Particle multi-scale coupling model construction method and sustainable self-repairing and self-adjusting ballast particles

Abstract

The invention belongs to the field of railway systems, and provides a particle multi-scale coupling model construction method and sustainable self-repairing and self-adjusting ballast particles, and the method comprises the steps of experimental data collection, original DEM model construction, three-dimensional graph analysis, motion behavior analysis, parameter adjustment, other model construction, model fusion and multi-scale calibration. Through a contact scale test, a Lunar abrasion test, a single ballast crushing test and a one-way cyclic load test, the number of parameters of the model is enriched, and the simulation accuracy of the model is improved; parameter optimization is carried out through the laser scanning and particle image velocity measurement technology, correction of model parameters is achieved, and the deviation between a model prediction result and the reality is reduced.

Description

Technical Field

[0001] The present invention relates to the field of railway systems, and in particular to a particle multi-scale coupling model construction method and sustainable self-repairing and self-adjusting ballast particles. Background Art

[0002] A typical railway system consists of trains and tracks. The tracks mainly include the following components: rails, sleepers, fasteners, ballast beds and roadbeds. As an important component, the ballast bed has the following functions: ensuring the geometric shape of the track, transferring and neutralizing the train load, and providing the main drainage function. The ballasted trackbed is usually paved with graded crushed stone, which is a non-renewable resource. The construction of new lines and the maintenance and repair of ballasted trackbeds consume a large amount of graded crushed stone, and resources such as mountains are prohibited from being mined. At the same time, the waste and aging ballast on the railway line is usually abandoned around the railway line, which has a great impact on the environment. The performance of bulk granular materials such as ballast has multiple scales: particle degradation / aging, overall deformation of particles, and contact between particles.

[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 combination of different scales to ultimately achieve a comprehensive multi-scale test evaluation. The experimental measurement of particle degradation is based on the change 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 conducted 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 purpose of the present invention is to provide a particle multi-scale coupling model construction method and sustainable self-repairing and self-adjusting ballast particles, so as to improve the model prediction accuracy and correct 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 load tests to obtain microscopic contact behavior data, abrasion rate data, crushing pressure data, and deformation data;

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

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

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

[0011] Using the particle degradation index and the movement behavior data, the parameters of the original DEM model are adjusted to obtain an improved DEM model;

[0012] The track and roadbed models are constructed using the finite element method, and the train dynamics behavior model is constructed using multi-body dynamics analysis;

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

[0014] The multi-scale coupling model is used to perform simulations 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 include: contact stiffness parameters and friction parameters; the wear rate data include: wear parameters and fatigue parameters; the crushing pressure data include: particle crushing strength parameters; the deformation data include: 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 the particle surface information of the target particle by 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 graphics 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 the 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 applied pressure is increased uniformly, and the pressure required to break the target particle is recorded to obtain the breaking pressure data.

[0031] Preferably, a sustainable self-repairing self-adjusting ballast particle comprises: coarse aggregate, fine aggregate, self-repairing material, self-adjusting material and a binder;

[0032] 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 between 1 and 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 glue; the adhesive includes: any one of low-carbon cement and polymer adhesive materials.

[0033] The present invention discloses the following technical effects:

[0034] The present invention provides a method for constructing a particle multi-scale coupling model and sustainable self-repairing and self-adjusting ballast particles. Through contact-scale tests, Los Angeles abrasion tests, single-body ballast crushing tests and unidirectional cyclic load tests, the problem of low accuracy of results caused by conventional methods only testing at the particle scale or particle collection scale is solved, and the construction of a multi-scale model is realized. Parameter optimization is performed through laser scanning and particle image velocimetry technology, which solves the problem of large deviation between the predicted results of existing models and the actual results, and the correction of model parameters is realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. 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 creative labor.

[0036] Figure 1 A schematic diagram of the process of constructing a particle multi-scale coupling model provided in an embodiment of the present invention;

[0037] Figure 2 A schematic diagram of sustainable self-repairing and self-adjusting ballast particles provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0038] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0039] The purpose of the present invention is to provide a particle multi-scale coupling model construction method and sustainable self-repairing and self-adjusting ballast particles, so as to improve the model prediction accuracy and correct the model parameters.

[0040] 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.

[0041] Figure 1 A schematic diagram of the process of constructing a particle multi-scale coupling model provided in 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:

[0042] Step 100: Conducting contact scale test, Los Angeles abrasion test, single ballast crushing test and unidirectional cyclic load test on target particles respectively, and obtaining microscopic contact behavior data, abrasion rate data, crushing pressure data and deformation data;

[0043] Step 200: constructing a model 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;

[0044] Step 300: During the unidirectional cyclic load test, the target particles are laser scanned to obtain a three-dimensional graph, and the three-dimensional graph is evaluated for particle degradation to obtain a particle degradation index;

[0045] 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;

[0046] Step 500: adjusting the parameters of the original DEM model using the particle degradation index and the movement behavior data to obtain an improved DEM model;

[0047] Step 600: constructing a track and roadbed model using the finite element method, and constructing a train dynamics behavior model using multi-body dynamics analysis;

[0048] Step 700: integrating the improved DEM model, the track and roadbed model and the train dynamics behavior model to obtain a multi-scale coupling model;

[0049] 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.

[0050] Specifically, the microscopic contact behavior data include: contact stiffness parameters and friction parameters; the wear rate data include: wear parameters and fatigue parameters; the crushing pressure data include: particle crushing strength parameters; the deformation data include: relaxation parameters, deformation parameters and degradation parameters.

[0051] 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:

[0052] Acquiring the particle surface information of the target particle by using laser scanning technology, and converting the particle surface information into the three-dimensional graph;

[0053] Reconstructing the original point cloud data of the three-dimensional graphics to obtain a three-dimensional model;

[0054] Extracting geometric features of the target particles using the three-dimensional model; the geometric features include: volume, surface area and shape;

[0055] The changes in the geometric characteristics before and after the unidirectional cyclic load test are quantified to obtain the particle degradation index.

[0056] 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:

[0057] Before the unidirectional cyclic load test, a preset number of the target particles are marked; the marking method includes: spraying a specific pattern or fluorescent powder on the target particles;

[0058] capturing continuous motion images of the target particles;

[0059] 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.

[0060] Optionally, the process of acquiring the microscopic contact behavior data includes:

[0061] 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.

[0062] Preferably, the process of acquiring the wear rate data includes:

[0063] 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.

[0064] Optionally, the process of acquiring the crushing pressure data includes:

[0065] A single target particle is placed in a press, the applied pressure is increased uniformly, and the pressure required to break the target particle is recorded to obtain the breaking pressure data.

[0066] 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;

[0067] 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 between 1 and 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.

[0068] Furthermore, the current traditional ballast production method is difficult to achieve quality control. The large amount of needle-like ballast particles produced for paving the ballasted track bed will cause uneven deformation of the track bed, and the needle-like ballast is easy to break. Sand and gravel as fine aggregate provide sufficient particle interlocking and friction properties, while tire-derived aggregate can neutralize and dissipate train loads. The bonding material uses ultra-low carbon environmentally friendly cement or high molecular polymer to achieve low-carbon production. The bonding material uses low-carbon cement (such as geopolymer cement), asphalt or other low-carbon environmentally friendly bonding materials to ensure effective bonding between aggregates and fibers. The artificial synthesis of ballast with the above materials can artificially control the shape and size to reduce crushing and control grading, so as to achieve the uniformity of the overall track bed.

[0069] Optionally, the fiber is glass fiber or other self-healing fiber. In addition to self-healing fibers, other concrete self-healing methods can also be used, such as: biological self-healing, capsule self-healing and other self-healing. The self-healing function of artificial synthetic ballast is used to reduce ballast degradation. Through design and optimization, settlement will be further reduced, and differential settlement and related compaction and stabilization will be significantly reduced.

[0070] Preferably, the self-adjusting material is a high molecular polymer, such as foaming agent ballast glue. When the ballast is broken or a large deformation of the roadbed occurs, causing ballast wear and damage, the artificial synthetic ballast releases the self-adjusting material to solidify and adjust the structure between the particles to achieve uniform deformation and small geometric shape adjustment. The multi-scale test includes: contact scale particle contact stiffness and friction test, particle scale Los Angeles wear test and monomer particle crushing test, and aggregate scale particle aggregate unidirectional cyclic load test.

[0071] Specifically, the contact-scale test studies the reaction of particles under pressure by measuring the contact stiffness and friction characteristics between particles. The test uses a special device to fix two ballast particles and measure the deformation of the particles under different normal and tangential forces to determine the stiffness coefficient and friction coefficient of the particles. The test results are used for numerical modeling of microscopic contact behavior.

[0072] Furthermore, at the scale of individual particles, the Los Angeles abrasion test is an important test for evaluating the wear durability of particles. The particles are placed in a Los Angeles abrasion machine, rotated for a certain period of time under standard conditions, and the mass loss of the particles after wear is measured to calculate the wear rate. This test method can reflect the durability of particles during use.

[0073] Specifically, at the scale of individual particles, the single ballast crushing test places a single particle in a press and applies gradually increasing pressure until the particle breaks. The strength characteristics of the particle are evaluated by measuring the crushing pressure. This test is used to analyze the crushing strength and resistance to crushing of particles, which is of great significance to the evaluation of the structural stability of granular materials.

[0074] Furthermore, at the aggregate scale, a unidirectional cyclic load is applied to simulate the stress of the particle aggregate under actual working conditions. This test studies the deformation, relaxation and deterioration behavior of the particle aggregate under repeated loads, helping to understand the stability and durability of the roadbed under repeated rolling of trains.

[0075] 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 acquired 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:

[0076] The extent of particle wear was quantified by comparing the volume changes before and after the test;

[0077] 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;

[0078] Changes in particle shape can reflect the degradation that has occurred during the test, such as changing from a spherical shape to a more pointed shape or showing signs of breakage;

[0079] Image processing algorithms are used to analyze the distribution and length of cracks on the particle surface to further quantify the degree of degradation;

[0080] Finally, the above analysis results are displayed in three-dimensional graphics through visualization technology, making the wear and degradation of particles more intuitive. The color heat map or grid map of the particle model is generated by 3D visualization software, and the particle degradation area is observed from different angles to form image data that can be used for reporting or model calibration.

[0081] Furthermore, the movement and rotation of individual particles are measured using particle image velocimetry (PIV) to calibrate and verify the multi-scale numerical simulation model mentioned later. Particle image velocimetry plays a key role in the measurement of particle movement and rotation. The process mainly includes the following steps to calibrate and verify the multi-scale numerical simulation model:

[0082] First, select and mark single or multiple particles for easy tracking in the experiment. Make sure the particles are clearly visible in the optical system during the experimental setup. Marking methods can include spraying specific patterns or fluorescent powder on the surface of the particles to enhance the capture of particle movement details.

[0083] Use a high-resolution camera to capture continuous motion images of particles under stress. PIV technology obtains the translation and rotation information of particles by calculating the displacement of particles between consecutive frames. In particular, for the rotation of particles, the rotation angle and speed of each particle can be accurately calculated based on the marking. This process generates full-field data of particle motion;

[0084] Through PIV software, the displacement data of the particles in the test is converted into a vector field of velocity and acceleration, and the motion trajectory and rotation characteristics of each particle are obtained. For changes in the rotation angle, PIV can calculate the angular velocity of the particle through the position change of the particle surface mark;

[0085] Compare and analyze the PIV experimental data with the output data 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 movement trajectory, speed and rotation angle of the particles in the numerical model are different from the PIV experimental results, the relevant parameters in the simulation model need to be adjusted. The adjusted parameters include the contact stiffness, friction coefficient, boundary conditions, etc. between the particles, so that the output of the model is closer to the experimental data;

[0086] After adjusting the model parameters, a new PIV test is performed and the results are compared with the simulation data again to verify the accuracy of the model. At this point, if the simulation results and the particle movement trends and numerical errors measured by PIV are within the allowable range, it means that the model is calibrated successfully and has the ability to predict actual particle behavior.

[0087] 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 scale unidirectional cyclic load tests, and system-scale train-track-roadbed coupling models are carried out. 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:

[0088] Contact-scale particle contact stiffness and friction tests measure the contact stiffness and friction characteristics between particles for contact-scale particle model construction. These parameters help define the microscopic interactions between particles, including contact deformation and friction, and accurately model the contact behavior between particles in discrete element models;

[0089] The particle-scale Los Angeles abrasion test evaluates the particle's resistance to degradation by measuring the particle's wear durability. The results provide wear and fatigue parameters for the particle-scale model to simulate the wear and performance degradation of particles under long-term cyclic loading;

[0090] The single particle crushing test provides the model with the strength parameters of particle crushing, which enables the model to simulate the crushing behavior of particles under extreme loads. These parameters are used to calibrate the strength distribution and crushing critical value of particles;

[0091] The particle assembly scale unidirectional cyclic load test observes the overall stress and deformation behavior of the particle assembly to obtain the relaxation, deformation and degradation characteristics of the particle assembly under cyclic load. These data are used in the particle assembly scale model to simulate the overall mechanical behavior of the particle assembly under dynamic load, such as density changes and adjustments to particle interactions;

[0092] The system-scale train-track-subgrade coupled model simulates the coupled interaction and dynamic response of the train, track and subgrade, and constructs parameters based on the data from the aforementioned tests. The model requires the use of multi-scale test data to calibrate the process of train load transfer to the subgrade and its transfer and absorption characteristics in the ballast layer.

[0093] Furthermore, the construction of the multiscale numerical model uses a variety of analysis methods such as discrete element analysis (DEM), finite element method (FEM), and multibody dynamics, which is divided into the following steps:

[0094] S1: At the contact scale, the discrete element method (DEM) is used to construct a particle contact model and define parameters such as contact stiffness and friction between particles. These parameters are derived from the results of particle contact stiffness and friction tests. The construction of the model includes fine simulation of particle shape and contact mechanical behavior between particles to accurately simulate the interaction between microscopic particles.

[0095] S2: Based on the data from the Los Angeles abrasion test and the single particle crushing test, wear and crushing rules are added to the particle scale model. DEM is used here to describe the mechanical behavior and microscopic damage mechanism of particles during wear and crushing, and to simulate the degradation of particles in long-term use by applying dynamic loads.

[0096] S3: At the aggregate scale, the particle aggregate unidirectional cyclic load test data is input into the DEM model to simulate the response of the particle aggregate under cyclic load. The aggregate model mainly studies the relative displacement of particles, changes in aggregate density, etc., to evaluate the long-term stability and reliability of particles in the ballast structure.

[0097] S4: On a system scale, a multi-body dynamic coupling model of train-track-roadbed is constructed. Finite element method (FEM) and multi-body dynamics analysis (MBD) are used in combination with the DEM model to simulate the mechanical response of the roadbed and roadbed under the dynamic load of the train. DEM is used to process the behavior of the granular roadbed, FEM is used for the track and roadbed, and MBD processes the dynamic behavior of the train. The three are combined to complete the construction of the coupling model.

[0098] S5: Perform multi-scale calibration of the model based on the above test data. The contact scale and particle scale data are used for micro calibration, and the particle set and system scale data are used for macro calibration. At each scale, the test results are compared with the displacement, stress, and particle rotation output by the simulation, and the parameters are gradually adjusted to improve the accuracy of the model.

[0099] The beneficial effects of the present invention are as follows:

[0100] 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; and optimizes the parameters through laser scanning and particle image velocimetry technology, realizes the correction of model parameters and reduces the deviation between the model prediction results and the actual results.

[0101] 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.

[0102] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood 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 load tests to obtain microscopic contact behavior data, abrasion rate data, crushing pressure data, and deformation data; According to the microscopic contact behavior data, the wear rate data, the crushing pressure data and the deformation data, a model is constructed using a discrete element method to obtain an original DEM model; During the unidirectional cyclic load test, the target particles are laser scanned to obtain a three-dimensional graph, and the three-dimensional graph is evaluated for particle degradation to obtain a particle degradation index; Using particle image velocimetry technology to measure the motion behavior of a single particle in the three-dimensional graph to obtain motion behavior data; Using the particle degradation index and the movement behavior data, the parameters of the original DEM model are adjusted to obtain an improved DEM model; The track and roadbed models are constructed using the finite element method, and the train dynamics behavior model is constructed using multi-body dynamics analysis; The improved DEM model, the track and roadbed model and the train dynamics behavior model are integrated to obtain a multi-scale coupling model; The multi-scale coupling model is used to perform simulations 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. A particle multi-scale coupling model construction method according to claim 1, characterized in that: The microscopic contact behavior data include: contact stiffness parameters and friction parameters; the wear rate data include: wear parameters and fatigue parameters; the crushing pressure data include: particle crushing strength parameters; the deformation data include: 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 the particle surface information of the target particle by 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 graphics 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 a single particle 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 the 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 applied pressure is increased uniformly, and the pressure required to break the target particle is recorded to obtain the breaking pressure data.

8. A sustainable self-repairing and self-adjusting ballast particle, characterized in that: include: coarse aggregate, fine aggregate, self-healing materials, self-adjusting materials, and binders; 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 between 1 and 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 glue; the adhesive includes: any one of low-carbon cement and polymer adhesive materials.

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