A method for constructing a particle multi-scale coupling model

Abstract

This invention, pertaining to the field of railway systems, provides a method for constructing a particle multiscale coupling model. The method comprises: experimental data collection, construction of an original DEM model, three-dimensional graphical analysis, motion behavior analysis, parameter adjustment, construction of additional models, model fusion, and multiscale calibration. Through contact-scale tests, Los Angeles abrasion tests, single-piece ballast crushing tests, and unidirectional cyclic loading tests, the present invention enriches the model's parameters and improves simulation accuracy. Parameter optimization through laser scanning and particle image velocimetry techniques enables calibration of model parameters, reducing the deviation between model predictions and actual results.

Description

Technical Field

[0001] The present invention relates to the field of railway systems, and in particular to a method for constructing a particle multi-scale coupling model. Background Art

[0002] A typical railway system consists of trains and tracks. The track primarily consists of rails, sleepers, fasteners, trackbed, and roadbed. As a critical component, the trackbed has the following functions: ensuring track geometry, transmitting and neutralizing train loads, and providing primary drainage. Ballasted trackbeds are typically paved with graded crushed stone, a non-renewable resource. The construction of new lines and the maintenance and repair of ballasted trackbeds consume large quantities of graded crushed stone, and mining of resources such as mountains is prohibited. The performance of bulk granular materials, such as ballast, is impacted by multiple scales: particle degradation / aging, overall particle deformation, and inter-particle contact.

[0003] In early research methods, laboratory tests were only conducted at the particle scale or particle collection scale, rarely at the contact scale, and no comprehensive multi-scale test evaluation was achieved by combining different scales. Experimental measurement of particle degradation is based on changes in the overall particle size, which has low accuracy. At the same time, the movement and rotation of individual particles determine the overall deformation of the particles, but early research methods only measured the acceleration of particles or particle collections without considering particle movement and rotation. For numerical simulation of particles, the model is also only performed at the particle scale or particle collection scale, and the model parameters are also calibrated based on tests at the particle scale or collection scale. The movement and rotation of particles cannot be corrected in the model, resulting in a large deviation between the model prediction results and the actual results. Summary of the Invention

[0004] In order to overcome the deficiencies of the prior art, the present invention aims to provide a method for constructing a particle multi-scale coupling model to improve the model prediction accuracy and calibrate the model parameters.

[0005] To achieve the above object, the present invention provides the following solutions:

[0006] A method for constructing a particle multi-scale coupling model, comprising:

[0007] The target particles were subjected to contact scale tests, Los Angeles abrasion tests, single ballast crushing tests, and unidirectional cyclic loading tests to obtain microscopic contact behavior data, wear rate data, crushing pressure data, and deformation data.

[0008] A model is constructed using a discrete element method according to the microscopic contact behavior data, the wear rate data, the crushing pressure data, and the deformation data to obtain an original DEM model;

[0009] During the unidirectional cyclic load test, the target particles are laser scanned to obtain a three-dimensional image, and the three-dimensional image is subjected to a particle degradation assessment to obtain a particle degradation index;

[0010] Using particle image velocimetry technology to measure the motion behavior of individual particles in the three-dimensional graph to obtain motion behavior data;

[0011] Adjusting parameters of the original DEM model using the particle degradation index and the movement behavior data to obtain an improved DEM model;

[0012] Use the finite element method to build track and roadbed models, and use multi-body dynamics analysis to build train dynamic behavior models;

[0013] fusing the improved DEM model, the track and roadbed model, and the train dynamics behavior model to obtain a multi-scale coupling model;

[0014] The multi-scale coupling model is used to perform simulation to obtain simulation results. The multi-scale coupling model is multi-scale calibrated according to the simulation results, the microscopic contact behavior data, the wear rate data, the crushing pressure data and the deformation data, and the standard completed multi-scale coupling model is output.

[0015] Preferably, the microscopic contact behavior data includes: contact stiffness parameters and friction parameters; the wear rate data includes: wear parameters and fatigue parameters; the crushing pressure data includes: particle crushing strength parameters; the deformation data includes: relaxation parameters, deformation parameters and degradation parameters.

[0016] Preferably, during the unidirectional cyclic load test, the target particles are laser scanned to obtain a three-dimensional graph, and the three-dimensional graph is subjected to a particle degradation assessment to obtain a particle degradation index, including:

[0017] Acquiring particle surface information of the target particle using laser scanning technology, and converting the particle surface information into the three-dimensional graph;

[0018] Reconstructing the original point cloud data of the three-dimensional graphic to obtain a three-dimensional model;

[0019] Extracting geometric features of the target particles using the three-dimensional model; the geometric features include volume, surface area, and shape;

[0020] The changes in the geometric characteristics before and after the unidirectional cyclic load test are quantified to obtain the particle degradation index.

[0021] Preferably, the motion behavior of a single particle in the three-dimensional graph is measured using particle image velocimetry technology to obtain motion behavior data, including:

[0022] Before the unidirectional cyclic load test, a preset number of target particles are marked; the marking method includes: spraying a specific pattern or fluorescent powder on the target particles;

[0023] capturing continuous motion images of the target particles;

[0024] The displacement data and rotation angle data of the target particles in the continuous motion image are extracted using particle image velocimetry technology to obtain the motion behavior data; the motion behavior data includes: velocity vector field, acceleration vector field and angular velocity vector field.

[0025] Preferably, the process of acquiring the microscopic contact behavior data includes:

[0026] The deformation of the two target particles in the contact setting under multiple groups of normal forces and tangential forces is measured to obtain the microscopic contact behavior data.

[0027] Preferably, the process of acquiring the wear rate data includes:

[0028] The target particles are placed in a Los Angeles abrader and rotated under preset conditions. The mass loss of the target particles after the rotation is completed is calculated to obtain the wear rate data.

[0029] Preferably, the process of obtaining the crushing pressure data includes:

[0030] A single target particle is placed in a press, the pressure applied is increased uniformly, and the pressure required to crush the target particle is recorded to obtain the crushing pressure data.

[0031] The present invention discloses the following technical effects:

[0032] The present invention provides a method for constructing a particle multi-scale coupling model. Through contact-scale tests, Los Angeles abrasion tests, single-body ballast crushing tests, and unidirectional cyclic load tests, the method solves the problem of low accuracy of results resulting from conventional methods that only test at the particle scale or particle aggregate scale, thereby realizing the construction of a multi-scale model. Parameter optimization is performed through laser scanning and particle image velocimetry technology, thereby solving the problem of large deviations between the predicted results of existing models and the actual results, thereby realizing the correction of model parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0034] Figure 1 A schematic diagram of the process of constructing a particle multi-scale coupling model provided by an embodiment of the present invention;

[0035] Figure 2 Schematic diagram of sustainable self-repairing and self-adjusting ballast particles provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0036] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0037] The purpose of the present invention is to provide a method for constructing a particle multi-scale coupling model to improve the model prediction accuracy and correct the model parameters.

[0038] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0039] Figure 1 A schematic diagram of the process of constructing a particle multi-scale coupling model provided by an embodiment of the present invention is shown in FIG. Figure 1 As shown, the present invention provides a method for constructing a particle multi-scale coupling model, comprising:

[0040] Step 100: Conducting contact scale tests, Los Angeles abrasion tests, single ballast crushing tests, and unidirectional cyclic loading tests on the target particles to obtain microscopic contact behavior data, wear rate data, crushing pressure data, and deformation data;

[0041] Step 200: constructing a model using the discrete element method based on the microscopic contact behavior data, the wear rate data, the crushing pressure data, and the deformation data to obtain an original DEM model;

[0042] Step 300: During the unidirectional cyclic load test, laser scanning is performed on the target particle to obtain a three-dimensional image, and particle degradation evaluation is performed on the three-dimensional image to obtain a particle degradation index;

[0043] Step 400: using particle image velocimetry technology to measure the motion behavior of a single particle in the three-dimensional graph to obtain motion behavior data;

[0044] Step 500: adjusting parameters of the original DEM model using the particle degradation index and the movement behavior data to obtain an improved DEM model;

[0045] Step 600: constructing a track and roadbed model using the finite element method, and constructing a train dynamic behavior model using multi-body dynamics analysis;

[0046] Step 700: Fusing the improved DEM model, the track and roadbed model, and the train dynamics behavior model to obtain a multi-scale coupling model;

[0047] Step 800: Use the multi-scale coupling model to perform simulation to obtain simulation results, perform multi-scale calibration on the multi-scale coupling model based on the simulation results, the microscopic contact behavior data, the wear rate data, the crushing pressure data and the deformation data, and output the standard completed multi-scale coupling model.

[0048] Specifically, the microscopic contact behavior data includes: contact stiffness parameters and friction parameters; the wear rate data includes: wear parameters and fatigue parameters; the crushing pressure data includes: particle crushing strength parameters; the deformation data includes: relaxation parameters, deformation parameters and degradation parameters.

[0049] Furthermore, during the unidirectional cyclic load test, the target particles are laser scanned to obtain a three-dimensional graph, and the three-dimensional graph is subjected to a particle degradation assessment to obtain a particle degradation index, including:

[0050] Acquiring particle surface information of the target particle using laser scanning technology, and converting the particle surface information into the three-dimensional graph;

[0051] Reconstructing the original point cloud data of the three-dimensional graphic to obtain a three-dimensional model;

[0052] Extracting geometric features of the target particles using the three-dimensional model; the geometric features include volume, surface area, and shape;

[0053] The changes in the geometric characteristics before and after the unidirectional cyclic load test are quantified to obtain the particle degradation index.

[0054] Preferably, the motion behavior of a single particle in the three-dimensional graph is measured using particle image velocimetry technology to obtain motion behavior data, including:

[0055] Before the unidirectional cyclic load test, a preset number of target particles are marked; the marking method includes: spraying a specific pattern or fluorescent powder on the target particles;

[0056] capturing continuous motion images of the target particles;

[0057] The displacement data and rotation angle data of the target particles in the continuous motion image are extracted using particle image velocimetry technology to obtain the motion behavior data; the motion behavior data includes: velocity vector field, acceleration vector field and angular velocity vector field.

[0058] Optionally, the process of acquiring the micro-contact behavior data includes:

[0059] The deformation of the two target particles in the contact setting under multiple groups of normal forces and tangential forces is measured to obtain the microscopic contact behavior data.

[0060] Preferably, the process of acquiring the wear rate data includes:

[0061] The target particles are placed in a Los Angeles abrader and rotated under preset conditions. The mass loss of the target particles after the rotation is completed is calculated to obtain the wear rate data.

[0062] Optionally, the process of obtaining the crushing pressure data includes:

[0063] A single target particle is placed in a press, the pressure applied is increased uniformly, and the pressure required to crush the target particle is recorded to obtain the crushing pressure data.

[0064] refer to Figure 2 , a sustainable self-repairing and self-adjusting ballast particle, comprising: coarse aggregate, fine aggregate, self-repairing material, self-adjusting material and a binder;

[0065] The coarse aggregate includes: construction recycling, ironmaking slag, slag and railway recycled ballast particles; the fine aggregate includes: tire-derived powder and sand and gravel with a size ranging from 1 to 5 mm; the self-repairing material includes: any one of self-repairing fibers and self-repairing capsules; the self-adjusting material includes: foaming agent ballast adhesive; the adhesive includes: any one of low-carbon cement and polymer adhesive materials, such as ballast adhesive.

[0066] Furthermore, current traditional ballast production methods are difficult to control in terms of quality. The large amount of needle-like ballast particles produced when used to lay the ballast track bed can cause uneven deformation and easily break. Sand and gravel, as fine aggregate, provide sufficient interlocking and friction properties, while tire-derived aggregate can neutralize and dissipate train loads. The binder material uses ultra-low-carbon, environmentally friendly cement or high-molecular polymers to achieve low-carbon production. Low-carbon cement (such as geopolymer cement), asphalt, or other low-carbon, environmentally friendly binders are used as the binder to ensure effective bonding between aggregate and fiber. Artificially synthesizing ballast using these materials allows for manual control of shape and size to reduce breakage and control gradation, achieving uniformity throughout the track bed.

[0067] Optionally, glass fibers or other self-healing fibers can be used. In addition to self-healing fibers, other concrete self-healing methods can also be employed, such as biorepair and capsule-based self-healing. The self-healing properties of synthetic ballast can be used to reduce ballast degradation. Through design and optimization, settlement can be further reduced, significantly minimizing differential settlement and associated compaction and stabilization issues.

[0068] Preferably, the self-adjusting material is a high molecular weight polymer, such as foaming agent ballast adhesive. When the ballast breaks or experiences significant roadbed deformation, causing wear and damage, the synthetic ballast releases the self-adjusting material to solidify and adjust the structure between particles, achieving uniform deformation and small-scale geometric adjustment. Multi-scale testing includes: contact-scale particle contact stiffness and friction testing, particle-scale Los Angeles abrasion testing and single-particle crushing testing, and aggregate-scale particle unidirectional cyclic loading testing.

[0069] Specifically, contact-scale experiments investigate how particles react under pressure by measuring the contact stiffness and friction between them. Using a custom-designed device, two ballast particles are fixed and their deformation under varying normal and tangential forces is measured, thereby determining their stiffness and friction coefficients. These results are used to numerically model microscopic contact behavior.

[0070] Furthermore, at the individual particle scale, the Los Angeles abrasion test is an important test for evaluating particle wear durability. Particles are placed in a Los Angeles abrader and rotated for a specified period of time under standard conditions. The mass loss after wear is measured and the wear rate is calculated. This test method can reflect the durability of particles during use.

[0071] Specifically, at the individual particle scale, the single ballast crushing test involves placing a single particle in a press and applying gradually increasing pressure until the particle breaks. The crushing pressure is measured to assess the particle's strength properties. This test analyzes the particle's crushing strength and resistance to crushing, and is crucial for assessing the structural stability of granular materials.

[0072] Furthermore, at the aggregate scale, unidirectional cyclic loading was applied to simulate the stresses on the aggregate under actual working conditions. This test investigated the deformation, relaxation, and degradation of the aggregate under repeated loading, helping to understand the stability and durability of the roadbed under repeated train rolling.

[0073] Preferably, a three-dimensional image of the particles is obtained based on laser scanning, and the three-dimensional graphics are analyzed and the particle degradation is evaluated with high precision and visualization to provide a quantitative particle degradation index. The method specifically includes the following analysis and evaluation process. Laser scanning technology is used to obtain particle surface information, and the surface details of the particles are converted into high-precision three-dimensional images. After scanning, the original point cloud data is processed by software to reconstruct the three-dimensional model of the particles, thereby accurately restoring the shape, surface roughness and other characteristics of the particles. Based on the obtained three-dimensional model, the geometric characteristics of the particles (such as volume, surface area, shape, etc.) are quantitatively analyzed. The scanned particle data is compared with the original particle model before the ballast degradation test to analyze the changes in particle wear, cracks, etc., and quantify the degree of degradation. The degradation index is calculated by comparing the changes in the shape and surface characteristics of the particles before and after the test. Specifically including:

[0074] The degree of particle wear was quantified by comparing the volume changes before and after the test;

[0075] The surface deterioration of the particle can be quantified due to the increase in surface area caused by surface cracks and roughness changes caused by wear;

[0076] Changes in particle shape can reflect their degradation during the test, such as changing from a spherical shape to a sharper shape or showing signs of breakage;

[0077] Image processing algorithms are used to analyze the distribution and length of cracks on the particle surface to further quantify the degree of degradation;

[0078] Finally, visualization technology presents these analysis results in 3D graphics, providing a more intuitive view of particle wear and degradation. 3D visualization software generates color heat maps or grid maps of the particle model, allowing observation of particle degradation areas from different angles. This generates image data that can be used for reporting or model calibration.

[0079] Furthermore, particle image velocimetry (PIV) is used to measure the movement and rotation of individual particles to calibrate and validate the multiscale numerical simulation model mentioned later. Particle image velocimetry plays a key role in measuring particle movement and rotation. The process mainly includes the following steps to calibrate and validate the multiscale numerical simulation model:

[0080] First, select and mark individual or multiple particles for easy tracking during the experiment. Ensure that the particles are clearly visible in the optical system during the experimental setup. Marking methods can include spraying specific patterns or fluorescent powders on the particle surface to enhance the capture of particle motion details.

[0081] A high-resolution camera is used to capture continuous images of particles in motion under load. PIV technology calculates the particle displacement between consecutive frames to obtain information on the particle's translation and rotation. In particular, for particle rotation, the rotation angle and velocity of each particle can be accurately calculated based on the markers. This process generates full-field data on particle motion.

[0082] PIV software converts the particle displacement data during the test into a vector field of velocity and acceleration, deriving the motion trajectory and rotational characteristics of each particle. For changes in rotation angle, PIV can calculate the particle's angular velocity based on the position changes of the particle surface markers.

[0083] Compare and analyze the PIV experimental data with the output of the discrete element numerical simulation model, paying special attention to the movement and rotation behavior of the particles at different time points. If the trajectory, velocity, and rotation angle of the particles in the numerical model differ from the PIV experimental results, the relevant parameters in the simulation model need to be adjusted. These parameters include the contact stiffness between the particles, the friction coefficient, the boundary conditions, etc., to make the model output closer to the experimental data.

[0084] After adjusting the model parameters, perform a new PIV test and compare the results with the simulation data to verify the model's accuracy. If the simulated results and the particle motion trends and numerical errors measured by PIV are within the acceptable range, the model is successfully calibrated and capable of predicting actual particle behavior.

[0085] Specifically, in terms of multi-scale numerical simulation modeling, contact-scale particle contact stiffness and friction tests, particle-scale Los Angeles wear tests and single-particle crushing tests, particle-assembly unidirectional cyclic load tests, and system-scale train-track-roadbed coupling models are used. At the same time, the discrete element analysis method is combined with the finite element method and multi-body dynamics to accurately and efficiently simulate the coupling interaction and dynamic response between trains, tracks, and roadbeds. In multi-scale numerical simulation modeling, the experiments described above provide key parameters and verification basis for model construction and calibration. These experiments provide mechanical behavior data of granular materials under different conditions and environments layer by layer, from the contact scale to the system scale, so that the numerical model can more comprehensively simulate the behavior of granular materials in actual working conditions. The test results are used to verify the numerical model, and the specific verification process is as follows:

[0086] Contact-scale particle contact stiffness and friction tests measure the contact stiffness and friction characteristics between particles for use in contact-scale particle modeling. These parameters help define the microscopic interactions between particles, including contact deformation and friction, enabling accurate modeling of interparticle contact behavior in discrete element models.

[0087] The Los Angeles abrasion test at the particle scale evaluates the particle degradation resistance by measuring the wear durability of the particles. The results provide wear and fatigue parameters for particle-scale models to simulate the wear and performance degradation of particles under long-term cyclic loading.

[0088] The single particle crushing test provides the model with strength parameters of particle crushing, enabling the model to simulate the crushing behavior of particles under extreme loads. These parameters are used to calibrate the strength distribution and crushing threshold of the particles;

[0089] Unidirectional cyclic loading tests at the particle aggregate scale observe the overall stress and deformation behavior of the particle aggregate, capturing its relaxation, deformation, and degradation characteristics under cyclic loading. These data are used in a particle aggregate scale model to simulate the overall mechanical behavior of the particle aggregate under dynamic loading, such as changes in density and adjustments in particle interactions.

[0090] The system-scale train-track-subgrade coupled model simulates the coupled interactions and dynamic responses of the train, track, and subgrade, with parameters established using data from the aforementioned tests. The model requires multi-scale test data to calibrate the transfer of train loads to the subgrade and the transfer and absorption characteristics of the ballast layer.

[0091] Furthermore, the construction of the multi-scale numerical model uses a variety of analysis methods such as discrete element analysis (DEM), finite element method (FEM), and multi-body dynamics, which is divided into the following steps:

[0092] S1: At the contact scale, the discrete element method (DEM) is used to construct a particle contact model, defining parameters such as interparticle contact stiffness and friction. These parameters are derived from the results of particle contact stiffness and friction testing. Model construction includes detailed simulation of particle shape and interparticle contact mechanical behavior to accurately simulate microscopic particle interactions.

[0093] S2: Based on data from Los Angeles abrasion tests and single-particle crushing tests, wear and crushing rules are incorporated into the particle-scale model. The DEM is used here to describe the mechanical behavior and microscopic failure mechanisms of particles during wear and crushing. Dynamic loading is applied to simulate the degradation of particles over long-term use.

[0094] S3: At the aggregate scale, data from unidirectional cyclic loading tests on aggregate particles is fed into a DEM model to simulate the aggregate's response to cyclic loading. The aggregate model primarily investigates relative particle displacement and changes in aggregate density to assess the long-term stability and reliability of the particles within the roadbed structure.

[0095] S4: At the system level, a multi-body dynamics coupling model of the train, track, and roadbed is constructed. Finite element method (FEM) and multi-body dynamics analysis (MBD) are used in conjunction with a DEM model to simulate the mechanical response of the roadbed and roadbed under dynamic train loads. DEM is used to analyze the behavior of the granular roadbed, FEM is used for the track and roadbed, and MBD is used to analyze the train dynamics. The three methods are combined to complete the construction of the coupled model.

[0096] S5: Based on the aforementioned experimental data, the model is calibrated at multiple scales. Contact- and particle-scale data are used for microcalibration, while particle-assembly and system-scale data are used for macrocalibration. At each scale, the experimental results are compared with the simulation outputs of displacement, stress, and particle rotation, and parameters are gradually adjusted to improve model accuracy.

[0097] The beneficial effects of the present invention are as follows:

[0098] The present invention enriches the number of model parameters and improves the simulation accuracy of the model through contact scale tests, Los Angeles abrasion tests, single ballast crushing tests and unidirectional cyclic load tests; through parameter optimization through laser scanning and particle image velocimetry technology, the model parameters are corrected and the deviation between the model prediction results and the actual results is reduced.

[0099] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0100] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only intended to help understand the method and core concept of the present invention. At the same time, those skilled in the art will find that the specific implementation methods and application scopes may vary based on the concept of the present invention. In summary, the contents of this specification should not be construed as limiting the present invention.

Claims

1. A method for constructing a particle multi-scale coupling model, characterized in that: include: The target particles were subjected to contact scale tests, Los Angeles abrasion tests, single ballast crushing tests, and unidirectional cyclic loading tests to obtain microscopic contact behavior data, wear rate data, crushing pressure data, and deformation data. A model is constructed using a discrete element method according to the microscopic contact behavior data, the wear rate data, the crushing pressure data, and the deformation data to obtain an original DEM model; During the unidirectional cyclic load test, the target particles are laser scanned to obtain a three-dimensional image, and the three-dimensional image is subjected to a particle degradation assessment to obtain a particle degradation index; Using particle image velocimetry technology to measure the motion behavior of individual particles in the three-dimensional graph to obtain motion behavior data; Adjusting parameters of the original DEM model using the particle degradation index and the movement behavior data to obtain an improved DEM model; Use the finite element method to build track and roadbed models, and use multi-body dynamics analysis to build train dynamic behavior models; fusing the improved DEM model, the track and roadbed model, and the train dynamics behavior model to obtain a multi-scale coupling model; The multi-scale coupling model is used to perform simulation to obtain simulation results. The multi-scale coupling model is multi-scale calibrated according to the simulation results, the microscopic contact behavior data, the wear rate data, the crushing pressure data and the deformation data, and the standard completed multi-scale coupling model is output.

2. The method for constructing a particle multi-scale coupling model according to claim 1, characterized in that: The microscopic contact behavior data includes: contact stiffness parameters and friction parameters; the wear rate data includes: wear parameters and fatigue parameters; the crushing pressure data includes: particle crushing strength parameters; the deformation data includes: relaxation parameters, deformation parameters and degradation parameters.

3. The method for constructing a particle multi-scale coupling model according to claim 1, characterized in that: During the unidirectional cyclic load test, the target particles are laser scanned to obtain a three-dimensional graph, and the three-dimensional graph is subjected to a particle degradation assessment to obtain a particle degradation index, including: Acquiring particle surface information of the target particle using laser scanning technology, and converting the particle surface information into the three-dimensional graph; Reconstructing the original point cloud data of the three-dimensional graphic to obtain a three-dimensional model; Extracting geometric features of the target particles using the three-dimensional model; the geometric features include volume, surface area, and shape; The changes in the geometric characteristics before and after the unidirectional cyclic load test are quantified to obtain the particle degradation index.

4. The method for constructing a particle multi-scale coupling model according to claim 1, characterized in that: The motion behavior of individual particles in the three-dimensional graph is measured using particle image velocimetry technology to obtain motion behavior data, including: Before the unidirectional cyclic load test, a preset number of target particles are marked; the marking method includes: spraying a specific pattern or fluorescent powder on the target particles; capturing continuous motion images of the target particles; The displacement data and rotation angle data of the target particles in the continuous motion image are extracted using particle image velocimetry technology to obtain the motion behavior data; the motion behavior data includes: velocity vector field, acceleration vector field and angular velocity vector field.

5. The method for constructing a particle multi-scale coupling model according to claim 1, characterized in that: The process of obtaining the micro-contact behavior data includes: The deformation of the two target particles in the contact setting under multiple groups of normal forces and tangential forces is measured to obtain the microscopic contact behavior data.

6. The method for constructing a particle multi-scale coupling model according to claim 1, characterized in that: The process of acquiring the wear rate data includes: The target particles are placed in a Los Angeles abrader and rotated under preset conditions. The mass loss of the target particles after the rotation is completed is calculated to obtain the wear rate data.

7. The method for constructing a particle multi-scale coupling model according to claim 1, characterized in that: The process of obtaining the crushing pressure data includes: A single target particle is placed in a press, the pressure applied is increased uniformly, and the pressure required to crush the target particle is recorded to obtain the crushing pressure data.

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