Method and system for predicting long-term settlement of ballastless track subgrade of high-speed railway

Abstract

The invention relates to the technical field of railway subgrade engineering, and discloses a long-term settlement prediction method and system for a ballastless track subgrade of a high-speed railway, and the method comprises the steps: determining the relational data of the cumulative plastic strain of subgrade filler and the cyclic dynamic load action frequency; establishing a cumulative plastic strain prediction empirical model; carrying out numerical simulation on long-term settlement of a target roadbed by enabling the cyclic load action times to be equivalent to a time measurement unit and enabling accumulated plastic strain to be equivalent to static creep, and constructing a track-roadbed finite element model and a train-track multi-body dynamic model; carrying out joint simulation by utilizing iterative calculation to establish a train-track-roadbed coupling dynamics numerical simulation model; the train speed, the operation time, the initial moisture content of the roadbed and the number of times of humidification are substituted into the train-rail-roadbed coupling dynamics numerical simulation model to calculate the vertical deformation of the top face of the roadbed, and the long-term settlement evolution law of the target roadbed is predicted based on the vertical deformation of the top face of the roadbed.

Description

Technical Field

[0001] The present invention relates to the technical field of railway subgrade engineering, and particularly to a method and system for predicting long-term settlement of ballastless track subgrade of high-speed railway. Background Art

[0002] During the operation of high-speed railways in humid and rainy regions, due to the influence of natural factors such as rainfall and groundwater level fluctuations, the subgrade is in an environment of wetting and drying alternation for a long time, which easily causes significant changes in the mechanical properties of the subgrade soil, and further affects the settlement characteristics of the subgrade. With the rapid development of high-speed railways, the problem of subgrade settlement has gradually become one of the key factors affecting the operation safety and comfort of high-speed railways. Due to its special engineering geological characteristics and operation environment, the red clay subgrade of high-speed railways is prone to significant cumulative settlement under the action of wetting, which further affects the safety and stability of train operation. Therefore, in order to improve the safety and stability of train operation and understand the settlement change of the subgrade under the action of wetting, it is necessary to predict the settlement of the subgrade.

[0003] Currently, in the prior art, the commonly used subgrade settlement prediction methods mainly include the layer-wise summation method, curve fitting method, finite element method, etc. However, these methods have many deficiencies in predicting the settlement evolution of high-speed railway subgrades with some specific soil types, especially the red clay subgrades of high-speed railways under the action of wetting. For example, the layer-wise summation method is difficult to consider the influence of lateral deformation of soil and time factors. Although the curve fitting method can establish a relationship model between settlement and time, it is difficult to accurately describe the influence of wetting on settlement evolution. The finite element method, on the other hand, requires the establishment of a complex mathematical model, with a large amount of calculation and sensitivity to parameters, and there is usually a large deviation between the calculated long-term settlement and the actual value. It can be seen that the existing subgrade settlement prediction methods have problems of incomplete factor consideration and low calculation accuracy. Summary of the Invention

[0004] The present invention provides a method and system for predicting long-term settlement of ballastless track subgrade of high-speed railway to solve the problems of incomplete factor consideration and low calculation accuracy existing in the existing subgrade settlement prediction methods.

[0005] To achieve the above object, the present invention is realized through the following technical solutions: In the first aspect, the present invention provides a method for predicting long-term settlement of ballastless track subgrade of high-speed railway, including: Collecting target subgrade fillers, and determining the relationship data between the cumulative plastic strain of the subgrade fillers and the number of cyclic dynamic loadings according to the moisture content, number of wetting times and dynamic stress characteristics of the target subgrade fillers; Based on the relationship data between the cumulative plastic strain of the dynamic subgrade fillers and the number of cyclic dynamic loadings, establishing an empirical model for predicting cumulative plastic strain considering the amplitude of moisture content, number of wetting times and amplitude of dynamic stress; Equivalent the number of cyclic load applications to a time measurement unit, and the cumulative plastic strain to static creep, then conduct a numerical simulation on the long-term settlement of the target subgrade. Based on the numerical simulation results, construct a finite element model of the track-subgrade; Construct a multi-body dynamics model of the train-track. Use iterative calculations to conduct a joint simulation on the finite element model of the track-subgrade and the multi-body dynamics model of the train-track to establish a numerical simulation model of the train-track-subgrade coupled dynamics; Substitute the train speed, operation time, initial water content of the subgrade, and the number of wetting times into the numerical simulation model of the train-track-subgrade coupled dynamics to calculate the vertical deformation of the subgrade top surface, and predict the long-term settlement evolution law of the target subgrade based on the vertical deformation of the subgrade top surface.

[0006] Optionally, the relationship data between the cumulative plastic strain of the subgrade filler and the number of cyclic dynamic load applications determined according to the water content, the number of wetting times, and the characteristics of the dynamic stress applied to the target subgrade filler includes: Conduct dynamic triaxial tests based on the water content, the number of wetting times, and the characteristics of the dynamic stress applied to the target subgrade filler to obtain the relationship curve between the cumulative plastic strain of the target subgrade filler and the number of cyclic dynamic load applications; Take the relationship curve between the cumulative plastic strain and the number of cyclic dynamic load applications as the relationship data between the cumulative plastic strain of the target subgrade filler and the number of cyclic dynamic load applications.

[0007] Optionally, establishing an empirical formula for predicting cumulative plastic strain considering the amplitude of water content, the number of wetting times, and the amplitude of dynamic stress based on the relationship data between the cumulative plastic strain of the subgrade filler and the number of cyclic dynamic load applications includes: According to the relationship data between the cumulative plastic strain of the subgrade filler and the number of cyclic dynamic load applications, with the water content ratio, the amplitude of dynamic stress, the number of wetting times, and the number of vibrations as variables, construct empirical models for predicting cumulative plastic strain for stable subgrades and failed subgrades respectively; For the empirical model for predicting cumulative plastic strain of a stable subgrade, the model satisfies the following relationship: ; For the empirical model for predicting cumulative plastic strain of a failed subgrade, the model satisfies the following relationship: ; In the formula, represents the predicted cumulative plastic strain, represents the water content of the soil mass, represents the optimal water content of the soil mass, represents the amplitude of dynamic stress, represents the local atmospheric pressure, represents the number of cyclic wetting times, represents the number of dynamic load applications. k1, k2, k3, k4, k5, and b are all fitting coefficients, which are obtained by performing non-linear least squares curve fitting using the Levenberg-Marquardt algorithm.

[0008] Optionally, the numerical simulation of the long-term settlement of the target subgrade by equating the number of cyclic load applications to a time measurement unit and the cumulative plastic strain to static creep includes: The numerical simulation of the long-term settlement of the target subgrade is equivalent to the calculation of soil strain. The number of cyclic load applications is equated to a time measurement unit, and the cumulative plastic strain is equated to static creep to calculate the soil strain. The calculation of soil strain includes elastic strain calculation, plastic strain calculation, and creep calculation; The critical state theory is used to calculate the time-independent elastic strain. The stiffness constant expressed in terms of modulus in the elastic strain calculation is: ; ; In the formula, K and G are the elastic bulk compression modulus and shear modulus respectively, E is the elastic modulus, μ is the Poisson's ratio, e is the soil void ratio, is the slope of the rebound line in the e-lnp space, is the effective mean stress; The plastic strain is calculated by following the yield criterion of the modified Cam clay model and the associated flow rule. On the premise that the plastic potential function is the same as the yield surface function, the calculation of the plastic strain satisfies the following relationship: ; In the formula, is the slope of the critical state line, is the deviator stress, and in the calculation formula here , J2 is the second invariant of the deviator stress tensor, is the preconsolidation pressure of the soil, is the effective mean stress; The calculation for creep satisfies the following relationship: ; In the formula, is the empirical expression of the axial cyclic cumulative strain rate of the soil sample under undrained triaxial conditions established based on experimental or measured data, is the creep potential function, is the rate-dependent cyclic cumulative strain rate tensor, is the dynamic stress level, is the total strain rate, is the dynamic load application time, is other internal variables, is the effective mean stress, is the partial derivative symbol.

[0009] Optionally, the method of using iterative calculation to jointly simulate the track-subgrade finite element model and the train-track multibody dynamics model to establish a train-track-subgrade coupled dynamics numerical simulation model includes: Derive the wheel-rail force data from the train-track multibody dynamics model, and apply the wheel-rail force data to the rail surface of the track-subgrade finite element model to obtain the rail surface lateral deformation data and the rail surface longitudinal deformation data; Apply the rail surface lateral deformation data and the rail surface longitudinal deformation data to the track structure in the train-track multibody dynamics model to derive new wheel-rail force data, forming an iterative loop; After reaching the preset cycle time, extract the mechanical response data, and use the mechanical response data to eliminate the initial instability in the train-track multibody dynamics model and the influence of the boundary conditions in the track-subgrade finite element model; Based on the train-track multibody dynamics model with initial instability eliminated and the track-subgrade finite element model with the influence of boundary conditions eliminated, establish a train-track-subgrade coupled dynamics numerical simulation model.

[0010] Optionally, the wheel-rail force data includes: vertical force and lateral force, and the rail surface lateral deformation data and the rail surface longitudinal deformation data are obtained by superimposing the high-speed railway random unevenness spectrum and the vehicle-induced track additional unevenness.

[0011] Optionally, substituting the train speed, operation time, initial water content of the subgrade, and wetting times into the train-track-subgrade coupled dynamics numerical simulation model to calculate the vertical deformation amount of the subgrade top surface includes: Input parameters such as subgrade water content, cyclic wetting times, train speed, and prediction duration to obtain the joint simulation results of the train-track multibody dynamics model and the track-subgrade finite element model, and draw the time history curves of the vertical deformation amount and settlement rate of the subgrade top surface based on the simulation results.

[0012] In a second aspect, an embodiment of the present application provides a long-term settlement prediction system for a ballastless track subgrade of a high-speed railway, including a fitting device and a prediction device; The fitting device is used to fit the curve into a function including wetting times, water content amplitude, train speed, and prediction time according to the time history data of the vertical deformation amount of the subgrade top surface obtained by the method in the first aspect; A predictor, which is used to input the number of wetting times, the amplitude of water content, the train speed, and the prediction time, calculate and plot the time history curve of the vertical deformation of the subgrade top surface within the prediction time range, and compare it with the preset subgrade settlement threshold to give an over-limit warning message.

[0013] Beneficial effects: The long-term settlement prediction method for the ballastless track subgrade of high-speed railways provided by the present invention establishes a more accurate empirical formula for predicting the cumulative plastic strain by considering multiple factors such as wetting characteristics, including the amplitude of water content, the number of wetting times, and the amplitude of dynamic stress. This enables a closer approximation to the actual situation when predicting the settlement evolution law of the red clay subgrade of high-speed railways during long-term operation, significantly improving the prediction accuracy. At the same time, by establishing a train-track-subgrade coupled dynamic numerical simulation model, this model can comprehensively consider the dynamic response of the subgrade under the action of train dynamic loads. Through the method of cyclic iteration for joint simulation, it can more realistically simulate the actual situation when the train runs on the high-speed railway line, providing more reliable data support for settlement prediction; The creep static equivalent theory is introduced in the calculation, and the cumulative deformation under long-term cyclic loads is regarded as static creep, which can more accurately simulate the mechanical behavior under long-term dynamic wetting action, further improving the accuracy of settlement prediction. And in the stage of predicting the settlement evolution, it not only provides the time history curves of the top surface settlement and settlement rate under different combinations of the number of subgrade wetting times and the amplitude of water content, but also can realize the rapid prediction and evaluation warning of the long-term subgrade settlement, and can more comprehensively evaluate the impact of subgrade settlement on the train operation performance. Description of the drawings

[0014] Figure 1 It is one of the flowcharts of the long-term settlement prediction method for the ballastless track subgrade of high-speed railways in the preferred embodiment of the present invention; Figure 2 It is the second flowchart of the long-term settlement prediction method for the ballastless track subgrade of high-speed railways in the preferred embodiment of the present invention; Figure 3 It is the numerical calculation flowchart of the cumulative plastic deformation in the preferred embodiment of the present invention; Figure 4 It is the schematic diagram of the train-track model provided by the preferred embodiment of the present invention; Figure 5 It is the schematic diagram of the track-subgrade model provided by the preferred embodiment of the present invention; Figure 6 It is the joint simulation flowchart of the train-track-subgrade coupled dynamic model provided by the preferred embodiment of the present invention; Figure 7 It is the comparison schematic diagram of the predicted value and the measured value of the subgrade settlement provided by the preferred embodiment of the present invention. Specific implementation manners

[0015] The technical solutions of the present invention will be described clearly and completely below. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0016] Unless otherwise defined, the technical terms or scientific terms used in the present invention shall have the ordinary meanings understood by those of ordinary skill in the art to which the present invention pertains. The "first", "second" and similar terms used in the present invention do not denote any order, quantity or importance, but are only used to distinguish different components. Similarly, the terms such as "a" or "one" do not denote a quantity limitation, but mean that there is at least one. The terms such as "connected" or "coupled" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The terms such as "upper", "lower", "left" and "right" are only used to represent relative position relationships. When the absolute position of the object being described changes, the relative position relationship also changes accordingly.

[0017] Please refer to Figure 1 , the embodiments of the present application provide a method for predicting long-term settlement of a ballastless track subgrade of a high-speed railway, including: Collecting target subgrade fillers, and determining the relationship data between the accumulated plastic strain of the subgrade fillers and the number of cyclic dynamic loadings according to the moisture content, wetting times and dynamic stress characteristics of the target subgrade fillers; Based on the relationship data between the accumulated plastic strain of the dynamic subgrade fillers and the number of cyclic dynamic loadings, establishing an empirical model for predicting the accumulated plastic strain considering the amplitude of moisture content, wetting times and amplitude of dynamic stress; Equivalent the number of cyclic loadings to a time measurement unit, and equivalent the accumulated plastic strain to static creep to perform numerical simulation on the long-term settlement of the target subgrade, and construct a track-subgrade finite element model based on the numerical simulation results; Constructing a train-track multibody dynamics model, and performing joint simulation on the track-subgrade finite element model and the train-track multibody dynamics model by iterative calculation to establish a train-track-subgrade coupled dynamics numerical simulation model; Substituting the train speed, operation time, initial moisture content and wetting times of the subgrade into the train-track-subgrade coupled dynamics numerical simulation model to calculate the vertical deformation amount of the subgrade top surface, and predicting the long-term settlement evolution law of the target subgrade based on the vertical deformation amount of the subgrade top surface.

[0018] In the above embodiments, by incorporating the number of wetting cycles of the subgrade and the amplitude of water content into the prediction system of subgrade settlement, the problem in the existing settlement prediction that only considers the temperature effect but not the wetting effect is improved, and the prediction accuracy is enhanced.

[0019] As Figure 2 shown, the above embodiments can be further refined into the following steps: Step 1: Prepare specimens with water contents of 20.5%, 22.0%, 23.5%, and 25.0%. For each water content, prepare several specimens with wetting cycle numbers n = 0, 1, 2, 3, and 4. Step 2: Conduct dynamic triaxial tests, which are achieved through the following process: The dynamic stress is selected as 30 kPa, 50 kPa, 70 kPa, and 90 kPa. The semi - sine waveform is used for cyclic loading of the dynamic load, the loading frequency f is 1 Hz, the loading time is 0.1 s, and the intermittent time is 0.9 s. At the same time, considering the vertical load generated by the overlying track structure of the subgrade soil, after applying the confining pressure, a static deviator stress of 0.5 times the confining pressure is applied. From 5 different cyclic numbers, 4 different water content amplitudes, and 4 different dynamic stress amplitudes, the time - history curves of the cumulative strain of the specimens under a total of 80 test conditions are obtained.

[0020] Step 3: Combining the above dynamic triaxial test results, referring to the common form of the cumulative strain prediction model, using the water content ratio w / w OMC , dynamic stress amplitude σ d , wetting cycle number n, and vibration number N as variables, establish cumulative strain prediction models for stable and failure types respectively.

[0021] For the stable - type prediction model, its relationship is as follows: ; For the failure - type prediction model, its relationship is as follows: ; In the formula, represents the predicted cumulative plastic strain, represents the water content of the soil, represents the optimum water content of the soil, represents the dynamic stress amplitude, represents the local atmospheric pressure, represents the number of cyclic wetting, represents the number of dynamic load applications, and k1, k2, k3, k4, k5, and b are all fitting coefficients, which are obtained by using the Levenberg - Marquardt algorithm for nonlinear least - squares curve fitting.

[0022] Step 4: Use the Levenberg - Marquardt algorithm for nonlinear least - squares curve fitting to obtain the fitting coefficients as shown in Table 1 below: Table 1: Fitting Coefficients under Different Model Types

[0023] Step 5: Combining the creep static equivalence theory, regarding the cumulative deformation under long-term cyclic loading as static creep, and equivalenting the number of cyclic loading applications to a time measurement unit, numerically simulate the long-term settlement of the subgrade on the ABAQUS platform, and write the above prediction model in the form of a UMAT subroutine. Calculate the soil strain under cyclic dynamic loading separately for elastic strain, plastic strain, and creep parts.

[0024] Furthermore, use the critical state theory to calculate the time-independent elastoplastic deformation. For the elastic deformation part, its stiffness constants are: ; ; where K and G are the elastic bulk compression modulus and shear modulus respectively, E is the elastic modulus, μ is the Poisson's ratio, e is the soil void ratio, is the slope of the rebound line in the e-lnp space, is the effective mean stress.

[0025] For plastic deformation, adopt the yield criterion following the modified Cam clay model and the associated flow rule. The plastic potential function is the same as the yield surface function, that is: ; where, is the slope of the critical state line, is the deviatoric stress, and in the calculation formula here , J2 is the second invariant of the deviatoric stress tensor, is the preconsolidation pressure of the soil, is the effective mean stress.

[0026] Furthermore, considering the similarity between the development law of the cumulative residual deformation of the soil under long-term cyclic loading and the creep deformation of the soil under static loading, equivalent the number of cyclic loading applications to a time measurement unit, introduce the creep potential function in the creep calculation theory, and combine the empirical model of the cyclic cumulative deviator strain of the soil under undrained conditions to establish a simplified calculation method for describing the cyclic cumulative deformation of the soil. The cyclic cumulative strain rate tensor related to time can be expressed as: ; where, is the empirical expression of the axial cyclic cumulative strain rate of the soil sample under undrained triaxial conditions established based on experimental or measured data, is the creep potential function, is the rate-dependent cyclic cumulative strain rate tensor, is the dynamic stress level, is the total strain rate, is the dynamic load application time, are other internal variables, is the effective mean stress, is the partial derivative symbol.

[0027] With the help of the user subroutine interface provided by the large commercial software Abaqus, the above algorithm is written into a UMAT subroutine. The numerical simulation workflow is as Figure 3 shown, and the input parameters include the number of soil wetting times and the amplitude of water content.

[0028] Step 6: Based on the SIMPACK software, a vehicle-track multi-body dynamics simulation model is established. The physical and mechanical parameters of the car body are those of the CRH380A EMU train. As Figure 4 shown, taking this embodiment as an example, the car body of the vehicle-track multi-body dynamics simulation model established uses the CRH380A EMU train, with a length of 25000 mm, a car body height of 3700 mm, a wheel pair interval of 2500 mm between wheel pair groups, a wheel pair group interval of 17500 mm, a car body center of gravity height of 1520 mm, and a bogie center of gravity height of 510 mm.

[0029] Step 7: Taking the CRTS-I type double-block ballastless track of high-speed railway as an example, a track-subgrade finite element simulation model is established based on the Abaqus software. The model is 65 m long longitudinally, 30 m wide and 10 m high at the foundation. The cross-sectional dimensions are drawn according to the standard design drawing of the subgrade section of the CRTS-I type double-block ballastless track, and the slope of the subgrade slope is taken as 1:1.5. As Figure 5 shown, the simulation model includes a track structure, a subgrade structure and an intermediate filling area. The track structure consists of 60 kg / m rail 1, WG-I sleeper 2, track slab 3, and support layer 4. The subgrade structure consists of asphalt concrete 5, subgrade surface layer 6, subgrade bottom layer 7, subgrade body 8, and foundation soil 9. The intermediate filling area consists of C25 concrete 10 and graded crushed stone 11. The material property parameters of each component are taken as the measured values of a certain section of the Wuhan-Guangzhou high-speed railway. The subgrade part uses a custom red clay material and associates with the UMAT subroutine.

[0030] Step 8: Use the iterative simulation scheme as Figure 6 shown to conduct a co-simulation on the vehicle-track multi-body dynamics simulation model and the track-subgrade finite element simulation model.

[0031] In a single loop, the wheel-rail force data exported by SIMPACK is applied to the rail surface of the ABAQUS model, and the lateral and longitudinal deformation data of the rail surface exported by ABAQUS is applied to the track structure of the SIMPACK model. Sampling (from the SIMPACK simulation results) and repetition (for the longitudinal rail surface deformation data) are used during data transplantation; Starting from the 10th second of the output results of the vehicle-track model, mechanical response data is extracted to eliminate the influence of the initial instability of the train model and the boundary conditions of the track-subgrade finite element model; Taking the average value of the wheel-rail forces during the train passing period as the equivalent static load, it is applied at the longitudinal midpoint of the track-subgrade model; The wheel-rail forces include vertical forces and lateral forces, and the rail surface deformation is obtained by superimposing the high-speed railway random unevenness spectrum and the vehicle-induced additional unevenness of the track.

[0032] Simulate 1500 trains passing unidirectionally at a speed of 250 km / h in sequence, and obtain the time history curve of the cumulative plastic strain on the subgrade top surface along the center line of the track after the wheel set cyclic load is applied 48000 times, as Figure 7 shown. It can be seen that when using the cyclic iteration method for simulation, the cumulative deformation amount on the subgrade top surface obtained when 1500 trains pass is 1.15 mm, which is 2.22% smaller than the measured value; while the result obtained by the traditional method without considering cyclic iteration is 0.98 mm, which is 16.75% smaller than the measured value. This shows that the static creep equivalent model and the cyclic iteration method proposed in the present invention can effectively simulate the development of subgrade settlement.

[0033] Step Nine: Change the wetting times, moisture content amplitude, and train speed parameters of the input model to obtain settlement prediction results including but not limited to the time history curves of the subgrade top surface settlement amount and settlement rate.

[0034] Under different wetting times, when the moisture content of the subgrade red clay is 20.5%, the simulation calculation results of the settlement evolution of the subgrade top surface when 10000 pairs of trains pass bidirectionally are shown in Table 2: Table 2: Simulation calculation results of the settlement evolution of the subgrade top surface under different wetting times

[0035] Under different soil moisture contents, when the subgrade filler has not experienced cyclic wetting, the simulation calculation results of the settlement evolution of the subgrade top surface when the EMU passes at 350 km / h for 10000 trains are shown in Table 3: Table 3: Simulation calculation results of the settlement evolution of the subgrade top surface under different soil moisture contents

[0036] An embodiment of the present invention further provides a long-term settlement prediction system for the ballastless track subgrade of high-speed railways, including a fitting device and a prediction device; The fitting device is configured to fit a curve into a function including the number of wetting times, the moisture content amplitude, the train speed, and the prediction time according to the time history data of the vertical deformation amount of the subgrade top surface obtained by the long-term settlement prediction method for the ballastless track subgrade of high-speed railways; The prediction device is configured to input parameters such as the number of wetting times, the moisture content amplitude, the train speed, and the prediction time, calculate and plot the time history curve of the vertical deformation amount of the subgrade top surface within the prediction time range, and compare it with a preset subgrade settlement threshold to give an over-limit warning message.

[0037] The preferred specific embodiments of the present invention have been described in detail above. It should be understood that those of ordinary skill in the art can make many modifications and variations according to the concept of the present invention without creative work. Therefore, all technical solutions that can be obtained by those skilled in the art in the technical field of the present invention based on the concept of the present invention through logical analysis, reasoning, or limited experiments should be within the protection scope determined by the claims.

Claims

1. A long-term settlement prediction method for ballastless track subgrade of high-speed railway, characterized in that, Including: Collecting target subgrade fillers, and determining the relationship data between the cumulative plastic strain of the subgrade fillers and the number of cyclic dynamic loadings according to the water content, wetting times, and dynamic stress characteristics of the target subgrade fillers; Establishing an empirical prediction model for cumulative plastic strain considering the amplitude of water content, wetting times, and dynamic stress amplitude based on the relationship data between the cumulative plastic strain of the subgrade fillers and the number of cyclic dynamic loadings; Equivalenting the number of cyclic loadings to a time measurement unit and the cumulative plastic strain to static creep to conduct numerical simulation of the long-term settlement of the target subgrade, and constructing a finite element model of the track-subgrade based on the results of the numerical simulation; Constructing a multi-body dynamics model of the train-track, and using an iterative calculation method to conduct joint simulation of the finite element model of the track-subgrade and the multi-body dynamics model of the train-track to establish a numerical simulation model of the train-track-subgrade coupled dynamics; Substituting the train speed, operation time, initial water content of the subgrade, and wetting times into the numerical simulation model of the train-track-subgrade coupled dynamics to calculate the vertical deformation of the subgrade top surface, and predicting the long-term settlement evolution law of the target subgrade based on the vertical deformation of the subgrade top surface.

2. The long-term settlement prediction method for the ballastless track subgrade of high-speed railway according to claim 1, characterized in that, The determining the relationship data between the cumulative plastic strain of the subgrade fillers and the number of cyclic dynamic loadings according to the water content, wetting times, and dynamic stress characteristics of the target subgrade fillers includes: Conducting dynamic triaxial tests based on the water content, wetting times, and dynamic stress characteristics of the target subgrade fillers to obtain the relationship curve between the cumulative plastic strain of the target subgrade fillers and the number of cyclic dynamic loadings; Taking the relationship curve between the cumulative plastic strain and the number of cyclic dynamic loadings as the relationship data between the cumulative plastic strain of the target subgrade fillers and the number of cyclic dynamic loadings.

3. The method for predicting the long-term settlement of the ballastless track subgrade of high-speed railway according to claim 1, characterized in that, The establishing an empirical prediction formula for cumulative plastic strain considering the amplitude of water content, wetting times, and dynamic stress amplitude based on the relationship data between the cumulative plastic strain of the subgrade fillers and the number of cyclic dynamic loadings includes: According to the relationship data between the cumulative plastic strain of the subgrade fillers and the number of cyclic dynamic loadings, using the water content ratio, dynamic stress amplitude, wetting times, and vibration times as variables to construct empirical prediction models for cumulative plastic strain for stable subgrades and failure subgrades respectively; For the empirical prediction model of cumulative plastic strain of stable subgrades, the empirical prediction model of cumulative plastic strain of stable subgrades satisfies the following relational expression: ； For the empirical prediction model of cumulative plastic strain of failure subgrades, the empirical prediction model of cumulative plastic strain of failure subgrades satisfies the following relational expression: ； In the formula, represents the predicted cumulative plastic strain, represents the water content of the soil, represents the optimum water content of the soil, represents the dynamic stress amplitude, represents the local atmospheric pressure, represents the number of cyclic wetting, represents the number of dynamic load applications. k1, k2, k3, k4, k5, and b are all fitting coefficients, and the fitting coefficients are obtained by performing non-linear least squares curve fitting using the Levenberg-Marquardt algorithm.

4. The long-term settlement prediction method for the ballastless track subgrade of high-speed railway according to claim 1, characterized in that The equivalenting the number of cyclic loadings to a time measurement unit and the cumulative plastic strain to static creep to conduct numerical simulation of the long-term settlement of the target subgrade includes: Equivalenting the numerical simulation of the long-term settlement of the target subgrade to the calculation of soil strain, equivalenting the number of cyclic loadings to a time measurement unit and the cumulative plastic strain to static creep to calculate the soil strain, and the calculation of soil strain includes elastic strain calculation, plastic strain calculation, and creep calculation; Calculating the time-independent elastic strain using the critical state theory, and the stiffness constant expressed in modulus in the elastic strain calculation is: ； ； where K and G are the elastic bulk compression modulus and the shear modulus respectively, E is the elastic modulus, μ is the Poisson's ratio, e is the void ratio of the soil mass, is the slope of the swelling line in the e-lnp space, is the effective mean stress; The plastic strain is calculated by following the yield criterion of the Modified Cam-Clay model and the associated flow rule. On the premise that the plastic potential function is the same as the yield surface function, the calculation of the plastic strain satisfies the following relationship: ； In the formula, is the slope of the critical state line, is the deviator stress, and in the calculation formula here , J2 is the second invariant of the deviator stress tensor, is the pre-consolidation pressure of the soil mass, is the effective mean stress; The calculation for creep satisfies the following relationship: ； In the formula, is the empirical expression of the axial cyclic cumulative strain rate of the soil sample under the undrained triaxial condition established based on test or measured data, is the creep potential function, is the rate-dependent cyclic cumulative strain rate tensor, is the dynamic stress level, is the total strain rate, is the loading time of the dynamic load, is other internal variables, is the effective mean stress, is the partial derivative symbol.

5. The long-term settlement prediction method for the ballastless track subgrade of high-speed railway according to claim 1, characterized in that The iterative calculation method is used to jointly simulate the track-subgrade finite element model and the train-track multibody dynamics model to establish a train-track-subgrade coupled dynamics numerical simulation model, including: Derive the wheel-rail force data from the train-track multibody dynamics model, and apply the wheel-rail force data to the track surface of the track-subgrade finite element model to obtain the lateral deformation data and longitudinal deformation data of the track surface; Apply the lateral deformation data and longitudinal deformation data of the track surface to the track structure in the train-track multibody dynamics model to derive new wheel-rail force data, forming an iterative cycle; After reaching the preset cycle time, extract the mechanical response data, and use the mechanical response data to eliminate the initial instability in the train-track multibody dynamics model and the influence of the boundary conditions in the track-subgrade finite element model; Based on the train-track multibody dynamics model with eliminated initial instability and the track-subgrade finite element model with eliminated boundary condition influence, establish a train-track-subgrade coupled dynamics numerical simulation model.

6. The long-term settlement prediction method for the ballastless track subgrade of high-speed railway according to claim 5, characterized in that The wheel-rail force data includes: vertical force and lateral force. The lateral deformation data and longitudinal deformation data of the track surface are obtained by superimposing the high-speed railway random irregularity spectrum and the vehicle-induced track additional irregularity.

7. The method for predicting long-term settlement of ballastless track subgrade of high-speed railway according to claim 1, characterized in that The calculation of substituting the train speed, operation time, initial water content of the subgrade, and wetting times into the train-track-subgrade coupled dynamics numerical simulation model to calculate the vertical deformation of the subgrade top surface includes: Input parameters such as subgrade water content, cyclic wetting times, train speed, and prediction duration to obtain the joint simulation results of the train-track multibody dynamics model and the track-subgrade finite element model, and draw the time history curves of the vertical deformation of the subgrade top surface and the settlement rate based on the simulation results.

8. A long-term settlement prediction system for the ballastless track subgrade of high-speed railways, characterized in that, Including a fitter and a predictor; The fitter is used to fit the curve into a function including wetting times, water content amplitude, train speed, and prediction time according to the time history data of the vertical deformation of the subgrade top surface obtained by the method according to any one of claims 1-7; The predictor is used to input wetting times, water content amplitude, train speed, and prediction time, calculate and draw the time history curve of the vertical deformation of the subgrade top surface within the prediction time range, and compare it with the preset subgrade settlement threshold to give an over-limit warning message.

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