Train-ballast track-roadbed system simulation method and system based on MBD-DEM-FDM coupling

Abstract

The invention discloses a train-ballast track-roadbed system simulation method based on MBD-DEM-FDM coupling, and the method comprises the steps: building a train model based on a multi-body dynamics MBD method: building a dynamic model of a train system, simplifying a suspension system of a train through a spring and a damper, and considering the interaction between the train and a track; establishing a three-dimensional ballast track bed model based on a discrete element method DEM; establishing a roadbed finite difference model based on a finite difference method FDM, including: regarding the roadbed as a continuous medium, and simulating mechanical behaviors and deformation characteristics of the roadbed under the action of a train load based on the finite difference method FDM; setting a coupling medium so as to couple the MBD-DEM-FDM, and carrying out real-time information exchange between the MBD and the DEM and FDM systems; and establishing a coupling model based on MBD-DEM-FDM coupling, and verifying and applying the coupling model. The invention further discloses a corresponding system, electronic equipment and a computer readable storage medium, and the comprehensive influence of the micromechanical characteristics of particles in the ballast bed and the train power effect on the track and the roadbed is considered.

Description

Technical Field

[0001] The present invention relates to the technical field of train-ballasted track-roadbed system simulation methods, and in particular to a train-ballasted track-roadbed system simulation method and system based on MBD-DEM-FDM coupling. Background Art

[0002] Railway lines are composed of ballasted tracks, roadbeds, bridges and tunnels, and are multi-layered, heterogeneous longitudinal structures. In order to ensure the stable operation of railway lines, each structural layer needs to meet functional and technical requirements and work together. However, existing studies often separate the upper train, track structure and lower structure, ignoring the mutual influence between them. This separation method is not conducive to systematic evaluation and research on the impact of local structural defects on the dynamic response changes of other structural layers, and cannot fully characterize the overall mechanical properties of the train-track-roadbed coupling system and the cyclic effects of real trains.

[0003] At present, the research on the dynamic response of train-ballasted track-roadbed is mainly carried out through field tests, full-scale model tests and theoretical numerical calculations. Due to the small number of detection points and low efficiency, field tests are difficult to obtain the internal defects of the ballasted track bed, and real-time rapid detection cannot be carried out, and it is difficult to conduct human intervention research. There is a certain gap between the full-scale model test and the actual situation on site, and it is impossible to truly restore the train circulation effect. Theoretical numerical calculations are mainly focused on the establishment and research of the train-ballasted track-roadbed coupling system model. Most of them are based on the traditional finite element method to consider the lower structure. Usually, the ballasted track bed is simplified as a discrete mass block or continuous medium, ignoring the characteristics of the ballasted track bed with many gaps inside and the point contact between the ballasts at the mesoscopic level. It is impossible to fully consider the hidden defects and mesoscopic mechanical behavior of the ballasted track bed, which has a certain impact on the research of the dynamic response of the overall structure. To solve the above problems, the discrete element method can well simulate the mesoscopic morphology and mechanical properties of the ballast particles inside the track bed, providing a better way to study the mesoscopic dynamic mechanical behavior of the ballasted track bed. However, current numerical simulation research on ballasted trackbed is still limited to the structural layer of the trackbed itself, ignoring the actual effect of the upper train.

[0004] In addition, the existing technical solutions mostly use multi-body dynamics methods to simulate the train vehicle subsystem, use finite element method to simulate the track and roadbed subsystems respectively, and use spring-damper elements to simulate the interaction between the structural layers. Figure 1 (a)- Figure 1 (b) shows the numerical model of the three-dimensional coupled system of train-ballasted track-roadbed. Based on the multi-body dynamics theory, a multi-rigid body model of the train vehicle is established. The schematic diagram of the three-dimensional multi-body dynamics model of the train vehicle is shown in Figure 2 (a)- Figure 2 (c) as shown.

[0005] The defects in the existing research on train-track-roadbed coupling system are mainly manifested in the following aspects:

[0006] (1) Existing studies often analyze the upper train, track structure, and lower structure separately, ignoring the interaction between them and failing to fully characterize the overall mechanical properties of the train-track-subgrade coupling system. This separation approach is not conducive to systematically evaluating the impact of local structural defects on the dynamic response of other structural layers.

[0007] (2) Due to the small number of test points and low efficiency, it is difficult to obtain the defects inside the ballasted trackbed during field testing, and it is impossible to detect and intervene in real time; full-scale model tests are difficult to truly restore the circulation of trains and cannot effectively represent the actual working conditions; traditional theoretical numerical calculation methods simplify the simulation of ballasted trackbeds, ignoring the internal void structure of the ballasted trackbed and the microscopic mechanical behavior of ballast particles, resulting in inaccurate research results on the overall dynamic response.

[0008] Therefore, it is of great significance to establish a numerical calculation model that can comprehensively analyze the real-time train operation and the microscopic mechanical behavior of ballasted track particles, and consider the interaction between ballasted track and roadbed, in order to study the spatial dynamic interaction and overall mechanical performance evolution of the train-track-roadbed coupling system. This numerical simulation method can reproduce the actual working conditions on site, reduce the burden of on-site measurements, and thus ensure the safe operation and long-term service of the railway. Summary of the invention

[0009] The purpose of the present invention is to provide a train-ballasted track-roadbed system simulation method and system based on MBD-DEM-FDM coupling, which is used to simulate the mechanical response of the train-track-roadbed system under complex dynamic conditions. A three-dimensional numerical calculation model based on the coupling of Multi-Body Dynamics (MBD)-Discrete Element Method (DEM)-Finite-difference methods (FDM) is intended to conduct a comprehensive study on the macro-micro dynamic response of the train-ballasted track-roadbed system. This model can make up for the shortcomings of the existing research on the overall mechanical behavior analysis of the coupling system, especially considering the micro-mechanical properties of the particles inside the ballast bed and the comprehensive influence of the train dynamics on the track and the roadbed. Through this method, the reproduction of the actual working conditions can be achieved, reducing the burden of on-site measurements, thereby providing a theoretical basis and technical support for the safe operation of high-speed and heavy-load railways.

[0010] The invention objectives and technical problems to be solved by the present invention include:

[0011] (1) A coupled model that can simultaneously consider the interaction between trains, tracks, and roadbed is established to study the dynamic behavior of the train-track-roadbed system under high-speed and heavy-load conditions.

[0012] (2) Through real-time coupling of MBD, DEM and FDM calculation methods, the microscopic dynamic mechanical behavior of ballasted track bed particles can be accurately simulated, and its influence on the overall mechanical response of the system can be revealed.

[0013] (3) Provide theoretical basis and technical guidance for the design and intelligent operation and maintenance of high-speed and heavy-load railways, and improve the safety and long-term service capability of the railway system.

[0014] A first aspect of the present invention is to provide a train-ballasted track-roadbed system simulation method based on MBD-DEM-FDM coupling, comprising:

[0015] S1, establishing a train model based on a multi-body dynamics MBD method, including: establishing a dynamic model of a train system based on the multi-body dynamics MBD method, wherein the suspension system of the train is simplified by springs and dampers, and the interaction between the train and the track is considered in the dynamic model of the train system;

[0016] S2, establish a three-dimensional ballasted track bed model based on discrete element method DEM;

[0017] S3, establishing a finite difference model of the roadbed based on the finite difference method FDM, including: the roadbed is regarded as a continuous medium, and the mechanical behavior and deformation characteristics of the roadbed under the train load are simulated based on the finite difference method FDM, thereby obtaining the finite difference model of the roadbed;

[0018] S4, setting a coupling medium to couple MBD-DEM-FDM, and performing real-time information exchange between MBD and DEM and FDM systems;

[0019] S5, establishing a coupling model based on MBD-DEM-FDM coupling and verifying and applying the coupling model, including: establishing a coupling model, obtaining simulation results based on the coupling model, and comparing and analyzing the simulation results with the on-site dynamic response to verify the correctness of the coupling model; establishing five ballast-deficient working conditions to calculate and obtain a schematic diagram of the particle contact force chain and a sleeper displacement acceleration curve to realize the application of the coupling model.

[0020] Preferably, the S1 comprises:

[0021] S11, based on MBD theory, a rigid body consisting of a car body, a bogie, and a wheelset is established, wherein the car body is connected to the two bogies through a primary suspension system and a secondary suspension system, and a spring and a damper of the suspension system are simplified into a linear model;

[0022] S12, in the modeling of the suspension system, the connection between the vehicle body and the bogie, and the connection between the bogie and the wheelset are simulated by linear springs and dampers;

[0023] S13, based on the Hamiltonian principle, starting from the total kinetic energy, total potential energy and virtual work of the system, through the construction of a generalized coordinate system, the mass matrix, stiffness matrix, damping matrix and load matrix of the system are obtained, and finally the vibration dynamics equations of the train system are formed, which are:

[0024]

[0025] Where: M v , C v and K v are the mass matrix, damping matrix and stiffness matrix of the train vehicle, respectively, and F v is the load vector, X v is the displacement matrix;

[0026] S14, establishing a three-dimensional train-track model, including: calculating the normal force between the wheel and rail based on the Hertz nonlinear contact theory; simulating the wheel-rail tangential contact force based on the Kalker creep theory; establishing a wheel-rail contact coupling model based on the normal force between the wheel and rail and the tangential contact force between the wheel and rail, wherein the wheel-rail contact coupling model can accurately calculate the dynamic changes of the wheel-rail contact during the train operation; continuing to comprehensively consider four different types of track unevenness, wherein the four types of track unevenness include height unevenness, direction unevenness, horizontal unevenness and regular unevenness, including: different types of track unevenness obtained by simulation and analysis using the trigonometric series method are input as external excitations into the wheel-rail contact coupling model to obtain a first comprehensive sample of height unevenness and horizontal unevenness, and a second comprehensive sample of gauge unevenness and direction unevenness; establishing the three-dimensional train-track model based on the first comprehensive sample and the second comprehensive sample;

[0027] S15, calculating the dynamic model of the train system based on the Wilson-θ integration method, including: firstly discretizing the vibration dynamics equations of the train system, introducing a correction factor θ to adjust the response in each time step by setting equally spaced discrete time points, and adjusting the acceleration, velocity and displacement of the next time step to reflect the correction effect of the current time step; then, gradually correcting the response of the system through an iterative process in each time step until a given convergence condition is met.

[0028] Preferably, S2 includes:

[0029] S21, constructing a mesoscopic mechanical model of ballast particles, including: simulating the contact, friction and rolling behaviors of ballast particles based on the discrete element method DEM, and establishing a particle accumulation model as the mesoscopic mechanical model of ballast particles by setting mesoscopic parameters such as particle gradation, size and density;

[0030] S22, compacting the ballast particle micromechanical model to establish the three-dimensional ballasted track bed model.

[0031] Preferably, the S21 includes:

[0032] (1) Define the geometric parameters of ballast particles, determine the particle size distribution, and use PFC software to generate particles;

[0033] (2) Considering the contact model between particles, the contact model between particles is set to an anti-rolling linear contact model, and boundary conditions are set to simulate the dynamic behavior between particles and other structural components.

[0034] Preferably, the S22 includes:

[0035] (1) In the designated area, ballast was generated three times. After each generation, a wall unit was generated above the ballast particles and compacted by the servo control principle. The compressive stress was 200 kPa. A total of three compaction procedures were performed. The ballast slope was 1:1.75, and the thickness of the final roadbed model was 0.55 m. Then, walls were generated on the top surface of the roadbed and the ballast slopes on both sides, and the last compaction was performed. Finally, the particles in the sleeper area were deleted and the sleepers were placed.

[0036] (2) By measuring the overall porosity of the ballast bed, the ρ of the final ballast bed model is calculated b About 1600kg / m 3 , meeting the requirements of the "Heavy Haul Railway Design Code" (TB 10625-2017).

[0037] Preferably, S3 includes:

[0038] S31, the roadbed is regarded as a continuous medium, a roadbed grid division numerical model is established, and material properties and boundary conditions of the roadbed grid division numerical model are set;

[0039] S32, solving the roadbed grid numerical model using a finite difference method to simulate the mechanical behavior and deformation characteristics of the roadbed under the train load, thereby obtaining the roadbed finite difference model.

[0040] Preferably, S4 includes:

[0041] S41, using the coupling relationship of track-ballast-subgrade interface to establish the coupling model between MBD-DEM and DEM-FDM;

[0042] S42, achieving real-time coupling between the train multi-body system and the discrete ballast particle system by defining a mechanical transfer relationship between the rail and the sleeper;

[0043] S43, by setting an artificial viscoelastic boundary in the discrete element numerical model, an equivalent simulation between the ballast mass and the discrete ballast particles is achieved, thereby achieving real-time information exchange between the MBD and DEM and FDM systems.

[0044] The second aspect of the present invention is to provide a train-ballasted track-roadbed system simulation system based on MBD-DEM-FDM coupling, which is used to implement the method of the first aspect, including:

[0045] A train model building module (101) is used to build a train model based on a multi-body dynamics (MBD) method, comprising: building a dynamics model of a train system based on the multi-body dynamics (MBD) method, wherein the train suspension system is simplified by using springs and dampers, and the interaction between the train and the track is considered;

[0046] A three-dimensional ballast model establishment module (102) is used to establish a three-dimensional ballast model based on a discrete element method (DEM); comprising: simulating the contact, friction and rolling behavior of ballast particles based on the discrete element method (DEM), establishing a particle accumulation model by setting microscopic parameters such as particle gradation, size and density, and compacting the particle accumulation model to establish the three-dimensional ballast model;

[0047] A roadbed finite difference model building module (103) is used to build a roadbed finite difference model based on a finite difference method FDM, comprising: the roadbed is regarded as a continuous medium, and the mechanical behavior and deformation characteristics of the roadbed under the action of train load are simulated based on the finite difference method FDM, thereby obtaining the roadbed finite difference model;

[0048] MBD-DEM-FDM coupling module (104), used to set a coupling medium so as to couple MBD-DEM-FDM and perform real-time information exchange between MBD and DEM and FDM systems;

[0049] A coupling model establishment and verification application module (105) is used to establish a coupling model based on MBD-DEM-FDM coupling and verify and apply the coupling model, including: establishing a coupling model, obtaining simulation results based on the coupling model, and comparing and analyzing the simulation results with the on-site dynamic response to verify the correctness of the coupling model; establishing five ballast-deficient working conditions to calculate and obtain a particle contact force chain diagram and a sleeper displacement acceleration curve diagram to realize the application of the coupling model.

[0050] A third aspect of the present invention provides an electronic device, comprising a processor and a memory, wherein the memory stores a plurality of instructions, and the processor is configured to read the instructions and execute the method described in the first aspect.

[0051] A fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a plurality of instructions, and the plurality of instructions can be read by a processor and execute the method described in the first aspect.

[0052] Beneficial effects of the method and system of the present invention:

[0053] The present invention proposes a three-dimensional numerical simulation method based on MBD-DEM-FDM coupling, which significantly improves the research accuracy of the dynamic behavior of the train-track-roadbed system. Compared with the existing technology, it has the following technical advantages:

[0054] 1. Accurate multi-scale coupling analysis

[0055] Deficiencies of existing technology: Traditional studies on train-track-roadbed systems mostly analyze the train, track, roadbed and roadbed separately, ignoring the interactions between them, making it difficult to accurately predict the overall mechanical behavior of the system.

[0056] Technical advantages: The present invention accurately simulates the interaction between trains, tracks, ballasts and roadbeds by coupling multi-body dynamics MBD with discrete element method DEM and finite difference method FDM, and can simultaneously capture the macroscopic dynamic response of the system and the microscopic mechanical behavior inside the ballast. This multi-scale coupling model can fully characterize the dynamic characteristics of each level of the system and reveal the transfer path and dynamic changes of loads between different structural layers.

[0057] 2. Micro-dynamic simulation of ballast particles

[0058] Deficiencies of the existing technology: In the existing technology, the ballasted track bed is often regarded as a continuous medium or a discrete mass block through a simplified method, ignoring the complex contact, rolling and friction characteristics between the ballast particles, and it is impossible to accurately simulate the microscopic mechanical behavior of the track bed.

[0059] Technical advantages: The present invention introduces the discrete element method (DEM) to finely model the shape, size and mechanical behavior of ballast particles, and can simulate the dynamic behaviors such as contact, sliding, wear and crushing between particles, so as to accurately reproduce the microscopic response of the roadbed under the action of train loads. This method effectively makes up for the shortcomings of the traditional continuum model and can reveal the relationship between the hidden defects inside the roadbed and the overall dynamic response of the system.

[0060] 3. Real-time coupling calculation interface

[0061] Deficiencies of existing technologies: Existing studies usually simulate the dynamic behaviors of trains, tracks, and roadbeds separately and manually input the results into other models, resulting in low computational efficiency and inability to achieve real-time coupled dynamic simulation.

[0062] Technical advantages: The present invention realizes the real-time coupling of MBD, DEM and FDM through the Python program interface, and can synchronously calculate the dynamic responses of different subsystems, avoiding the inaccuracy and inefficiency caused by manual input of results in traditional methods. This real-time calculation method not only improves the simulation efficiency, but also ensures the timeliness and accuracy of the system's dynamic response.

[0063] 4. More comprehensive system dynamic response

[0064] Deficiencies of existing technologies: Existing numerical simulation methods cannot simultaneously consider the macro- and micro-scale responses of trains, tracks, ballasts, and roadbed systems, making it difficult to predict the global dynamic behavior of trains under different operating conditions.

[0065] Technical advantages: The present invention can analyze the mechanical impact of train loads on tracks, roadbeds and roadbeds at the macro level, while simulating the local behavior of ballast particles at the micro level. Through this multi-level comprehensive analysis, it can provide a more comprehensive and accurate system dynamic response, especially in predicting track settlement, ballast wear and roadbed deformation. It has significant technical advantages.

[0066] 5. Efficient hidden disease simulation

[0067] Deficiencies of existing technologies: Traditional methods for detecting hidden roadbed defects mostly rely on on-site measurements, which makes it difficult to conduct real-time dynamic analysis and lacks microscopic mechanical analysis of hidden defects.

[0068] Technical advantages: The present invention can accurately reproduce the impact of hidden roadbed defects on the overall mechanical response of the system in numerical simulation through the discrete element method. Combined with the dynamic simulation of train loads, it can analyze in real time the dynamic impact of ballast deterioration, crushing and other defects on the train-track-roadbed system, providing a more accurate defect diagnosis tool.

[0069] In summary, the present invention overcomes the limitations of the existing technology by innovatively introducing the MBD-DEM-FDM coupling technology, and can simulate the complex mechanical behavior of the train-track-roadbed system more accurately and efficiently, significantly improving the prediction ability of the system's dynamic response, especially in the microscopic behavior and disease analysis of the roadbed under train loads. It shows unique technical advantages. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the related technologies, the drawings required for use in the specific embodiments or the related technical descriptions will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0071] Figure 1 Schematic diagram of the numerical model of the three-dimensional coupled system of train-ballasted track-roadbed established according to the prior art, where Figure 1 (a) is a longitudinal section view. Figure 1 (b) is a transverse cross-sectional view;

[0072] Figure 2 The figure is a schematic diagram of a three-dimensional multi-body dynamics model of a train vehicle established according to the prior art; Figure 2 (a) is a side view; Figure 2 (b) is a top view; Figure 2 (c) is a front view;

[0073] Figure 3 A flow chart of a train-ballasted track-roadbed system simulation method based on MBD-DEM-FDM coupling according to an embodiment of the present invention;

[0074] Figure 4 A schematic diagram of parameters and structure of a three-dimensional train model provided according to an embodiment of the present invention;

[0075] Figure 5 A schematic diagram of a three-dimensional train-ballasted track coupling model provided according to an embodiment of the present invention;

[0076] Figure 6 The ballast layer modeling process provided by the embodiment of the present invention, wherein Figure 6 (a) corresponds to the first three compaction processes, Figure 6 (b) After deleting the ballast on both sides, a wall is generated on the top surface of the roadbed and the ballast slopes on both sides, and the final compaction process is performed; Figure 6 (c) a process for placing sleepers corresponding to particles in the deleted sleeper area;

[0077] Figure 7 A schematic diagram of a coupling algorithm between discrete particles and a continuous medium contact surface provided according to an embodiment of the present invention; Figure 7 (a) is a schematic diagram of the coupling interface position; Figure 7 (b) is a schematic diagram of the coupling process principle;

[0078] Figure 8 A diagram of a three-dimensional coupling model of sleepers, ballast beds and roadbeds provided according to an embodiment of the present invention;

[0079] Fig. 9 A flowchart of numerical calculation and analysis provided according to an embodiment of the present invention;

[0080] Fig.10 The data interaction interface and flow chart of the MBD part and the DEM-FDM part provided according to the embodiment of the present invention;

[0081] Fig.11 A comparison chart of numerical simulation results and measured data provided according to an embodiment of the present invention; wherein Fig.11 (a) is a schematic diagram comparing the measured displacement of the rail with the simulation result; Fig.11 (b) is a schematic diagram comparing the measured displacement of the sleeper with the simulation result;

[0082] Fig.12 A schematic diagram of a ballast-deficient working condition for applying a model according to an embodiment of the present invention; wherein Fig.12 (a) is the working condition diagram of the ballast shortage in the middle of the sleeper; Fig.12 (b) is the working condition diagram of the lack of ballast at the rail support; Fig.12 (c) is the working condition diagram of partial ballast shortage on both sides; Fig.12 (d) is the working condition diagram of large area ballast shortage on both sides; Fig.12 (e) is the working condition diagram of complete ballastlessness;

[0083] Fig.13 A diagram showing the model application results provided according to an embodiment of the present invention; wherein Fig.13 (a) is a schematic diagram of the contact force chain results; Fig.13 (b) is a schematic diagram of sleeper displacement results; Fig.13 (c) is a schematic diagram of the sleeper acceleration results;

[0084] Fig.14 A diagram showing the architecture of a train-ballasted track-roadbed system simulation system based on MBD-DEM-FDM coupling according to an embodiment of the present invention;

[0085] Fig.15 A structural diagram of an electronic device provided according to an embodiment of the present invention. DETAILED DESCRIPTION

[0086] The technical solution of the present invention will be described clearly and completely below 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 creative work are within the scope of protection of the present invention.

[0087] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0088] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0089] Embodiment 1

[0090] See also Figure 3 This embodiment provides a train-ballasted track-roadbed system simulation method based on MBD-DEM-FDM coupling, including:

[0091] S1, establishing a train model based on a multi-body dynamics MBD method, including: establishing a dynamic model of a train system based on the multi-body dynamics MBD method, wherein the suspension system of the train is simplified by springs and dampers, and the interaction between the train and the track is considered in the dynamic model of the train system;

[0092] As a preferred embodiment, the S1 includes:

[0093] S11, based on MBD theory, a rigid body such as a car body, a bogie, and a wheelset is established, wherein the car body is connected to the two bogies through a primary suspension system and a secondary suspension system, and the spring and damper of the suspension system are simplified into a linear model, such as Figure 4 Each vehicle model has 30 degrees of freedom, of which each car body and bogie has 6 degrees of freedom, which are longitudinal displacement x c , lateral displacement y c , sinking and floating (vertical displacement) z c , roll angle θ c , pitch angle φ c and yaw angle φ c Each of the wheelsets has four degrees of freedom, namely longitudinal displacement x wi , lateral displacement y wiand vertical displacement (sinking and floating) z wi .

[0094] In this embodiment, the specific degrees of freedom are shown in Table 1, which shows the degree of freedom distribution of the train vehicle model.

[0095] Table 1

[0096]

[0097] S12, in the modeling of the suspension system, the connection between the vehicle body and the bogie, and the connection between the bogie and the wheelset are simulated by linear springs and dampers.

[0098] In the modeling of the suspension system, the connection between the car body and the bogie, and between the bogie and the wheelset are simulated by linear springs and dampers. This multi-degree-of-freedom model can not only fully describe the relative motion of various components during the operation of the train, but also consider the dynamic response characteristics of the train under different track conditions, thereby realizing the subsequent track-vehicle coupling dynamics analysis. Figure 4 This is a schematic diagram of the parameters and structure of a three-dimensional train model.

[0099] S13, based on the Hamiltonian principle, starting from the total kinetic energy, total potential energy and virtual work of the system, through the construction of a generalized coordinate system, the mass matrix, stiffness matrix, damping matrix and load matrix of the system are obtained, and finally the vibration dynamics equations of the train system are formed, which are:

[0100]

[0101] Where: M v , C v and K v are the mass matrix, damping matrix and stiffness matrix of the train vehicle, respectively, and F v is the load vector, X v is the displacement matrix.

[0102] In this embodiment, the train has many degrees of freedom, which makes its vibration equation very complicated. It is difficult to directly derive its motion equation by the traditional force balance analysis method. However, it is easier and more effective to analyze its motion law from the perspective of energy. Therefore, based on the Hamiltonian principle, starting from the total kinetic energy, total potential energy and virtual work of the system, through the construction of a generalized coordinate system, the mass matrix, stiffness matrix, damping matrix and load matrix of the system are obtained, and finally the vibration equation group of the train subsystem is formed.

[0103] S14, establishing a three-dimensional train-track model, including: calculating the normal force between the wheel and rail based on Hertz nonlinear contact theory; simulating the wheel-rail tangential contact force based on Kalker creep theory; establishing a wheel-rail contact coupling model based on the normal force between the wheel and rail and the tangential contact force between the wheel and rail, and the wheel-rail contact coupling model can accurately calculate the dynamic changes of the wheel-rail contact during the operation of the train; continuing to comprehensively consider four different types of track unevenness, the four types of track unevenness include height unevenness, directional unevenness, horizontal unevenness and regular unevenness, including: different types of track unevenness obtained by simulation and analysis using the trigonometric series method are input into the wheel-rail contact coupling model as external excitations to obtain a first comprehensive sample of height unevenness and horizontal unevenness, and a second comprehensive sample of gauge unevenness and directional unevenness; establishing the three-dimensional train-track model based on the first comprehensive sample and the second comprehensive sample.

[0104] The specific calculation formulas for the power spectral density of the four types of track irregularities are as follows:

[0105] (1) Uneven height:

[0106]

[0107] (2) Unsmooth direction:

[0108]

[0109] (3) Uneven level:

[0110]

[0111] (4) The power spectrum of track irregularity is generally similar to the expression of horizontal irregularity, but the influence of the distance between the left and right rolling circles is not considered, so its specific expression is as follows:

[0112]

[0113] In formula (2) to formula (5), the unit of formula (2), formula (3) and formula (5) is m 2 / (rad / m), the physical meaning of formula (4) is measured by inclination angle, so the unit is 1 / (rad / m); where b is half of the distance between the left and right rolling circles, and the embodiment of the present invention takes 0.75m based on existing research; Ω c ,Ω r ,Ω s , is the cutoff frequency; A a , A v , A g is the roughness coefficient, and the German low-interference track power spectrum is used. Its value is shown in Table 2. Low-interference power spectrum parameter values.

[0114] Table 2

[0115]

[0116] Different types of track irregularities obtained through simulation and analysis using the trigonometric series method are used as external excitation inputs to the overall coupled system calculations, resulting in a combination of high and low irregularities and horizontal irregularities, as well as a comprehensive sample of gauge and directional irregularities. The schematic diagram of the resulting train-track three-dimensional model is shown below: Figure 5 shown.

[0117] S15, calculating the dynamic model of the train system based on the Wilson-θ integration method, including: firstly discretizing the vibration dynamics equations of the train system, introducing a correction factor θ to adjust the response in each time step by setting equally spaced discrete time points, and adjusting the acceleration, velocity and displacement of the next time step to reflect the correction effect of the current time step; then, gradually correcting the response of the system through an iterative process in each time step until a given convergence condition is met.

[0118] S2, establish a three-dimensional ballasted track bed model based on the discrete element method (DEM);

[0119] As a preferred embodiment, the S2 includes:

[0120] S21, constructing a mesoscopic mechanical model of ballast particles, including: simulating the contact, friction and rolling behaviors of ballast particles based on the discrete element method DEM, and establishing a particle accumulation model as the mesoscopic mechanical model of ballast particles by setting mesoscopic parameters such as particle gradation, size and density;

[0121] In this embodiment, the S21 includes:

[0122] (1) Define the geometric parameters of ballast particles, determine the particle size distribution, and use PFC software to generate particles;

[0123] (2) Considering the contact model between particles, the contact model between particles is set to an anti-rolling linear contact model, and boundary conditions are set to simulate the dynamic behavior between particles and other structural components.

[0124] S22, compacting the ballast particle micromechanical model to establish the three-dimensional ballasted track bed model.

[0125] In this embodiment, the compaction step S22 is as follows: Figure 6 As shown, including:

[0126] (1) In a specified area, ballast is generated three times, and after each generation, wall units are generated above the ballast particles and compacted using the servo control principle (e.g. Figure 6 (a) shows that the compressive stress is 200 kPa, and three compaction procedures are carried out. The ballast slope is 1:1.75, and the thickness of the final ballast bed model is 0.55 m. Then, walls are generated on the top surface of the ballast bed and the ballast slopes on both sides, and the final compaction is carried out. Figure 6 (b) as shown; finally, the particles in the sleeper area are deleted and the sleepers are placed, as shown in Figure 6 (c) as shown.

[0127] (2) By measuring the overall porosity of the ballast bed, the ρ of the final ballast bed model is calculated b About 1600kg / m 3 , meeting the requirements of the Heavy Haul Railway Design Code (TB 10625-2017). Viscoelastic artificial boundary conditions are used to reduce the reflection effect of the ballast edge and ensure the accuracy of the numerical simulation.

[0128] S3, establishing a finite difference model of the roadbed based on the finite difference method FDM, including: establishing a finite difference model of the roadbed based on the finite difference method FDM, including: the roadbed is regarded as a continuous medium, and the mechanical behavior and deformation characteristics of the roadbed under the train load are simulated based on the finite difference method FDM, thereby obtaining the finite difference model of the roadbed;

[0129] As a preferred implementation, S3 includes:

[0130] S31, the roadbed is regarded as a continuous medium, a roadbed grid division numerical model is established, and material properties and boundary conditions of the roadbed grid division numerical model are set;

[0131] In this embodiment, the specific location and method of setting up the boundary conditions are as follows:

[0132] (1) A wall unit is established on the roadbed surface in the FDM calculation area, and data information of velocity and force in the coupling process is transmitted through the wall unit to realize the interactive iterative coupling process of force and velocity between the DEM calculation area and the FDM calculation area.

[0133] The coupling process occurs at the contact interface between each sleeper and ballast, and at the contact interface between the roadbed and ballast, such as Figure 7 (a) The coupling mechanism is that the vertices of the coupling wall are connected by the mesh nodes at the coupling interface in the FDM calculation area, and the two move synchronously with each other. The coupled triangular wall surface will generate the contact force (F) generated by the particle motion in the PFC calculation area. c ) and contact torque (M c). However, since the Zone unit in FLAC cannot directly withstand bending moments, the concentrated forces are interpreted and transferred during the coupling calculation process, each grid vertex is equivalently weighted, and the equivalent weighted vertex force is transferred to the FDM grid. At the same time, according to Newton's second law, any displacement caused by the force at the grid point will also drive the movement of the coupled wall, which further leads to corresponding changes in the position of the particles in the DEM area. These changes in the relative position between the particles and the coupling interface lead to new FDM grids. c and M c The specific process is as follows Figure 7 (b) as shown.

[0134] (2) The continuous iteration of the above process realizes the real-time coupling between the discrete domain and the continuous domain.

[0135] S32, solving the numerical model of the roadbed mesh by finite difference method, simulating the mechanical behavior and deformation characteristics of the roadbed under the train load, thereby obtaining a DEM ballasted trackbed three-dimensional model including three sleepers. The model is shown as follows Figure 8 shown.

[0136] S4, setting a coupling medium to couple MBD-DEM-FDM, and performing real-time information exchange between MBD and DEM and FDM systems;

[0137] As a preferred implementation, S4 includes:

[0138] S41, using the coupling relationship of track-ballast-subgrade interface to establish the coupling model between MBD-DEM and DEM-FDM;

[0139] S42, achieving real-time coupling between the train multi-body system and the discrete ballast particle system by defining a mechanical transfer relationship between the rail and the sleeper;

[0140] S43, by setting an artificial viscoelastic boundary in the discrete element numerical model, an equivalent simulation between the ballast mass and the discrete ballast particles is achieved, thereby achieving real-time information exchange between the MBD and DEM and FDM systems.

[0141] In this embodiment, the implementation of step S4 includes: firstly transmitting the train load to the ballast-roadbed system through the spring damping system, and then transmitting the reaction force calculated in the ballast-roadbed system and the dynamic response of each structural layer to the upper train model in real time, so as to realize the real-time dynamic coupling calculation of the entire coupling system, wherein the real-time dynamic coupling calculation is used to simulate the dynamic response of the train when it is running. During the real-time dynamic coupling calculation process, the MBD and DEM and FDM systems will exchange information in real time to ensure that the interaction between the train and the track, ballast and roadbed is accurately captured. The specific flow chart is as follows: Fig. 9 shown.

[0142] like Fig. 9 As shown, the specific implementation process of this embodiment includes:

[0143] (1) The data interaction interface between the MBD part and the DEM-FDM part is established through Python program, and the motion response of the train is transmitted to the track bed and roadbed, and the corresponding calculation and judgment are performed. If the set threshold is met, the dynamic analysis of the next time step is performed. The specific judgment formula and process are shown in formula (6), formula (7) and Fig.10 As shown:

[0144] In order to accurately simulate the mechanical behavior of the fastener in the MBD and DEM systems, the fastener is equivalently modeled through a spring damping system. The equivalent force at the fastener at each time step is calculated in real time. The calculation formulas for the sleeper force in each three-dimensional direction are shown in equations (6) and (7):

[0145]

[0146]

[0147] Where: F x1 、F y1 、F z1 They represent the fastener forces acting on the left rail in the x, y, and z directions respectively; F x2 、F y2 、F z2 They represent the fastener forces acting on the right rail in the x, y, and z directions respectively; k x , k y , k z Respectively represent the spring stiffness coefficients of the fastener in the x, y, and z directions; c x 、c y 、c z Represent the damping coefficients of the fastener in the x, y, and z directions respectively.

[0148] (2) Establish the data interaction interface between the DEM part and the MBD part in the ballast structure layer through the PFC program:

[0149] A. First, the particle aggregate is equivalent to a three-dimensional block unit, and the equivalent axial stress inside the particle aggregate is calculated by formula (8):

[0150]

[0151] Where: a is the equivalent axial stress inside the particle assembly unit; F ai is the resultant axial contact force on the unit boundary; Di is the diameter of the boundary unit particle; F is the axial contact pressure on a single particle unit; D is the diameter of a single particle unit.

[0152] B. Next, establish boundary conditions, including: the viscoelastic artificial boundary is realized by arranging distributed springs and dampers on the truncated boundary. The spring is used to simulate the elastic recovery of the infinite domain, and the damper is responsible for absorbing energy. The spring and damper forces are applied in the normal and tangential directions respectively, so as to effectively simulate the energy propagation and absorption under dynamic conditions in the three-dimensional model. The calculated stress equation is formula (9):

[0153]

[0154] Where: n and σ s are the normal and tangential stresses respectively; C n and C s are the damping coefficients in the normal and tangential directions respectively; K n and K s are the spring stiffness in normal and tangential directions respectively; and are the normal and tangential velocities respectively; u n and u s are the normal and tangential displacements, respectively.

[0155] C. Discretization, including: In order to apply the viscoelastic boundary to the discrete element model, the formula needs to be discretized. By introducing the calibration coefficient β 3p , β 3s , and combined with the equivalent axial stress formula and the stress equation, the force formula of each particle on the boundary condition is obtained as shown in formula (10), and the calibration coefficients are adjusted to optimize the wave absorption effect, and the optimal values ​​of these coefficients are determined by a step-by-step iterative method.

[0156]

[0157] D. Based on the above process, the force of the spring damping system between the ballast mass blocks in the MBD system can be equivalent to the force of the granular ballast particles in the DEM system, and the force is updated in real time and transmitted to the DEM system. At the same time, the DEM system updates the dynamic response such as particle displacement, velocity, acceleration, etc. in real time, and calculates the dynamic change of the center of mass of the aggregate through the following formulas (11) and (12), and obtains the dynamic response of the aggregate and transmits it to the MBD system.

[0158] Center of mass displacement:

[0159] Center of mass velocity:

[0160] S5, establishing a coupling model based on MBD-DEM-FDM coupling and verifying and applying the coupling model, including: establishing a coupling model, obtaining simulation results based on the coupling model, and comparing and analyzing the simulation results with the on-site dynamic response to verify the correctness of the coupling model; establishing five ballast-deficient working conditions to calculate and obtain a schematic diagram of the particle contact force chain and a sleeper displacement acceleration curve to realize the application of the coupling model.

[0161] In this embodiment, the train-ballasted track-roadbed system simulation method based on MBD-DEM-FDM coupling is based on the on-site working parameters of the heavy-duty Shuohuang Railway Line. The axle weight of the HXD1 locomotive is 25t and it runs at a speed of 80km / h. The MBD-DEM-FDM coupling model is established to calculate the simulation results of the rail displacement and the sleeper displacement, which are compared and analyzed with the on-site measured dynamic response. Fig.11 As shown, it can be seen that the simulation results are in good agreement with the measured data, which verifies the correctness of the coupling method.

[0162] In addition, based on the on-site working condition parameters of the heavy-duty Shuohuang Railway Line, five working conditions were established: ballast missing in the middle of the sleeper, ballast missing at the rail support, partial ballast missing on both sides, large-area ballast missing on both sides, and complete ballast missing. Fig.12 As shown in the figure, the particle contact force chain diagram and the sleeper displacement acceleration curve are calculated as shown in Fig.13 As shown, the specific application of the MBD-DEM-FDM coupling model is realized.

[0163] Embodiment 2

[0164] like Fig.14 As shown, this embodiment provides a train-ballasted track-roadbed system simulation system based on MBD-DEM-FDM coupling, which is used to implement the method of embodiment 1, including:

[0165] The train model building module 101 is used to build a train model based on a multi-body dynamics MBD method, including: building a dynamic model of a train system based on the multi-body dynamics MBD method, in which the suspension system of the train is simplified by springs and dampers, and the interaction between the train and the track is considered;

[0166] The three-dimensional ballast model establishment module 102 is used to establish a three-dimensional ballast model based on the discrete element method DEM method; including: simulating the contact, friction and rolling behavior of ballast particles based on the discrete element method DEM, establishing a particle accumulation model by setting microscopic parameters such as particle gradation, size and density, and compacting the particle accumulation model to establish the three-dimensional ballast model;

[0167] The subgrade finite difference model building module 103 is used to build a subgrade finite difference model based on the finite difference method FDM, including: the subgrade is regarded as a continuous medium, and the mechanical behavior and deformation characteristics of the subgrade under the train load are simulated based on the finite difference method FDM, thereby obtaining the subgrade finite difference model;

[0168] MBD-DEM-FDM coupling module 104, used to set a coupling medium so as to couple MBD-DEM-FDM and perform real-time information exchange between MBD and DEM and FDM systems;

[0169] The coupling model establishment and verification application module 105 is used to establish a coupling model based on MBD-DEM-FDM coupling and verify and apply the coupling model, including: establishing a coupling model, obtaining simulation results based on the coupling model, and comparing and analyzing the simulation results with the on-site dynamic response to verify the correctness of the coupling model; establishing five ballast-deficient working conditions to calculate and obtain a particle contact force chain diagram and a sleeper displacement acceleration curve diagram to realize the application of the coupling model.

[0170] The embodiment of the present invention overcomes the limitations of the prior art by proposing a three-dimensional numerical simulation method based on MBD-DEM-FDM coupling in a train-ballasted track-roadbed system, and particularly achieves improvements and innovations in the following aspects:

[0171] 1. Coupling of multi-body dynamics MBD and discrete element method DEM: The embodiment of the present invention realizes real-time coupling of the multi-body dynamics model of the train and the discrete element model of the roadbed particles for the first time, which can accurately simulate the microscopic mechanical behavior of ballast particles under the action of train loads and reveal the complex mechanical effects in train load transfer. Compared with the simplified processing method of ballast particles in existing research, the present invention greatly improves the simulation accuracy by truly simulating the contact, rolling and friction of particles.

[0172] Technical effect: This method can more accurately predict the dynamic impact of train loads on track and roadbed systems, and effectively reveal the mechanical mechanism of problems such as long-term track settlement and roadbed deterioration.

[0173] 2. Establishment of a three-dimensional coupling model: By combining MBD, DEM and FDM, a complete train-track-ballast-roadbed coupling model is formed. This model can not only analyze the macroscopic dynamic response of the train and track, but also capture the microscopic mechanical behavior of the ballast through DEM, and analyze the deformation characteristics of the roadbed through FDM.

[0174] Technical effect: The model can accurately simulate the macro- and micro-dynamic responses of the train under different operating conditions, greatly enhancing the expressiveness of the overall mechanical behavior of the system and improving the ability to predict the deformation and damage of the track and roadbed.

[0175] 3. Coupling calculation interface: Based on Python program, the present invention realizes the coupling interface between MBD system and DEM system, and on this basis realizes multi-level coupling with FDM. This method can exchange the force and displacement information of each subsystem in real time, ensuring the efficient calculation and stability of the system.

[0176] Technical effect: Through this real-time coupled calculation, the present invention can simulate the complex dynamic behavior of the train under different working conditions, including the interaction between the train, track, ballast and roadbed, effectively reducing the need for on-site measurements.

[0177] Invention point:

[0178] 1. Establishment of MBD-DEM-FDM coupled numerical model: A three-dimensional coupled computational model based on multibody dynamics, discrete element method and finite difference method is proposed to simulate the dynamic interaction of the train-track-ballast-roadbed system.

[0179] 2. Real-time coupling calculation interface: The embodiment of the present invention realizes the real-time coupling of MBD with DEM and FDM systems through Python program, and performs dynamic information exchange.

[0180] 3. Discrete element ballast bed particle micromechanical model: The embodiment of the present invention aims at the micromechanical behavior of ballast particles, and establishes a discrete element model that takes into account particle contact, rolling and friction, which can accurately simulate the microdynamic response of the ballast bed.

[0181] 4. Equivalent processing method of coupling interface: Through the spring damping system between the track and the ballast bed, the coupling calculation of MBD and DEM, DEM and FDM is realized, and the mechanical properties of each layer structure are taken into account.

[0182] The present invention also provides a memory storing a plurality of instructions, wherein the instructions are used to implement the method as in the first embodiment.

[0183] like Fig.15 As shown, the present invention also provides an electronic device, including a processor 301 and a memory 302 connected to the processor 301, the memory 302 stores a plurality of instructions, and the instructions can be loaded and executed by the processor so that the processor can execute the method as in the first embodiment.

[0184] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. The train-ballasted track-roadbed system simulation method based on MBD-DEM-FDM coupling is characterized by: include: S1, establishing a train model based on a multi-body dynamics MBD method, including: establishing a dynamic model of a train system based on the multi-body dynamics MBD method, wherein the suspension system of the train is simplified by springs and dampers, and the interaction between the train and the track is considered in the dynamic model of the train system; S2, establish a three-dimensional ballasted track bed model based on discrete element method DEM; S3, establishing a finite difference model of the roadbed based on the finite difference method FDM, including: the roadbed is regarded as a continuous medium, and the mechanical behavior and deformation characteristics of the roadbed under the train load are simulated based on the finite difference method FDM, thereby obtaining the finite difference model of the roadbed; S4, setting a coupling medium to couple MBD-DEM-FDM, and performing real-time information exchange between MBD and DEM and FDM systems; S5, establishing a coupling model based on MBD-DEM-FDM coupling and verifying and applying the coupling model, including: establishing a coupling model, obtaining simulation results based on the coupling model, and comparing and analyzing the simulation results with the on-site dynamic response to verify the correctness of the coupling model; establishing five ballast-deficient working conditions to calculate and obtain a schematic diagram of the particle contact force chain and a sleeper displacement acceleration curve to realize the application of the coupling model.

2. The method for simulating a train-ballasted track-roadbed system based on MBD-DEM-FDM coupling according to claim 1, characterized in that: The S1 includes: S11, based on MBD theory, a rigid body consisting of a car body, a bogie, and a wheelset is established, wherein the car body is connected to the two bogies through a primary suspension system and a secondary suspension system, and a spring and a damper of the suspension system are simplified into a linear model; S12, in the modeling of the suspension system, the connection between the vehicle body and the bogie, and the connection between the bogie and the wheelset are simulated by linear springs and dampers; S13, based on the Hamiltonian principle, starting from the total kinetic energy, total potential energy and virtual work of the system, through the construction of a generalized coordinate system, the mass matrix, stiffness matrix, damping matrix and load matrix of the system are obtained, and finally the vibration dynamics equations of the train system are formed, which are: Where: M v , C v and K v are the mass matrix, damping matrix and stiffness matrix of the train vehicle, respectively, and F v is the load vector, X v is the displacement matrix; S14, establishing a three-dimensional train-track model, including: calculating the normal force between the wheel and rail based on the Hertz nonlinear contact theory; simulating the wheel-rail tangential contact force based on the Kalker creep theory; establishing a wheel-rail contact coupling model based on the normal force between the wheel and rail and the tangential contact force between the wheel and rail, wherein the wheel-rail contact coupling model can accurately calculate the dynamic changes of the wheel-rail contact during the train operation; continuing to comprehensively consider four different types of track unevenness, wherein the four types of track unevenness include height unevenness, direction unevenness, horizontal unevenness and regular unevenness, including: different types of track unevenness obtained by simulation and analysis using the trigonometric series method are input as external excitations into the wheel-rail contact coupling model to obtain a first comprehensive sample of height unevenness and horizontal unevenness, and a second comprehensive sample of gauge unevenness and direction unevenness; establishing the three-dimensional train-track model based on the first comprehensive sample and the second comprehensive sample; S15, calculating the dynamic model of the train system based on the Wilson-θ integration method, including: firstly discretizing the vibration dynamics equations of the train system, introducing a correction factor θ to adjust the response in each time step by setting equally spaced discrete time points, and adjusting the acceleration, velocity and displacement of the next time step to reflect the correction effect of the current time step; then, gradually correcting the response of the system through an iterative process in each time step until a given convergence condition is met.

3. The train-ballasted track-roadbed system simulation method based on MBD-DEM-FDM coupling according to claim 2 is characterized in that: The S2 includes: S21, constructing a mesoscopic mechanical model of ballast particles, including: simulating the contact, friction and rolling behaviors of ballast particles based on the discrete element method DEM, and establishing a particle accumulation model as the mesoscopic mechanical model of ballast particles by setting mesoscopic parameters such as particle gradation, size and density; S22, compacting the ballast particle micromechanical model to establish the three-dimensional ballasted track bed model.

4. The train-ballasted track-roadbed system simulation method based on MBD-DEM-FDM coupling according to claim 3 is characterized in that: The S21 includes: (1) Define the geometric parameters of ballast particles, determine the particle size distribution, and use PFC software to generate particles; (2) Considering the contact model between particles, the contact model between particles is set to an anti-rolling linear contact model, and boundary conditions are set to simulate the dynamic behavior between particles and other structural components.

5. The method for simulating a train-ballasted track-roadbed system based on MBD-DEM-FDM coupling according to claim 4, characterized in that: The S22 includes: (1) In the designated area, ballast was generated three times. After each generation, a wall unit was generated above the ballast particles and compacted by the servo control principle. The compressive stress was 200 kPa. A total of three compaction procedures were performed. The ballast slope was 1:1.75, and the thickness of the final roadbed model was 0.55 m. Then, walls were generated on the top surface of the roadbed and the ballast slopes on both sides, and the last compaction was performed. Finally, the particles in the sleeper area were deleted and the sleepers were placed. (2) By measuring the overall porosity of the ballast bed, the ρ of the final ballast bed model is calculated b About 1600kg / m 3 , meeting the requirements of the "Heavy Haul Railway Design Code" (TB 10625-2017).

6. The method for simulating a train-ballasted track-roadbed system based on MBD-DEM-FDM coupling according to claim 5, characterized in that: The S3 includes: S31, the roadbed is regarded as a continuous medium, a roadbed grid division numerical model is established, and material properties and boundary conditions of the roadbed grid division numerical model are set; S32, solving the roadbed grid numerical model using a finite difference method to simulate the mechanical behavior and deformation characteristics of the roadbed under the train load, thereby obtaining the roadbed finite difference model.

7. The method for simulating a train-ballasted track-roadbed system based on MBD-DEM-FDM coupling according to claim 6, characterized in that: The S4 includes: S41, using the coupling relationship of track-ballast-subgrade interface to establish the coupling model between MBD-DEM and DEM-FDM; S42, achieving real-time coupling between the train multi-body system and the discrete ballast particle system by defining a mechanical transfer relationship between the rail and the sleeper; S43, by setting an artificial viscoelastic boundary in the discrete element numerical model, an equivalent simulation between the ballast mass and the discrete ballast particles is achieved, thereby achieving real-time information exchange between the MBD and DEM and FDM systems.

8. A train-ballasted track-roadbed system simulation system based on MBD-DEM-FDM coupling, used to implement the method of the first aspect, comprising: A train model building module (101) is used to build a train model based on a multi-body dynamics (MBD) method, comprising: building a dynamics model of a train system based on the multi-body dynamics (MBD) method, wherein the train suspension system is simplified by using springs and dampers, and the interaction between the train and the track is considered; A three-dimensional ballast model establishment module (102) is used to establish a three-dimensional ballast model based on a discrete element method (DEM); comprising: simulating the contact, friction and rolling behavior of ballast particles based on the discrete element method (DEM), establishing a particle accumulation model by setting microscopic parameters such as particle gradation, size and density, and compacting the particle accumulation model to establish the three-dimensional ballast model; A roadbed finite difference model building module (103) is used to build a roadbed finite difference model based on a finite difference method FDM, comprising: the roadbed is regarded as a continuous medium, and the mechanical behavior and deformation characteristics of the roadbed under the action of train load are simulated based on the finite difference method FDM, thereby obtaining the roadbed finite difference model; MBD-DEM-FDM coupling module (104), used to set a coupling medium so as to couple MBD-DEM-FDM and perform real-time information exchange between MBD and DEM and FDM systems; A coupling model establishment and verification application module (105) is used to establish a coupling model based on MBD-DEM-FDM coupling and verify and apply the coupling model, including: establishing a coupling model, obtaining simulation results based on the coupling model, and comparing and analyzing the simulation results with the on-site dynamic response to verify the correctness of the coupling model; establishing five ballast-deficient working conditions to calculate and obtain a particle contact force chain diagram and a sleeper displacement acceleration curve diagram to realize the application of the coupling model.

9. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores a plurality of instructions, and the processor is used to read the instructions and execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a plurality of instructions, and the plurality of instructions can be read by a processor to execute the method according to any one of claims 1 to 7.

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