Methods and apparatus for analyzing the fracture toughness of ceramics

Abstract

This invention relates to artificial intelligence technology and discloses a method and apparatus for analyzing the fracture toughness of ceramics. The method includes: constructing a finite element model of a target ceramic; generating experimental data of the target ceramic based on the finite element model; calculating damage variables of the target ceramic based on the experimental data; generating a fracture toughness index of the target ceramic using a preset fracture toughness index algorithm and the damage variables; generating a fracture toughness curve of the target ceramic based on the fracture toughness index and the experimental data; and performing fracture toughness analysis on the target ceramic based on the fracture toughness curve. This invention can improve the efficiency of fracture toughness analysis of ceramics.

Description

Technical Field

[0001] This invention relates to the field of artificial intelligence technology, and in particular to a method and apparatus for analyzing the fracture toughness of ceramics. Background Technology

[0002] Ceramic materials are widely used in various engineering fields, such as aerospace, automotive, and electronic equipment. Understanding the fracture toughness of ceramic materials is crucial for key components and structures in these applications. By analyzing the fracture toughness of ceramics, it is possible to assess whether they will fracture or break under stress conditions, thereby ensuring the safety of products or structures.

[0003] Traditional methods typically require the preparation of a large number of ceramic samples and the conduct of complex physical experiments, which is time-consuming and cumbersome. In addition, different forces need to be applied to the ceramic samples and fracture experiments need to be conducted under different conditions, which takes a long time and requires a large number of experiments to obtain reliable results, resulting in low efficiency in ceramic fracture toughness analysis. Summary of the Invention

[0004] This invention provides a method and apparatus for analyzing the fracture toughness of ceramics, the main purpose of which is to solve the problem of low efficiency in analyzing the fracture toughness of ceramics.

[0005] To achieve the above objectives, the present invention provides a method for analyzing the fracture toughness of ceramics, comprising:

[0006] Construct a finite element model of the target ceramic;

[0007] Experimental data for the target ceramic were generated based on the finite element model.

[0008] The damage variable of the target ceramic is calculated based on the experimental data.

[0009] The fracture toughness index of the target ceramic is generated using a preset fracture toughness index algorithm and the damage variable, wherein the preset fracture toughness index algorithm is as follows:

[0010]

[0011] Wherein, K is the fracture toughness index of the target ceramic, Y is the geometric factor, σ is the stress intensity factor of the target ceramic, and a is the crack length of the target ceramic;

[0012] The fracture toughness curve of the target ceramic is generated based on the fracture toughness index and the experimental data, and the fracture toughness analysis of the target ceramic is performed based on the fracture toughness curve.

[0013] Optionally, the construction of the finite element model of the target ceramic includes:

[0014] Generate the geometric model of the target ceramic;

[0015] The target ceramic is discretized based on the geometric model to obtain a mesh model of the target ceramic.

[0016] The material properties of the mesh model are configured to obtain the configuration model of the mesh model;

[0017] Generate the boundary conditions of the configuration model, and construct the finite element model of the target ceramic based on the boundary conditions and the configuration model.

[0018] Optionally, generating the geometric model of the target ceramic includes:

[0019] Collect the three-dimensional geometric shape information of the target ceramic;

[0020] A geometric model of the target ceramic is generated based on the three-dimensional geometric information.

[0021] Optionally, generating the geometric model of the target ceramic includes:

[0022] The parameters of the preset scanning device are configured according to the target ceramic to obtain the configured scanning device;

[0023] The target ceramic is scanned using the configured scanning device to obtain the scan data of the target ceramic;

[0024] The scanned data is converted into three-dimensional point cloud data, and a geometric model of the target ceramic is generated based on the three-dimensional point cloud data.

[0025] Optionally, generating the geometric model of the target ceramic based on the three-dimensional point cloud data includes:

[0026] The 3D point cloud data is filtered using a preset filtering algorithm to obtain filtered 3D point cloud data. The preset filtering algorithm is as follows:

[0027]

[0028] Wherein, G(x,y) is the weight distribution of data points in the three-dimensional point cloud data, x is the abscissa of each point in the three-dimensional point cloud data, μ is the mean of the weight distribution, y is the ordinate of each point in the three-dimensional point cloud data, and σ is the standard deviation of the weight distribution.

[0029] The filtered data is reconstructed to obtain a triangular mesh model of the filtered data;

[0030] The triangular mesh model is smoothed to obtain a smoothed model of the triangular mesh model, and the smoothed model is determined to be the geometric model of the target ceramic.

[0031] Optionally, generating experimental data for the target ceramic based on the finite element model includes:

[0032] Finite element analysis is performed on the target ceramic based on the finite element model to obtain the finite element data of the target ceramic.

[0033] The target data of the limited metadata is extracted to obtain the target data of the limited metadata, and the target data is determined to be the experimental data of the target ceramic.

[0034] Optionally, calculating the damage variable of the target ceramic based on the experimental data includes:

[0035] Determine the damage index of the target ceramic;

[0036] The damage variable of the target ceramic is calculated based on the experimental data and the damage index.

[0037] Optionally, calculating the damage variable of the target ceramic based on the experimental data and the damage index includes:

[0038] The experimental data is filtered according to the damage index to obtain the damage index data in the experimental data.

[0039] The mean of the damage index data is calculated to obtain the mean data of the damage index data;

[0040] The mean data is determined as the damage variable of the target ceramic.

[0041] Optionally, generating the fracture toughness curve of the target ceramic based on the fracture toughness index and the experimental data includes:

[0042] Establish the data correlation between the fracture toughness index and the experimental data;

[0043] Data points for the target ceramic are generated based on the data correlation.

[0044] The fracture toughness curve of the target ceramic is plotted based on the data points.

[0045] To address the aforementioned problems, the present invention also provides a ceramic fracture toughness analysis device, characterized in that the device comprises:

[0046] The finite element model building module is used to build the finite element model of the target ceramic.

[0047] An experimental data generation module is used to generate experimental data for the target ceramic based on the finite element model.

[0048] The damage variable calculation module is used to calculate the damage variable of the target ceramic based on the experimental data.

[0049] A fracture toughness index generation module is used to generate a fracture toughness index of the target ceramic using a preset fracture toughness index algorithm and the damage variable, wherein the preset fracture toughness index algorithm is:

[0050]

[0051] Wherein, K is the fracture toughness index of the target ceramic, Y is the geometric factor, σ is the stress intensity factor of the target ceramic, and a is the crack length of the target ceramic;

[0052] The fracture toughness analysis module is used to generate the fracture toughness curve of the target ceramic based on the fracture toughness index and the experimental data, and to perform fracture toughness analysis on the target ceramic based on the fracture toughness curve.

[0053] This invention constructs a finite element model of the target ceramic, enabling simulation experiments on a computer. This avoids the need for preparing large numbers of samples and conducting time-consuming tests. Experimental data for the target ceramic is generated directly from the finite element model, eliminating the need for actual physical experiments. This allows for faster acquisition of the required data. Damage variables of the target ceramic are calculated using the experimental data. A pre-defined fracture toughness index algorithm, combined with the damage variables, is used to calculate the fracture toughness index of the target ceramic. This index quantitatively describes the fracture resistance of the ceramic. A fracture toughness curve of the target ceramic is generated based on the fracture toughness index and the experimental data. This curve provides a more intuitive understanding of the material's fracture performance and its relationship with crack length. Therefore, this invention proposes a recommended method and apparatus for ceramic fracture toughness analysis, which can solve the problem of low efficiency in ceramic fracture toughness analysis. Attached Figure Description

[0054] Figure 1 This is a schematic flowchart of a ceramic fracture toughness analysis method provided in an embodiment of the present invention;

[0055] Figure 2 This is a schematic diagram of the process for generating a geometric model of a target ceramic according to an embodiment of the present invention;

[0056] Figure 3 This is a schematic flowchart illustrating the calculation of damage variables of a target ceramic according to an embodiment of the present invention.

[0057] Figure 4 This is a functional block diagram of a ceramic fracture toughness analysis device provided in an embodiment of the present invention;

[0058] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0059] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0060] This application provides a method for analyzing the fracture toughness of ceramics. The execution subject of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, or other similar device. In other words, the method can be executed by software or hardware installed on a terminal device or a server-side device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cluster of cloud servers. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0061] Reference Figure 1 The diagram shown is a schematic flowchart of a ceramic fracture toughness analysis method according to an embodiment of the present invention. In this embodiment, the ceramic fracture toughness analysis method includes:

[0062] S1. Construct the finite element model of the target ceramic.

[0063] In this embodiment of the invention, constructing the finite element model of the target ceramic includes:

[0064] Generate the geometric model of the target ceramic;

[0065] The target ceramic is discretized based on the geometric model to obtain a mesh model of the target ceramic.

[0066] The material properties of the mesh model are configured to obtain the configuration model of the mesh model;

[0067] Generate the boundary conditions of the configuration model, and construct the finite element model of the target ceramic based on the boundary conditions and the configuration model.

[0068] In detail, generating the geometric model of the target ceramic refers to collecting the three-dimensional geometric shape information of the target ceramic and modeling it using computer-aided design (CAD) software, or scanning the target ceramic using a scanning device and converting the scanned data into three-dimensional point cloud data to generate the geometric model.

[0069] In detail, the discretization of the target ceramic based on the geometric model refers to discretizing the geometric model into a finite number of small units, such as triangles, quadrilaterals, or hexahedrons, to obtain a mesh model of the target ceramic. The discretization can be performed using mesh generation algorithms, such as triangulation algorithms or quadrilateral mesh generation algorithms.

[0070] In detail, configuring the material properties of the mesh model refers to assigning appropriate material properties to each element of the mesh model, including elastic modulus, Poisson's ratio, density, etc. These properties can be determined based on the material properties and experimental data of the target ceramic, or estimated through literature review or professional knowledge.

[0071] In detail, the boundary conditions include constraint conditions and loading conditions, wherein constraint conditions are used to limit the degrees of freedom of the model, such as fixing boundaries or constraining displacements; and loading conditions represent the external loads or constraints applied to the model during the simulation.

[0072] Specifically, generating the geometric model of the target ceramic includes:

[0073] Collect the three-dimensional geometric shape information of the target ceramic;

[0074] A geometric model of the target ceramic is generated based on the three-dimensional geometric information.

[0075] In detail, generating the geometric model of the target ceramic based on the three-dimensional geometric shape information means drawing the geometric model of the ceramic using CAD software and the three-dimensional geometric shape information.

[0076] Furthermore, the CAD software used for drawing is determined, including but not limited to: AutoCAD, SolidWorks, CATIA, etc. Then, a new project is created in the CAD software or an existing ceramic model is opened, and the drawing tools provided by the CAD software are used to draw according to the three-dimensional geometric information, wherein the three-dimensional geometric information may be the size and geometry of the ceramic.

[0077] In detail, see Figure 2 As shown, the process of generating the geometric model of the target ceramic includes:

[0078] S21. Configure the preset scanning device parameters according to the target ceramic to obtain the configured scanning device;

[0079] S22. The target ceramic is scanned using the configured scanning device to obtain the scanning data of the target ceramic;

[0080] S23. Convert the scanned data into three-dimensional point cloud data, and generate a geometric model of the target ceramic based on the three-dimensional point cloud data.

[0081] Specifically, the preset scanning device can be a laser scanning device or a structured light scanning device.

[0082] In detail, the parameter configuration of the preset scanning device based on the target ceramic can be performed on the preset scanning device according to the size, shape and surface characteristics of the target ceramic. This includes selecting a suitable scanning device type (such as a laser scanner or a structured light scanner), setting parameters such as the resolution, light source intensity and scanning speed of the scanning device, so as to ensure that the scanning device can accurately capture the geometric information of the target ceramic.

[0083] In detail, scanning the target ceramic using the configured scanning device means moving along the surface of the target ceramic, irradiating the ceramic with a light source or laser beam, and recording the geometric coordinates and intensity information of each scanning point.

[0084] In detail, configuring the parameters of the preset scanning equipment according to the target ceramic means selecting a suitable scanning technology based on the characteristics of the ceramic and the required accuracy, preparing the corresponding scanner, light source, three-axis platform and other equipment, and ensuring that they are working properly.

[0085] In detail, scanning the target ceramic using the configured scanning device refers to placing the ceramic in the scanning area, scanning the target ceramic according to the adjusted parameters of the device, and then using professional scanning data processing software to generate the scanning data of the target ceramic. The scanning data processing software may be GeomagicWrap, Rapidform, CloudCompare, etc.

[0086] In detail, the three-dimensional point cloud data consists of a large number of discrete points, each of which has its coordinate information in three-dimensional space.

[0087] Specifically, generating the geometric model of the target ceramic based on the three-dimensional point cloud data includes:

[0088] The 3D point cloud data is filtered using a preset filtering algorithm to obtain filtered 3D point cloud data. The preset filtering algorithm is as follows:

[0089]

[0090] Wherein, G(x,y) is the weight distribution of data points in the three-dimensional point cloud data, x is the abscissa of each point in the three-dimensional point cloud data, μ is the mean of the weight distribution, y is the ordinate of each point in the three-dimensional point cloud data, and σ is the standard deviation of the weight distribution.

[0091] The filtered data is reconstructed to obtain a triangular mesh model of the filtered data;

[0092] The triangular mesh model is smoothed to obtain a smoothed model of the triangular mesh model, and the smoothed model is determined to be the geometric model of the target ceramic.

[0093] In detail, the preset filtering algorithm reduces the impact of noise by performing a weighted average of the signal. The preset filtering algorithm can be used to construct a filter for the three-dimensional point cloud data, wherein the weight values ​​for the weighted average of the signal by the filter are determined by the preset filtering algorithm.

[0094] In detail, the process of filtering the 3D point cloud data using a preset filtering algorithm to obtain filtered 3D point cloud data involves first generating a filter for the 3D point cloud data according to the preset filtering algorithm, and then determining the size and shape of the filter, as the size and shape of the filter will affect the filtered point cloud data. Generally, an appropriate filter size and shape can be selected according to the distribution and characteristics of the 3D point cloud data. Common filter shapes include circles, squares, and rectangles. Then, for each point in the 3D point cloud data, a filter can be constructed with that point as the center. Based on the selected filter size and shape, the distance between the filter center point and the surrounding points is calculated, and the weight value is calculated according to the preset filtering algorithm. By calculating the distance between the filter center point and the surrounding points and the weight value, the weighted average value of each point can be obtained, which is the filtered 3D point cloud data.

[0095] In detail, the mesh reconstruction of the filtered data refers to generating a high-quality geometric model by performing mesh reconstruction on the point cloud data. The mesh reconstruction is the process of converting the point cloud data into a triangular mesh model. Commonly used algorithms include Poisson reconstruction, Ball-Pivoting algorithm, Marching Cubes algorithm, etc.

[0096] In detail, the curve smoothing process of the triangular mesh model refers to smoothing and patching the mesh to obtain a more realistic, continuous and complete geometric surface.

[0097] S2. Generate experimental data for the target ceramic based on the finite element model.

[0098] In this embodiment of the invention, generating experimental data for the target ceramic based on the finite element model includes:

[0099] Finite element analysis is performed on the target ceramic based on the finite element model to obtain the finite element data of the target ceramic.

[0100] The target data of the limited metadata is extracted to obtain the target data of the limited metadata, and the target data is determined to be the experimental data of the target ceramic.

[0101] In detail, the finite element analysis of the target ceramic based on the finite element model refers to selecting an appropriate solver and analysis type, such as static analysis or dynamic analysis, in the finite element analysis software, running the finite element analysis software, solving the stress, deformation, crack and other responses of the ceramic under given loading conditions, and ensuring that the finite element analysis converges and reaches a stable state. The response data of the finite element model is the finite element data of the target ceramic.

[0102] In detail, the target extraction of the finite metadata to obtain the target data of the finite metadata refers to filtering out data related to strain, crack density, effect volume, etc. in the finite metadata, including information such as the coordinates, size, and material properties of each element, as well as its stress, strain, displacement, and other response data under force.

[0103] S3. Calculate the damage variable of the target ceramic based on the experimental data.

[0104] In this embodiment of the invention, calculating the damage variable of the target ceramic based on the experimental data includes:

[0105] Determine the damage index of the target ceramic;

[0106] The damage variable of the target ceramic is calculated based on the experimental data and the damage index.

[0107] In detail, the damage index is one or more parameters closely related to the performance and reliability of the target ceramic, which can be determined by engineering experience, experimental testing or numerical simulation, and here it can refer to crack length.

[0108] In detail, see Figure 3 As shown, the calculation of the damage variable of the target ceramic based on the experimental data and the damage index includes:

[0109] S31. Based on the damage index, the experimental data is filtered to obtain the damage index data in the experimental data;

[0110] S32. Calculate the mean of the damage index data to obtain the mean data of the damage index data;

[0111] S33. Determine the mean data as the damage variable of the target ceramic.

[0112] In detail, the step of filtering the experimental data according to the damage index to obtain the damage index data in the experimental data refers to setting corresponding output variables in the finite element analysis software according to the selected damage index, extracting the values ​​of these variables at the location of interest or in the global range, and determining the extracted values ​​as the damage index data in the experimental data.

[0113] In detail, the calculation of the mean of the damage index data refers to averaging the data of multiple samples to obtain the mean data of the damage index data. This can eliminate the random error and fluctuation of the data and obtain more reliable and stable damage index data.

[0114] In detail, the damage variable can be used to assess the degree of damage to the target ceramic.

[0115] S4. Generate the fracture toughness index of the target ceramic using a preset fracture toughness index algorithm and the damage variable.

[0116] In this embodiment of the invention, generating the fracture toughness index of the target ceramic using a preset fracture toughness index algorithm and the damage variable means using a preset fracture toughness index algorithm to transform the damage variable into the fracture toughness index of the target ceramic. That is, the damage variable is substituted into the calculation formula according to the preset fracture toughness index algorithm, the calculation is performed, and the fracture toughness index of the target ceramic is obtained.

[0117] In detail, the algorithm for the preset fracture toughness index is as follows:

[0118]

[0119] Wherein, K is the fracture toughness index of the target ceramic, Y is the geometric factor, σ is the stress intensity factor of the target ceramic, and a is the crack length of the target ceramic.

[0120] In detail, the fracture toughness index K is an important parameter for measuring a material's ability to resist fracture.

[0121] Specifically, the unit of the fracture toughness index K is MPa·m. 0.5The geometric factor Y is generally in the range of 1.12-1.35, depending on the geometry of the specimen; the stress intensity factor σ of the target ceramic is in MPa·m. 0.5 The crack length σ of the target ceramic is in meters (m).

[0122] Furthermore, the stress intensity factor σ of the target ceramic can be determined based on the applied force, the specimen width, and the distance from the load point to the crack tip.

[0123] S5. Generate the fracture toughness curve of the target ceramic based on the fracture toughness index and the experimental data, and perform fracture toughness analysis on the target ceramic based on the fracture toughness curve.

[0124] In this embodiment of the invention, generating the fracture toughness curve of the target ceramic based on the fracture toughness index and the experimental data includes:

[0125] Establish the data correlation between the fracture toughness index and the experimental data;

[0126] Data points for the target ceramic are generated based on the data correlation.

[0127] The fracture toughness curve of the target ceramic is plotted based on the data points.

[0128] In detail, the establishment of the data correlation between the fracture toughness index and the experimental data can be achieved by using regression analysis to determine the mathematical relationship between the fracture toughness index and the experimental data. By establishing the data correlation, the experimental data and the fracture toughness index can be linked, thereby enabling data transformation and analysis in subsequent steps.

[0129] In detail, based on the established data correlations, experimental data and fracture toughness indices are used to transform the data into data points for the target ceramic. According to the different characteristics of the experimental data and the definition of the fracture toughness indices, the experimental data can be mapped to the corresponding fracture toughness indices, generating corresponding data points. These data points represent the fracture toughness of the target ceramic under different conditions.

[0130] Specifically, based on the generated data points, a fracture toughness curve of the target ceramic is plotted. Connecting the data points in a specific order yields the shape of the fracture toughness curve. This curve can demonstrate the fracture toughness characteristics of the target ceramic under different conditions, such as strength and ductility.

[0131] In this embodiment of the invention, the fracture toughness analysis of the target ceramic based on the fracture toughness curve includes: analyzing the shape of the curve to determine the basic characteristics of the target ceramic. For example, the upward trend and inflection point of the curve can reflect the strength and ductility of the material, while the downward trend of the curve may indicate the brittleness and failure mode of the material; evaluating the fracture toughness of the target ceramic based on the specific values ​​and shape of the fracture toughness curve, that is, the fracture toughness of the target ceramic can be quantified based on the slope, peak value, area, and other characteristics of the curve. These indicators can be used to compare the fracture toughness performance of different materials or to evaluate the performance differences of the same material under different conditions; and predicting the failure behavior of the target ceramic under stress conditions based on the fracture toughness curve. For example, the shape and trend of the curve can be used to determine whether the material fractures under tensile, compressive, or shear loads.

[0132] This invention constructs a finite element model of the target ceramic, enabling simulation experiments on a computer. This avoids the need for preparing large numbers of samples and conducting time-consuming tests. Experimental data for the target ceramic is generated directly from the finite element model, eliminating the need for actual physical experiments. This allows for faster acquisition of the required data. Damage variables of the target ceramic are calculated using the experimental data. A pre-defined fracture toughness index algorithm, combined with the damage variables, is used to calculate the fracture toughness index of the target ceramic. This index quantitatively describes the fracture resistance of the ceramic. A fracture toughness curve of the target ceramic is generated based on the fracture toughness index and the experimental data. This curve provides a more intuitive understanding of the material's fracture performance and its relationship with crack length. Therefore, this invention proposes a recommended method for ceramic fracture toughness analysis, which solves the problem of low efficiency in ceramic fracture toughness analysis.

[0133] like Figure 4 The diagram shown is a functional block diagram of a ceramic fracture toughness analysis device provided in an embodiment of the present invention.

[0134] The ceramic fracture toughness analysis device 100 of this invention can be installed in an electronic device. Depending on the functions it performs, the ceramic fracture toughness analysis device 100 may include a finite element model construction module 101, an experimental data generation module 102, a damage variable calculation module 103, a fracture toughness index generation module 104, and a fracture toughness analysis module 105. The module described in this invention can also be called a unit, referring to a series of computer program segments that can be executed by the processor of an electronic device and perform a fixed function, stored in the memory of the electronic device.

[0135] In this embodiment, the functions of each module / unit are as follows:

[0136] The finite element model construction module 101 is used to construct the finite element model of the target ceramic.

[0137] The experimental data generation module 102 is used to generate experimental data of the target ceramic based on the finite element model.

[0138] The damage variable calculation module 103 is used to calculate the damage variable of the target ceramic based on the experimental data;

[0139] The fracture toughness index generation module 104 is used to generate the fracture toughness index of the target ceramic using a preset fracture toughness index algorithm and the damage variable, wherein the preset fracture toughness index algorithm is:

[0140]

[0141] Wherein, K is the fracture toughness index of the target ceramic, Y is the geometric factor, σ is the stress intensity factor of the target ceramic, and a is the crack length of the target ceramic;

[0142] The fracture toughness analysis module 105 is used to generate a fracture toughness curve of the target ceramic based on the fracture toughness index and the experimental data, and to perform fracture toughness analysis on the target ceramic based on the fracture toughness curve.

[0143] In the several embodiments provided by this invention, it should be understood that the disclosed methods and apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0144] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed across multiple network elements. Some or all of the modules may be selected to achieve the purpose of the solution of this embodiment according to actual needs.

[0145] In addition, the functional modules in various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or hardware plus software functional modules.

[0146] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0147] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence (AI) refers to the theories, methods, technologies, and application devices that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0148] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices recited in a device claim may also be implemented by a single unit or device through software or hardware. The terms "first," "second," etc., are used to indicate names and do not indicate any specific order.

Claims

1. A method for analyzing the fracture toughness of ceramics, characterized in that, The method includes: Constructing a finite element model of the target ceramic includes: Generating the geometric model of the target ceramic includes: The parameters of the preset scanning device are configured according to the target ceramic to obtain the configured scanning device; The target ceramic is scanned using the configured scanning device to obtain the scan data of the target ceramic; Converting the scanned data into three-dimensional point cloud data, and generating a geometric model of the target ceramic based on the three-dimensional point cloud data, includes: filtering the three-dimensional point cloud data using a preset filtering algorithm to obtain filtered data of the three-dimensional point cloud data, wherein the preset filtering algorithm is: ,in, It is the weight distribution of data points in the three-dimensional point cloud data. It is the x-coordinate of each point in the 3D point cloud data. It is the mean of the weight distribution. It is the ordinate of each point in the three-dimensional point cloud data. It is the standard deviation of the weight distribution; The filtered data is reconstructed to obtain a triangular mesh model of the filtered data; The triangular mesh model is smoothed to obtain a smoothed model of the triangular mesh model, and the smoothed model is determined to be the geometric model of the target ceramic. The target ceramic is discretized based on the geometric model to obtain a mesh model of the target ceramic. The material properties of the mesh model are configured to obtain the configuration model of the mesh model; Generate the boundary conditions of the configuration model, and construct the finite element model of the target ceramic based on the boundary conditions and the configuration model; Experimental data for the target ceramic were generated based on the finite element model. The damage variable of the target ceramic is calculated based on the experimental data. The fracture toughness index of the target ceramic is generated using a preset fracture toughness index algorithm and the damage variable, wherein the preset fracture toughness index algorithm is as follows: ,in, It is the fracture toughness index of the target ceramic. It is a geometric factor. It is the stress intensity factor of the target ceramic. It is the crack length of the target ceramic; The fracture toughness curve of the target ceramic is generated based on the fracture toughness index and the experimental data, and the fracture toughness analysis of the target ceramic is performed based on the fracture toughness curve.

2. The ceramic fracture toughness analysis method as described in claim 1, characterized in that, The process of generating the geometric model of the target ceramic includes: Collect the three-dimensional geometric shape information of the target ceramic; A geometric model of the target ceramic is generated based on the three-dimensional geometric information.

3. The ceramic fracture toughness analysis method as described in claim 1, characterized in that, The experimental data for generating the target ceramic based on the finite element model includes: Finite element analysis is performed on the target ceramic based on the finite element model to obtain the finite element data of the target ceramic. The target data of the limited metadata is extracted to obtain the target data of the limited metadata, and the target data is determined to be the experimental data of the target ceramic.

4. The ceramic fracture toughness analysis method as described in claim 1, characterized in that, The calculation of the damage variable of the target ceramic based on the experimental data includes: Determine the damage index of the target ceramic; The damage variable of the target ceramic is calculated based on the experimental data and the damage index.

5. The ceramic fracture toughness analysis method as described in claim 4, characterized in that, The calculation of the damage variable of the target ceramic based on the experimental data and the damage index includes: The experimental data is filtered according to the damage index to obtain the damage index data in the experimental data. The mean of the damage index data is calculated to obtain the mean data of the damage index data; The mean data is determined as the damage variable of the target ceramic.

6. The method for analyzing the fracture toughness of ceramics as described in any one of claims 1 to 5, characterized in that, The step of generating the fracture toughness curve of the target ceramic based on the fracture toughness index and the experimental data includes: Establish the data correlation between the fracture toughness index and the experimental data; Data points for the target ceramic are generated based on the data correlation. The fracture toughness curve of the target ceramic is plotted based on the data points.

7. A ceramic fracture toughness analysis device, characterized in that, The apparatus is used to implement the ceramic fracture toughness analysis method as described in claim 1, and the apparatus comprises: The finite element model building module is used to build the finite element model of the target ceramic. An experimental data generation module is used to generate experimental data for the target ceramic based on the finite element model. The damage variable calculation module is used to calculate the damage variable of the target ceramic based on the experimental data. A fracture toughness index generation module is used to generate a fracture toughness index of the target ceramic using a preset fracture toughness index algorithm and the damage variable, wherein the preset fracture toughness index algorithm is: in, It is the fracture toughness index of the target ceramic. It is a geometric factor. It is the stress intensity factor of the target ceramic. It is the crack length of the target ceramic; The fracture toughness analysis module is used to generate the fracture toughness curve of the target ceramic based on the fracture toughness index and the experimental data, and to perform fracture toughness analysis on the target ceramic based on the fracture toughness curve.

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