all voxels contained in the grayscale mask of the main components of the material and generate a data file (i.e., generate a coordinate point matrix of a rows and 3 columns, where a is the number of coordinate points and the 3 columns are the x, y, and z coordinate values ​​of the voxel points respectively).

[0042] The main method for determining the principal orientation of multi-component materials is as follows: First, a representative cylinder RC is set as the computational domain, and it is ensured that each direction within the computational domain contains at least 5 microstructural feature cells; then, multiple random search points are set within the computational domain, and multiple directional vectors are set with each search point as the starting point; the quantization radius r = Th + Sp / 2 of the voxel distribution density of the principal component is set, where Th is the geometric feature size of the component of interest, and Sp is the geometric feature size of other components; the voxel distribution density in different directions is used as the criterion for determining the principal orientation of the material.

[0043] The specific steps for determining the main orientation of multi-component materials are as follows:

[0044] (2.1) Select a representative cylinder (RC) inside the material as the computational domain. In particular, when selecting the size of the representative cylinder RC, it should be ensured that the representative cylinder RC contains at least 5 characteristic cells of the microstructure of the main components in each direction.

[0045] (2.2) Randomly arrange Pn (Pn is the number of search points. There are N×N vectors starting from each search point, so the total number of vectors is Pn×N×N) points in the computational domain as random search points. Set N×N uniformly distributed vectors starting from each search point as the search vectors for the first principal direction of the material.

[0046] (2.3) Count the voxel coordinates that are less than r away from the line containing each search vector, and use this count as the number of voxel points in that direction at that search point. The search radius r should be determined according to the following:

[0047] r = Th + Sp / 2;

[0048] Where Th represents the geometric feature size of the principal component, and Sp represents the geometric feature size of the other components;

[0049] (2.4) Divide the number of voxels by the length of the line intercepted by the representative cylinder RC to obtain the voxel density at the search point in that direction;

[0050] (2.5) Determine the direction e1 with the largest voxel point density. This direction is the first principal direction of the material. The point density ρ1 at this time is the voxel point density in this direction. The search point at this time is determined as the unique search point for subsequent calculations.

[0051] (2.6) With the above-mentioned unique search point as the center, arrange M uniformly distributed vectors in a plane perpendicular to the first principal direction e1 of the material as the search vectors for the second principal direction of the material.

[0052] (2.7) Repeat steps (2.3)-(2.4) to determine the direction with the largest voxel point density, which is the second principal direction e2 of the material. The point density ρ2 at this time is the voxel point density in this direction.

[0053] (2.8) Cross product the first principal direction e1 and the second principal direction e2 of the material to obtain the third principal direction e3 of the material. Use the third principal direction e3 of the material as the search vector and repeat steps (2.3)-(2.4) to obtain the voxel density ρ3 in this direction.

[0054] The above-mentioned assessment of the degree of anisotropy in multi-component materials mainly involves a quantitative analysis of the degree of anisotropy. The specific method is as follows:

[0055] Define the degree of anisotropy (DA) of multi-component materials:

[0056] DA = 1 - ρ3 / ρ1;

[0057] Where ρ1 is the density of the bulk particles of the principal components in the first principal direction, and ρ3 is the density of the bulk particles of the principal components in the third principal direction; the degree of anisotropy at this time is the normalized result (0≤DA<1); when DA is 0, it indicates that the material is completely isotropic; where, the normalization definition of the degree of anisotropy is: DA=1-ρ3 / ρ1, which greatly reduces the influence of micro-CT scan resolution.

[0058] Example 1

[0059] Example 1 of this invention uses a porous solid material as an example. The specific implementation of Example 1 of this invention is described in detail with reference to the accompanying drawings:

[0060] Micro-CT scans are performed on the material; there are no specific requirements for the scan resolution, as long as the structures of different components can be distinguished. For example... Figure 1 As shown, a representative cylindrical RC (5mm in diameter, 5mm in height, containing more than 5 solid structural cells in each direction) is selected. The material image is segmented by grayscale values, and grayscale masks for the main components are created. 1 represents the main component of the material, i.e., the solid phase; 2 represents the other components of the material, i.e., the porous portion. The coordinate information of all voxel points of the main components is extracted to complete the scattering processing of the porous solid material microstructure.

[0061] like Figure 2 As shown, 50 random points are arranged inside the representative cylinder RC as search points 4; 360×360 search vectors 5 are set through each search point.

[0062] As shown in Figure 3, the distance between all voxel points of the sample after scattering and vector 7 is calculated. Voxel points with a distance less than the search radius 6 are counted and divided by the length of the line intercepted by the representative cylinder RC, which is taken as the voxel point density in that direction at the search point. The direction e1 with the maximum point density is determined, and the search point where the point density is located is calculated. This search point is defined as the unique search point for subsequent calculations. Here, e1 is the first material principal direction of the sample. The maximum point density ρ1 at this time is the point density in that direction.

[0063] To make direction determination more accurate, the search radius r is defined as follows:

[0064]

[0065] Where Th is the characteristic size 8 of the solid structure and Sp is the characteristic size 9 of the pore structure; under this definition, the number of solid cells contained within the search radius will be between 1 and 2.

[0066] like Figure 4 As shown, with the unique search point Searchpoint as the center, 360 uniformly distributed vectors 11 are set in a plane perpendicular to the first principal direction 10 of the material. The same search radius 6 is used to count voxel points. The direction e2 with the largest voxel point density in the plane is determined as the second principal direction of the material. The point density at this time is the point density ρ2 in that direction.

[0067] The cross product of the first principal direction e1 and the second principal direction e2 of the material yields e3, which is the third principal direction of the material. Using e3 as the search direction, the point density ρ3 in this direction is calculated using the same search radius 6. The results of determining the three principal directions of the material are as follows: Figure 5 As shown.

[0068] Anisotropy is a parameter that measures the strength of a material's directionality. To quantify the degree of anisotropy and ensure that the results are not affected by the resolution of micro-CT scans, a normalization method is used to define this parameter; the definition of DA is as follows:

[0069]

[0070] Where ρ1 is the bulk density of the principal component in the first principal direction, and ρ3 is the bulk density of the principal component in the third principal direction. The anisotropy degree DA is in the range of 0 ≤ DA < 1; when DA is 0, it indicates that the material is completely isotropic.

[0071] This invention can effectively analyze the principal orientation and anisotropy of multi-component materials. It is accurate, convenient, flexible, and widely applicable, and has low sensitivity to image noise. It can provide a basis for the study of the mechanical properties of multi-component materials.

[0072] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for anisotropic analysis of the mechanical properties of multi-component materials, characterized in that... Based on micro-CT images, the internal microstructure of multi-component materials is processed into a scatter plot, and the main orientation and degree of anisotropy of multi-component materials are determined based on the scatter plot model of the microstructure. The specific steps for the scattered point processing of the internal microstructure of multi-component materials are as follows: (1.1) First, micro-CT scanning was used to obtain the internal microstructure of the multi-component material; (1.2) Perform image segmentation on the micro-CT data, set gray value thresholds, separate the main components of the material, and create separate gray value masks; (1.3) Extract the coordinate information of all voxel points contained in the grayscale mask of the main components of the material, and generate a coordinate data file; The method for determining the main direction of a multi-component material is as follows: a representative cylindrical computational domain is set up, and it is ensured that each direction within the computational domain contains at least 5 microstructure feature cells; multiple random search points are set up within the computational domain, and multiple directional vectors are set up with each search point as the starting point; the quantization radius of the voxel distribution density of the main component structure is set; the voxel distribution density within the same radius in different directions is used as the criterion for determining the main direction of the material. The determination of the degree of anisotropy of multi-component materials is a quantitative analysis of the degree of anisotropy. The method is as follows: Define the degree of anisotropy DA of multi-component materials: ； in, The bulk density of the main components in the first principal direction. The density of the main component particles along the third principal direction; the degree of anisotropy at this point is the normalized result. When DA is 0, it indicates that the material is completely isotropic.

2. The anisotropic analysis method for the mechanical properties of multi-component materials as described in claim 1, characterized in that: The process of scattering the internal microstructure of multi-component materials involves scattering the geometric features of the microstructure of multi-component materials based on the coordinates of micro-CT voxels.

3. The anisotropic analysis method for the mechanical properties of multi-component materials as described in claim 1, characterized in that, The specific steps for determining the main orientation of multi-component materials are as follows: (2.1) Select a representative cylinder inside the material as the computational domain. When selecting the size of the representative cylinder, it should be ensured that the representative cylinder contains at least 5 characteristic cells of the microstructure of the main components in each direction. (2.2) Randomly arrange Pn points in the computational domain as random search points, and set N×N uniformly distributed vectors as the search vectors for the first principal direction of the material, with each search point as the starting point; (2.3) Count the voxel coordinates that are less than r away from the line containing each search vector, and use this count as the number of voxel points in that direction at that search point. The determination of the search radius r should follow the following: Where Th is the geometric feature size of the principal component and Sp is the geometric feature size of the other components; (2.4) Divide the number of voxels by the length of the line intercepted by the representative cylinder to obtain the voxel density at the search point in that direction; (2.5) Determine the direction e1 where the voxel point density is the largest. This direction is the first principal direction of the material, and the point density at this point is... Given the voxel density in this direction, the search point at this point is determined as the unique search point for subsequent calculations; (2.6) With the above-mentioned unique search point as the center, arrange M uniformly distributed vectors in a plane perpendicular to the first principal direction e1 of the material as the search vectors for the second principal direction of the material. (2.7) Repeat steps (2.3)-(2.4) to determine the direction with the maximum voxel point density, which is the second principal direction e2 of the material. The point density at this time is The voxel density in this direction; (2.8) Cross product the first principal direction e1 and the second principal direction e2 of the material to obtain the third principal direction e3 of the material. Use the third principal direction e3 of the material as the search vector and repeat steps (2.3)-(2.4) to obtain the voxel density in this direction. .

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