Method and system for analyzing performance response of particle dispersion type composite material

Abstract

The application discloses a particle dispersion type composite material performance response analysis method and system, relates to the technical field of nuclear fuel, nuclear material design and analysis, and comprises the following steps: determining particle dispersion type composite material data and dispersion particle data; establishing a geometric model according to the determined data; generating a polyhedral structure through a Voronoi space division algorithm; counting the number and volume of the generated polyhedrons, and judging whether the condition is met; calculating the residual volume of the polyhedrons, converting the volume of each polyhedron into a representative unit geometric size, and counting the distribution of the representative unit geometric size; performing geometric modeling and calculation on the representative unit geometric size, analyzing the relationship between the geometric size and performance, and finally determining the failure probability distribution of the dispersion particles. The application establishes the relationship and evaluation method between the equivalent geometric size and the quantitative performance of the dispersion particles, obtains the key parameters of the quantitative performance of the dispersion particles, and gives an improved guidance direction.

Description

Technical Field

[0001] This invention relates to the field of nuclear fuel and nuclear material design and analysis technology, and in particular to a method and system for analyzing the performance response of particulate dispersion composite materials. Background Technology

[0002] Particulate dispersion composites are composite materials in which inclusions are dispersed within a matrix material. These inclusions can be materials in the form of fibers, particles, etc., and can act as reinforcing or functional materials, thus endowing the composite material with unique properties and functions. In particulate dispersion composites, the particles are uniformly dispersed within the matrix material and work synergistically with it to achieve their intended effect.

[0003] Particulate dispersion composites possess many unique characteristics and advantages. First, particles can effectively enhance the mechanical properties of the matrix material. Second, different types of particles can endow composites with diverse functions, meeting the performance and functional requirements of various fields. Furthermore, the interfacial effect between particles and the matrix material is also a crucial factor influencing the performance of composites; improving the interface can enhance the overall performance of the composite material.

[0004] The wide range of applications for particulate dispersion composites covers multiple fields such as aerospace, automotive, construction, and electronics. In the field of materials science, the optimization design and performance improvement of particulate dispersion composites is a hot topic of research. Through continuous innovation and development, it is hoped that more competitive and widely applicable particulate dispersion composite products can be developed.

[0005] However, due to the complex structure of particulate dispersion composites, factors such as particle size, shape, and distribution affect their properties. The interface between particles and the matrix has a significant impact on composite performance, including interfacial adhesion and stress transfer. To accurately simulate the microstructure formed by particle dispersion, contact deformation between particles, and nonlinear interfacial effects between particles and the matrix, conventional numerical simulation methods only increase the complexity and computational cost. Therefore, a comprehensive and representative performance response calculation method needs to be developed to better understand and predict the properties of particulate dispersion materials.

[0006] To overcome the inapplicability of conventional simulation methods to novel composite materials, the purpose of this invention is to provide a performance response calculation method for particulate dispersion composite materials used in nuclear fuels and nuclear materials, serving as a reference for the design and optimization of particulate dispersion composite materials. Summary of the Invention

[0007] In view of the above-mentioned problems, the present invention is proposed.

[0008] Therefore, the problem to be solved by this invention is: how to solve the problem that conventional simulation methods are not applicable to novel composite materials.

[0009] To address the aforementioned technical problems, this invention provides the following technical solution: a method for performance response analysis of particulate dispersion composite materials, comprising: determining particulate dispersion composite material data and dispersed particle data; establishing a geometric model based on the determined data; generating polyhedral structures based on the distribution of particles in the matrix material using a Voronoi space partitioning algorithm according to the established geometric model; statistically analyzing the number and volume of the generated polyhedra and determining whether they meet the judgment conditions; for polyhedra that meet the judgment conditions, calculating the remaining volume of the polyhedrons, converting the volume of each polyhedron into representative element geometric dimensions, and statistically analyzing the distribution of representative element geometric dimensions; performing geometric modeling and calculation on the representative element geometric dimensions, analyzing the relationship between geometric dimensions and performance, and finally determining the failure probability distribution of dispersed particles.

[0010] As a preferred embodiment of the performance response analysis method for particulate dispersion composite materials according to the present invention, the particulate dispersion composite material data includes the geometric shape, size, and structural characteristics of the particulate dispersion composite material, and determines whether to distinguish between the dispersion region and the non-dispersion region; the dispersed particle data includes the geometric shape, size, structural characteristics, distribution, and distribution characteristics of the dispersed particles.

[0011] As a preferred embodiment of the performance response analysis method for particulate dispersion composite materials according to the present invention, the geometric model includes a centroid position geometric model and a dispersion region geometric model. The centroid position geometric model includes, based on the determined geometric size, structural characteristics, distribution, or distribution characteristics of the dispersed particles, if the centroid position of the dispersed particles in the matrix material is obtained, writing the centroid position in the order of the dispersed particles into a text file, and reading the centroid position file of the dispersed particles into the geometric modeling software. If the centroid position of the dispersed particles in the matrix material cannot be determined, then, based on the known or assumed distribution characteristics of the dispersed particles, a particle group satisfying the number of dispersed particles is generated in the geometric modeling software using a known or assumed dispersion particle distribution characteristic function. The dispersion region geometric model includes, based on whether to distinguish between dispersed and non-dispersed regions, if dispersed and non-dispersed regions are distinguished in the entire material, then a geometric model of the dispersion region containing dispersed particles is established in the geometric modeling software. If dispersed and non-dispersed regions are not distinguished in the entire material, then a geometric model of the entire material containing dispersed particles is established in the geometric modeling software.

[0012] As a preferred embodiment of the performance response analysis method for particle-dispersed composite materials described in this invention, the polyhedral structure includes: based on the established geometric model, the distribution of particles in the matrix material is partitioned using the Voronoi space algorithm, with the particle positions as spatial points, generating a continuous three-dimensional polyhedral structure composed of perpendicular bisectors of lines connecting two adjacent points; the geometric model of the region containing dispersed particles is composed of multiple continuous three-dimensional polyhedra; the judgment of whether the judgment conditions are met includes counting the number and volume of the generated polyhedra, judging whether the number of polyhedra is consistent with the number of centroid position coordinates, judging the size of the polyhedral volume and the size of the dispersed particle volume; if there is a polyhedral volume that is not greater than the dispersed particle volume and the dispersed particle distribution characteristic function is assumed, then the dispersed particle distribution characteristic function needs to be adjusted, and the operation is repeated to ensure that the polyhedral volume is greater than the dispersed particle volume.

[0013] As a preferred embodiment of the performance response analysis method for particulate dispersion composite materials described in this invention, the following steps are included: calculating the remaining volume of the polyhedrons includes calculating the remaining volume after subtracting the volume of the dispersed particles from the volume of each polyhedron that satisfies two judgment conditions. The remaining volume is considered as the volume of the matrix material surrounding the dispersed particles. The step of converting each polyhedron volume into a representative unit geometric dimension includes converting each polyhedron volume into a representative unit geometric dimension with the same geometric shape as the dispersed particles according to the geometric shape and volume calculation formula of the dispersed particles. This is considered as an equivalent geometric dimension. The difference between the equivalent geometric dimension and the geometric dimension of the dispersed particles is the thickness of the matrix material uniformly surrounding the dispersed particles. The equivalent geometric dimensions are statistically analyzed to determine the statistical distribution. Multiple sets or representative geometric dimensions within the confidence interval are selected as modeling and analysis dimensions.

[0014] As a preferred embodiment of the performance response analysis method for particulate dispersed composite materials described in this invention, the geometric modeling includes: performing geometric modeling of dispersed particles and matrix materials according to multiple sets or representative geometric dimensions, with the model coordinate center being the centroid of the dispersed particles; setting material property parameters, physical field response functions, physical field properties, and boundary conditions; performing parallel calculations on the multiple sets or representative models that have been set; and outputting the quantified performance of dispersed particles under a matrix material of uniform thickness.

[0015] As a preferred embodiment of the performance response analysis method for particulate dispersion composite materials described in this invention, the determination of the failure probability distribution of dispersed particles includes: statistically analyzing the obtained quantified performance characteristics, comparing the obtained equivalent geometric dimension statistical distribution, determining whether the two are correlated, obtaining the correlation coefficient between the two through a correlation index if they are correlated, and evaluating the equivalent geometric dimensions according to the quantified performance characteristics based on segmented ranges if they are not correlated. If the correlation coefficient exists, the relationship between the quantified performance characteristics of dispersed particles under the full range of geometric dimensions is generalized based on the correlation coefficient between the obtained equivalent geometric dimension statistical distribution and the quantified performance characteristics. According to the stress intensity interference theory, the failure probability distribution of dispersed particles in the full time domain can be obtained based on the relationship between the quantified performance characteristics of dispersed particles under the full range of geometric dimensions.

[0016] Another objective of this invention is to provide a system for analyzing the performance response of particulate-dispersed composite materials, which solves the problem of performance response analysis of particulate-dispersed composite materials by constructing such a system.

[0017] To address the aforementioned technical problems, this invention provides the following technical solution: a performance response analysis system for particle-dispersed composite materials, comprising a data acquisition module, a geometric model establishment module, a polyhedral structure partitioning module, a judgment module, a statistical distribution module, and an analysis module; the data acquisition module is used to determine the particle-dispersed composite material data and dispersed particle data; the geometric model establishment module is used to establish a geometric model based on the determined data; the polyhedral structure partitioning module is used to generate polyhedral structures based on the distribution of particles in the matrix material using the Voronoi space partitioning algorithm according to the established geometric model; the judgment module is used to statistically analyze the number and volume of the generated polyhedra and determine whether they meet the judgment conditions; the statistical distribution module is used to calculate the remaining volume of the polyhedra that meet the judgment conditions, convert the volume of each polyhedron into the geometric dimensions of representative elements, and statistically analyze the distribution of the geometric dimensions of representative elements; the analysis module is used to perform geometric modeling and calculation on the geometric dimensions of representative elements, analyze the relationship between geometric dimensions and performance, and finally determine the failure probability distribution of dispersed particles.

[0018] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the performance response analysis method for particulate dispersion composite materials as described above.

[0019] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the performance response analysis method for particulate dispersion composite materials as described above.

[0020] The beneficial effects of this invention are as follows: The performance response analysis method for particulate dispersed composite materials provided by this invention is designed for complex particulate dispersed composite materials. By dividing the space through the centroid position of dispersed particles, the complex material structure is simplified. The calculation method of this invention establishes the relationship or evaluation method between equivalent geometric dimensions and the quantitative performance of dispersed particles. It can be extended to the design optimization of dispersed particles, obtain key parameters for the quantitative performance of dispersed particles, and provide guidance for improvement. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 The flowchart illustrates the performance response analysis method for particulate dispersion composite materials provided in the first embodiment of the present invention.

[0023] Figure 2 This is a structural diagram of the performance response analysis system for particulate dispersed composite materials provided in the second embodiment of the present invention.

[0024] Figure 3 This is a schematic diagram of the particle-dispersed composite material structure, which is the method for analyzing the performance response of particle-dispersed composite materials provided in the third embodiment of the present invention.

[0025] Figure 4 This is a schematic diagram of the Voronoi spatial structure partitioning for the performance response analysis method of particulate dispersed composite materials provided in the third embodiment of the present invention.

[0026] Figure 5 This is a schematic diagram of the equivalent size geometric model of the performance response analysis method for particulate dispersed composite materials provided in the third embodiment of the present invention. Detailed Implementation

[0027] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0028] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0029] Example 1 Reference Figure 1 This is the first embodiment of the present invention, which provides a method for performance response analysis of particulate dispersion composite materials, including: determining particulate dispersion composite material data and dispersed particle data; establishing a geometric model based on the determined data; generating polyhedral structures based on the distribution of particles in the matrix material using the Voronoi space partitioning algorithm according to the established geometric model; counting the number and volume of the generated polyhedra and determining whether they meet the judgment conditions; for polyhedra that meet the judgment conditions, calculating the remaining volume of the polyhedrons, converting the volume of each polyhedron into representative element geometric dimensions, and counting the distribution of representative element geometric dimensions; performing geometric modeling and calculation on the representative element geometric dimensions, analyzing the relationship between geometric dimensions and performance, and finally determining the failure probability distribution of dispersed particles.

[0030] Step 1: Determine the geometry, size, and structural characteristics of the particle dispersion composite material. Determine whether to distinguish between dispersed and non-dispersed regions. Depending on the composite material manufacturing process, some composite materials are directly manufactured as a mixed dispersion, while others are mixed dispersion followed by an outer coating layer of another single material, matrix material, or other mixed dispersion material. Determine the geometry, size, structural characteristics, distribution, and distribution features of the dispersed particles.

[0031] Step 2: Based on the geometric dimensions, structural features, distribution, or distribution characteristics of the dispersed particles determined in Step 1, if the centroid position of the dispersed particles in the matrix material is obtained through cross-sectional scanning or related techniques, the centroid position is written into a text file in the order of the dispersed particles, and the centroid position file of the dispersed particles is read into the geometric modeling software. If the centroid position of the dispersed particles in the matrix material cannot be determined, a particle group that satisfies the number of dispersed particles is generated in the geometric modeling software using the known or assumed distribution characteristics of the dispersed particles and the known or assumed distribution characteristic function of the dispersed particles.

[0032] Step 3: Based on the determined dispersed and non-dispersed regions, if the entire material is divided into dispersed and non-dispersed regions, then a geometric model containing the dispersed regions of dispersed particles is created in the geometric modeling software. If the entire material is not divided into dispersed and non-dispersed regions, then a geometric model of the entire material containing the dispersed particles is created in the geometric modeling software.

[0033] Step 4: Based on the geometric model established in Step 2 and Step 3, the distribution of particles in the matrix material is divided by the Voronoi space partitioning algorithm. The positions of the dispersed particles are used as spatial points to generate a continuous three-dimensional polyhedron structure composed of perpendicular bisecting planes of straight lines connecting two adjacent points. The geometric model of the region containing dispersed particles is composed of multiple continuous three-dimensional polyhedra.

[0034] Step 5: Count the number and volume of the multiple polyhedra generated in Step 4, and determine whether the number of polyhedra is consistent with the number of centroid position coordinates. Determine the size of the polyhedron volume and the size of the dispersed particle volume. If there is a polyhedron volume that is not greater than the dispersed particle volume and the dispersed particle distribution characteristic function is assumed, then the dispersed particle distribution characteristic function in Step 2 needs to be adjusted. Repeat Steps 2-5 to ensure that the polyhedron volume is greater than the dispersed particle volume. Determining that the two are consistent is to generate a sample that meets the requirements of quantity or dispersed particle volume filling ratio, because the numerical model is definitely the same as the actual composite material sample.

[0035] Step 6: For the volume of the polyhedron that satisfies the two judgment conditions in Step 5, calculate the remaining volume after subtracting the volume of the dispersed particles from the volume of each polyhedron. The remaining volume is regarded as the volume of the matrix material surrounding the dispersed particles.

[0036] Step 7: Convert the volume of each polyhedron into a representative unit geometric dimension that is the same as the geometric dimension of the dispersed particles according to the geometry and volume calculation formula of the dispersed particles. This geometric dimension is regarded as the equivalent geometric dimension. The difference between the equivalent geometric dimension and the geometric dimension of the dispersed particles is the thickness of the matrix material uniformly surrounding the dispersed particles. The volume calculation formula depends on the specific shape. Some regular shapes have fixed formulas, such as spheres, while others involve integrals or other calculation methods.

[0037] Step 8: Statistically analyze each equivalent geometric dimension to determine its statistical distribution, and select multiple groups or representative geometric dimensions within the confidence interval as the modeling and analysis dimensions for subsequent steps.

[0038] Step 9: In numerical analysis software or numerical performance analysis program, perform geometric modeling of the dispersed particles and matrix material according to the multiple sets or representative geometric dimensions selected in step 8. The model coordinate center is the centroid of the dispersed particles. Set the material property parameters, the material's physical field response function, physical field properties, and boundary conditions.

[0039] Step 10: Perform parallel calculations on multiple groups or representative models set up in Step 9, and output the quantified performance of dispersed particles under a matrix material of uniform thickness using numerical analysis software or numerical performance analysis program.

[0040] Step 11: Perform statistical analysis on the quantitative performance obtained in Step 10, and compare it with the statistical distribution of the equivalent geometric dimensions obtained in Step 8 to determine whether the two are correlated. If they are correlated, the correlation coefficient between them can be obtained through the correlation index. If they are not correlated, the equivalent geometric dimensions are evaluated according to the quantitative performance by segmenting the equivalent geometric dimensions. The correlation judgment is actually whether the quantitative performance has a certain probability distribution form, such as uniform distribution. If the corresponding geometric dimensions are also uniformly distributed, then there is a correlation. This can be determined by statistical analysis.

[0041] Step 12: If the correlation coefficient exists, then based on the correlation coefficient between the statistical distribution of equivalent geometric dimensions and the quantization performance obtained in Step 11, the relationship between the quantization performance of dispersed particles under geometric dimensions across the entire range is generalized to obtain the relationship between the quantization performance of dispersed particles.

[0042] Step 13: Based on the stress intensity interference theory, the failure probability distribution of dispersed particles in the entire time domain can be obtained based on the quantitative performance relationship of dispersed particles under the geometric size of the entire range.

[0043] Numerical analysis software or numerical performance analysis programs include multi-scale, multi-physics, and multi-scale multi-physics coupling analysis programs; geometric modeling software includes various software applied in the field of industrial design.

[0044] Example 2 Reference Figure 2 This is the second embodiment of the present invention, which differs from the previous embodiment in that it provides a performance response analysis system for particle-dispersed composite materials, including: a data acquisition module, a geometric model establishment module, a polyhedral structure division module, a judgment module, a statistical distribution module, and an analysis module.

[0045] The data acquisition module is used to determine the data of the particle-dispersed composite material and the dispersed particle data.

[0046] The geometric model building module is used to build a geometric model based on the given data.

[0047] The polyhedral structure partitioning module is used to generate polyhedral structures based on the distribution of particles in the matrix material according to the established geometric model using the Voronoi space partitioning algorithm.

[0048] The judgment module is used to count the number and volume of the generated polyhedra and determine whether they meet the judgment conditions.

[0049] The statistical distribution module is used to calculate the remaining volume of a polyhedron that meets the judgment conditions, convert the volume of each polyhedron into the geometric dimensions of a representative element, and statistically analyze the distribution of the geometric dimensions of the representative element.

[0050] The analysis module is used to perform geometric modeling and calculation of the geometric dimensions of representative units, analyze the relationship between geometric dimensions and performance, and finally determine the failure probability distribution of dispersed particles.

[0051] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0052] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0053] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0054] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0055] Example 3 Reference Figures 3-5 This is the third embodiment of the present invention, which differs from the previous two embodiments in that it is used to verify and explain the technical effects adopted in the present invention, so as to verify the real effect of the method.

[0056] Step 1, as follows Figure 3 As shown, the geometry of the particulate dispersion composite material is determined to be a cube, and the dimensions are determined according to... Figure 1 The composite material can be divided into a dispersed region and a non-dispersed region. The geometry of the dispersed particles is defined as cubic and their size is defined. The dispersed particles are distributed within the dispersed region.

[0057] Step 2: Based on the geometric dimensions, structural features, distribution, or distribution characteristics of the dispersed particles determined in Step 1, if the centroid position of the dispersed particles in the matrix material is obtained through cross-sectional scanning or related techniques, the centroid position is written into a text file in the order of the dispersed particles, and the centroid position file of the dispersed particles is read into the geometric modeling software. If the centroid position of the dispersed particles in the matrix material cannot be determined, a particle group that satisfies the number of dispersed particles is generated in the geometric modeling software using the known or assumed distribution characteristics of the dispersed particles and the known or assumed distribution characteristic function of the dispersed particles.

[0058] Step 3: Based on the determined dispersed and non-dispersed regions, if the entire material is divided into dispersed and non-dispersed regions, then a geometric model containing the dispersed regions of dispersed particles is created in the geometric modeling software. If the entire material is not divided into dispersed and non-dispersed regions, then a geometric model of the entire material containing the dispersed particles is created in the geometric modeling software.

[0059] Step 4: Based on the geometric model established in Steps 2 and 3, the distribution of particles in the matrix material is analyzed using the Voronoi spatial partitioning algorithm. Using the particle positions as spatial points, a continuous three-dimensional polyhedron structure is generated, composed of perpendicular bisectors of lines connecting adjacent points. The geometric model of the region containing dispersed particles is then composed of multiple continuous three-dimensional polyhedra, such as... Figure 4 As shown.

[0060] Step 5: Count the number and volume of the multiple polyhedra generated in Step 4, determine whether the number of polyhedra is consistent with the number of centroid position coordinates, and determine the size of the polyhedron volume and the size of the dispersed particle volume. If there is a polyhedron volume that is not greater than the dispersed particle volume and the dispersed particle distribution characteristic function is assumed, then the dispersed particle distribution characteristic function in Step 2 needs to be adjusted, and Steps 2-5 are repeated to ensure that the polyhedron volume is greater than the dispersed particle volume.

[0061] Step 6: For the volume of the polyhedron that satisfies the two judgment conditions in Step 5, calculate the remaining volume after subtracting the volume of the dispersed particles from the volume of each polyhedron. The remaining volume is regarded as the volume of the matrix material surrounding the dispersed particles.

[0062] Step 7: Convert the volume of each polyhedron into a representative unit geometric dimension that is the same as the geometric dimension of the dispersed particles according to the geometric shape and volume calculation formula of the dispersed particles. This geometric dimension is regarded as the equivalent geometric dimension. The difference between the equivalent geometric dimension and the geometric dimension of the dispersed particles is the thickness of the matrix material uniformly surrounding the dispersed particles.

[0063] Step 8: Statistically analyze each equivalent geometric dimension to determine its statistical distribution, and select multiple or representative geometric dimensions within the confidence interval as the dimensions for modeling and analysis in subsequent steps, such as... Figure 5 As shown.

[0064] Step 9: In numerical analysis software or numerical performance analysis program, perform geometric modeling of the dispersed particles and matrix material according to the multiple sets or representative geometric dimensions selected in step 8. The model coordinate center is the centroid of the dispersed particles. Set the material property parameters, the material's physical field response function, physical field properties, and boundary conditions.

[0065] Step 10: Perform parallel calculations on multiple groups or representative models set up in Step 9. The numerical analysis software or numerical performance analysis program outputs the quantitative performance of the dispersed particles under a matrix material of uniform thickness, such as tangential stress, first principal stress, and maximum internal temperature.

[0066] Step 11: Perform statistical analysis on the quantified performance obtained in Step 10, and compare it with the statistical distribution of the equivalent geometric dimensions obtained in Step 8 to determine whether the two are correlated. If they are correlated, the correlation coefficient can be obtained by selecting correlation indexes such as Pearson correlation coefficient (linear relationship) or Spearman correlation coefficient (non-linear relationship). If they are not correlated, evaluate the equivalent geometric dimensions according to the quantified performance in n segments. For example, if the quantified performance of dispersed particles in the intervals [0, di] and [dj, dn] is lower than the safety target value, such as tangential stress, first principal stress, and highest internal temperature, while the quantified performance in the interval [di, dj] is higher than the safety target value, there may be a risk.

[0067] Step 12: If the correlation coefficient exists, then based on the correlation coefficient between the statistical distribution of equivalent geometric dimensions and the quantization performance obtained in Step 11, the relationship between the quantization performance of dispersed particles under geometric dimensions across the entire range is generalized to obtain f=F(d).

[0068] Step 13: Based on the stress intensity interference theory, the failure probability distribution of dispersed particles in the whole time domain can be obtained by using the quantitative performance relationship f=F(d) of dispersed particles under the geometric size of the whole range.

[0069] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for analyzing the performance response of particulate dispersion composite materials, characterized in that: include, Determine the data for particulate dispersion composite materials and dispersed particle data; Establish a geometric model based on the determined data; Based on the established geometric model, the distribution of particles in the matrix material is used to generate a polyhedral structure through the Voronoi space partitioning algorithm. Count the number and volume of the generated polyhedra, and determine whether they meet the judgment criteria; For polyhedra that meet the judgment conditions, calculate the remaining volume of the polyhedron, convert the volume of each polyhedron into the geometric dimensions of representative elements, and statistically analyze the distribution of the geometric dimensions of representative elements. Geometric modeling and calculation of representative unit geometry are performed, the relationship between geometry and performance is analyzed, and the failure probability distribution of dispersed particles is finally determined. The calculation of the remaining volume of the polyhedron includes calculating the remaining volume after subtracting the volume of the dispersed particles from the volume of each polyhedron that meets the two judgment conditions. The remaining volume is regarded as the volume of the matrix material surrounding the dispersed particles. The process of converting the volume of each polyhedron into a representative unit geometric dimension includes converting the volume of each polyhedron into a representative unit geometric dimension with the same geometric shape as the dispersed particles according to the geometry and volume calculation formula of the dispersed particles. This is considered as an equivalent geometric dimension. The difference between the equivalent geometric dimension and the geometric dimension of the dispersed particles is the thickness of the matrix material uniformly surrounding the dispersed particles. The equivalent geometric dimensions are statistically analyzed to determine the statistical distribution. Multiple sets or representative geometric dimensions within the confidence interval are selected as the modeling and analysis dimensions.

2. The method for analyzing the performance response of particulate dispersion composite materials as described in claim 1, characterized in that: The data of the particulate dispersion composite material includes the geometry, size, and structural characteristics of the particulate dispersion composite material, and determines whether to distinguish between the dispersion region and the non-dispersion region; The dispersed particle data includes the geometry, size, structural features, distribution, and distribution characteristics of the dispersed particles.

3. The method for analyzing the performance response of particulate dispersion composite materials as described in claim 2, characterized in that: The geometric model includes a centroid location geometric model and a diffusion region geometric model; The centroid position geometric model includes, based on the determined geometric size, structural features, distribution, or distribution characteristics of the dispersed particles, if the centroid position of the dispersed particles in the matrix material is obtained, then the centroid position is written into a text file in the order of the dispersed particles, and the centroid position file of the dispersed particles is read into the geometric modeling software. If the centroid position of the dispersed particles in the matrix material cannot be determined, then based on the known or assumed distribution characteristics of the dispersed particles, a particle group that satisfies the number of dispersed particles is generated in the geometric modeling software using a known or assumed dispersion particle distribution characteristic function. The geometric model of the dispersion region includes, depending on whether dispersion and non-dispersion regions are distinguished, if dispersion and non-dispersion regions are distinguished in the entire material, then a geometric model of the dispersion region containing dispersion particles is established in the geometric modeling software; if dispersion and non-dispersion regions are not distinguished in the entire material, then a geometric model of the entire material containing dispersion particles is established in the geometric modeling software.

4. The method for analyzing the performance response of particulate dispersion composite materials as described in claim 3, characterized in that: The polyhedral structure includes a continuous three-dimensional polyhedral structure composed of perpendicular bisecting planes connecting two adjacent points, generated by using the position of the dispersed particles as spatial points, based on the established geometric model and the distribution of particles in the matrix material through the Voronoi spatial partitioning algorithm. The geometric model of the region containing dispersed particles is composed of multiple continuous three-dimensional polyhedra. The determination of whether the conditions are met includes counting the number and volume of multiple polyhedra generated, determining whether the number of polyhedra is consistent with the number of centroid position coordinates, determining the size of the polyhedron volume and the size of the dispersed particle volume. If there is a polyhedron volume that is not greater than the dispersed particle volume and the dispersed particle distribution characteristic function is assumed, then the dispersed particle distribution characteristic function needs to be adjusted, and the operation is repeated to ensure that the polyhedron volume is greater than the dispersed particle volume.

5. The method for analyzing the performance response of particulate dispersion composite materials as described in claim 4, characterized in that: The geometric modeling includes geometrically modeling the dispersed particles and matrix material according to multiple selected sets or representative geometric dimensions. The model coordinate center is the centroid of the dispersed particles, and material property parameters, physical field response function, physical field properties, and boundary conditions are set. Parallel computation is performed on multiple or representative models that have been configured, and the quantified performance of dispersed particles in a matrix material with uniform thickness is output.

6. The method for analyzing the performance response of particulate dispersion composite materials as described in claim 5, characterized in that: The determination of the failure probability distribution of dispersed particles includes statistical analysis of the obtained quantified performance, comparison with the obtained statistical distribution of equivalent geometric dimensions, and determination of whether the two are correlated. If the two are correlated, the correlation coefficient between the two is obtained through the correlation index. If the two are not correlated, the equivalent geometric dimensions are evaluated according to the quantified performance and the equivalent geometric dimensions are evaluated according to the segmented range. If a correlation coefficient exists, then based on the correlation coefficient between the obtained equivalent geometric size statistical distribution and the quantization performance, the relationship between the quantization performance of dispersed particles under the geometric size range can be generalized to obtain the relationship between the quantization performance of dispersed particles under the geometric size range. Based on the stress intensity interference theory, the failure probability distribution of dispersed particles in the entire time domain can be obtained by using the quantitative performance relationship of dispersed particles under geometric dimensions across the entire range.

7. A system employing the performance response analysis method for particulate dispersion composite materials as described in any one of claims 1 to 6, characterized in that: It includes a data acquisition module, a geometric model building module, a polyhedral structure division module, a judgment module, a statistical distribution module, and an analysis module; The data acquisition module is used to determine the data of the particulate dispersion composite material and the dispersed particle data; The geometric model building module is used to build a geometric model based on the determined data; The polyhedral structure partitioning module is used to generate polyhedral structures based on the distribution of particles in the matrix material according to the established geometric model using the Voronoi space partitioning algorithm. The judgment module is used to count the number and volume of the generated polyhedra and determine whether they meet the judgment conditions. The statistical distribution module is used to calculate the remaining volume of a polyhedron that meets the judgment conditions, convert the volume of each polyhedron into the geometric dimensions of a representative unit, and statistically analyze the distribution of the geometric dimensions of the representative unit. The analysis module is used to perform geometric modeling and calculation of the geometric dimensions of representative units, analyze the relationship between geometric dimensions and performance, and finally determine the failure probability distribution of dispersed particles.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the method for analyzing the performance response of particulate dispersed composite materials according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the method for analyzing the performance response of particulate dispersion composite materials as described in any one of claims 1 to 6.

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