Roadbed state evolution method and system under intermittent load effect

Abstract

The invention discloses a roadbed state evolution method and system under an intermittent load effect. The method comprises the following steps: obtaining roadbed filler information corresponding to a roadbed, wherein the roadbed filler information comprises particle systems corresponding to multiple layers of different filler substances; determining stress and strain corresponding to the structure of the particle system under the intermittent load effect, and establishing a state evolution model of the roadbed based on the stress and the strain; historical strain parameters of the roadbed are obtained, and the characteristic strain of the particle system is determined based on the historical strain parameters; and correcting the state evolution model based on the characteristic strain so as to determine the state evolution variable of the roadbed under the intermittent load through the corrected state evolution model. According to the method, the roadbed state evolution variable under the intermittent load can be accurately determined, safe and smooth operation of road traffic is guaranteed, the service life of the roadbed is prolonged, and the road maintenance cost is reduced.

Description

Technical Field

[0001] The present application relates to the technical field of roadbed design, and in particular to a method and system for evolving roadbed states under intermittent loads. Background Art

[0002] In the field of road engineering, predicting subgrade settlement is crucial for ensuring long-term road stability and driving safety. Although numerous research results and corresponding state evolution models have been developed for subgrade settlement prediction, most existing state evolution models are based on continuous loading conditions. While these models can, to a certain extent, reflect the subgrade's settlement behavior under continuous loading, in actual engineering applications, the load borne by the subgrade is not always continuous.

[0003] Therefore, the existing roadbed settlement state evolution model based on continuous loading conditions has great limitations when predicting roadbed settlement under intermittent loads, and it is difficult to accurately reflect the actual settlement of the roadbed under intermittent loads. This urgently requires the development of a new state evolution model that can accurately consider the characteristics of intermittent loads and their impact on roadbed settlement. Summary of the Invention

[0004] In order to solve the above technical problems, the embodiments of the present application provide a method and system for the evolution of roadbed state under intermittent loads.

[0005] According to one aspect of an embodiment of the present application, a method for the evolution of roadbed state under intermittent loads is provided, comprising: obtaining roadbed filler information corresponding to the roadbed, the roadbed filler information including a particle system corresponding to multiple layers of different filler materials; determining the stress and strain corresponding to the structure of the particle system under intermittent loads, and establishing a state evolution model of the roadbed based on the stress and the strain; obtaining historical strain parameters of the roadbed, and determining the characteristic strain of the particle system based on the historical strain parameters; and correcting the state evolution model based on the characteristic strain to determine the state evolution variables of the roadbed under intermittent loads through the corrected state evolution model.

[0006] According to one aspect of an embodiment of the present application, the method also includes: under the action of intermittent loads, obtaining the phase change characteristics corresponding to the particle system when subjected to force, and determining the state evolution variables of the particle system based on the phase change characteristics; determining the steady-state conditions corresponding to the state evolution variables and the non-equilibrium potential function of the non-equilibrium state, and determining the dynamic equilibrium relationship corresponding to the particle system based on the steady-state conditions and the non-equilibrium potential function; constructing a state evolution model corresponding to the state evolution variables based on the dynamic equilibrium relationship, and the state evolution model includes an explicit expression of the state evolution variables.

[0007] According to one aspect of an embodiment of the present application, the method also includes: performing a force analysis on the particle system, and determining the phase change characteristics corresponding to the particle system when subjected to force based on the analysis results, the phase change characteristics including solid phase, liquid phase and critical state; determining the quantitative index of the non-equilibrium thermodynamics of the particle system based on the phase change characteristics, and using the quantitative index as the state evolution variable of the particle system.

[0008] According to one aspect of an embodiment of the present application, the steady-state conditions corresponding to the state evolution variables and the non-equilibrium potential function of the non-equilibrium state are determined, and the dynamic equilibrium relationship corresponding to the particle system is determined based on the steady-state conditions and the non-equilibrium potential function, including: establishing a state evolution equation of the state evolution variables in combination with the steady-state conditions and the non-equilibrium potential function; solving the state evolution equation to obtain a steady-state solution corresponding to the state evolution equation and a recovery condition corresponding to the steady-state solution; and determining the dynamic equilibrium relationship corresponding to the particle system based on the steady-state solution and the recovery condition corresponding to the steady-state solution.

[0009] According to one aspect of an embodiment of the present application, after constructing the state evolution model corresponding to the state evolution variable based on the dynamic equilibrium relationship, and the state evolution model includes an explicit expression of the state evolution variable, the method further includes: determining the real-time stress and real-time load change rate corresponding to the structure of the particle system under intermittent load, and introducing the real-time stress and the real-time load change rate into the explicit expression to obtain an updated explicit expression; and determining the state evolution model of the roadbed under intermittent load based on the updated explicit expression.

[0010] According to one aspect of an embodiment of the present application, the method further includes: under the action of intermittent load, using a sinusoidal wave load as the input form of the load in the loading stage; determining the real-time stress of the particle system in the intermittent stage and the real-time stress of the particle system in the loading stage based on the sinusoidal wave load and the explicit expression; and determining the real-time stress under the action of the intermittent load based on the real-time stress in the intermittent stage and the real-time stress in the loading stage.

[0011] According to one aspect of an embodiment of the present application, the method further includes: after the roadbed enters the intermittent stage, determining the first stage load based on the static load of the upper structure of the roadbed; connecting the first stage load with the second stage load to obtain a connection load, and the second stage load is the load corresponding to the loading stage; and determining the real-time load change rate corresponding to the structure of the particle system based on the connection load.

[0012] According to one aspect of an embodiment of the present application, the state evolution model is corrected based on the characteristic strain, including: obtaining historical strain parameters of the roadbed under intermittent load, the historical strain parameters including the strain state of the state evolution variable in the connection state between the loading state and the intermittent state; determining the characteristic strain of the roadbed based on the strain state, the characteristic strain including the relevant historical strain range of the state evolution variable in the connection state; introducing the expression of the state evolution variable based on the characteristic strain to obtain the corrected state evolution model.

[0013] According to one aspect of an embodiment of the present application, determining the characteristic strain of the roadbed based on the strain state includes: defining the state evolution variable in the connection state as a weighted average of the historical strain path; establishing an exponential decay weight function between the length of the historical strain path and the weighted average, so as to determine the characteristic strain of the roadbed based on the exponential decay weight function.

[0014] According to one aspect of an embodiment of the present application, a system for the evolution of roadbed state under intermittent loads is provided, the system comprising a processor, an input device, an output device and a memory, the processor, input device, output device and memory being interconnected, wherein the memory is used to store a computer program, the computer program comprising program instructions, and the processor is configured to call the program instructions to execute the above-mentioned method for the evolution of roadbed state under intermittent loads.

[0015] In the technical solution provided in the embodiments of the present application, by obtaining the roadbed filler information corresponding to the roadbed, which includes a multi-layer particle system of different filler materials, and determining the stress and strain corresponding to the particle system structure under intermittent loads, and based on this, establishing a state evolution model of the roadbed, the dynamic change process of the roadbed under specific load conditions can be quantified, which helps to clearly understand the state evolution law of the roadbed in different intermittent load stages, and further obtain the historical strain parameters of the roadbed and determine the characteristic strain of the particle system, fully considering the impact of the mechanical effects experienced by the roadbed in the past on its current performance, and can capture the potential change characteristics of the roadbed caused by long-term use or complex environmental factors. Finally, based on the characteristic strain, the state evolution model is corrected, which greatly improves the accuracy and reliability of the model, so that the corrected state evolution model can more realistically reflect the actual state of the roadbed under intermittent loads, and can accurately determine the roadbed state evolution variables, ensure the safety and smooth operation of road traffic, extend the service life of the roadbed, and reduce road maintenance costs.

[0016] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification, are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and it is clear that a person of ordinary skill in the art can derive other drawings based on these drawings without inventive effort.

[0018] Figure 1 It is a flow chart of a method for evolving roadbed state under intermittent loads, shown as an exemplary embodiment of the present application.

[0019] Figure 2 yes Figure 1 Step S120 in the illustrated embodiment is a flow chart in an exemplary embodiment.

[0020] Figure 3 Figure 2 Step S210 in the illustrated embodiment is a flow chart in an exemplary embodiment.

[0021] Figure 4 yes Figure 2 Step S220 in the illustrated embodiment is a flow chart in an exemplary embodiment.

[0022] Figure 5 yes Figure 1 Step S120 in the illustrated embodiment is a flow chart in another exemplary embodiment.

[0023] Figure 6 yes Figure 5 Step S510 in the illustrated embodiment is a flow chart in an exemplary embodiment.

[0024] Figure 7 FIG. 4 is another exemplary embodiment of the present application showing the state evolution diagram of the roadbed from dynamic load to static load.

[0025] Figure 8 Figure 5 Step S510 in the illustrated embodiment is a flow chart in another exemplary embodiment.

[0026] Figure 9 FIG. 4 is another exemplary embodiment of the present application showing the state evolution diagram of the roadbed from static load to dynamic load.

[0027] Figure 10 is a block diagram of a roadbed state evolution system under intermittent loads, shown as an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0028] Exemplary embodiments will be described in detail herein, examples of which are illustrated in the accompanying drawings. When the following description refers to the drawings, identical numerals in different figures represent identical or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of systems and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0029] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0030] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, while others may be combined or partially combined. Therefore, the actual execution order may vary depending on the actual situation.

[0031] In this application, "plurality" refers to two or more. "And / or" describes the relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can mean: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally indicates that the related objects are in an "or" relationship.

[0032] First, it's important to note that the most notable characteristic of intermittent high-speed rail loading is its intermittent nature. During the intervals between trains, the roadbed bears virtually no direct load from the trains. Therefore, predicting the cumulative strain in the roadbed under intermittent high-speed rail loading typically requires more complex dynamic analysis and simulations. This requires clarifying the distinction between intermittent and continuous loading to accurately capture the dynamic characteristics of the load and its impact on the roadbed.

[0033] Despite numerous research results on predicting subgrade settlement and the development of corresponding state evolution models, most existing subgrade settlement state evolution models are based on continuous loading conditions. While models based on continuous loading conditions can, to a certain extent, reflect the settlement behavior of subgrades under continuous load, in actual engineering applications, the loads borne by subgrades are not always continuous. For railway subgrades in particular, the loads generated by train operation are typically intermittent loads—that is, the load is not applied continuously but occurs during the passage of trains, followed by intervals between load applications. Numerous practical studies have demonstrated that the cumulative subgrade settlement under intermittent loading differs significantly from that under continuous loading. The cumulative deformation process of subgrades caused by intermittent loading is more complex, incorporating the partial recovery effect of the subgrade fill material during the intermittent loading intervals. Furthermore, the intermittent loads generated by trains do not simply damage the subgrade but actually have a positive effect on reducing the accumulated plastic strain in the subgrade fill material. Therefore, the existing subgrade settlement state evolution model established based on continuous loading conditions has great limitations when predicting subgrade settlement under intermittent loading, and it is difficult to accurately reflect the actual settlement of the subgrade under intermittent loading.

[0034] In order to solve the above problems, the present application proposes a method and system for the evolution of roadbed state under intermittent loads, an electronic device, a computer-readable storage medium and a computer program product. These embodiments will be described in detail below.

[0035] See also Figure 1 , Figure 1 The method for evolving the subgrade state under intermittent loads shown in an exemplary embodiment of the present application includes at least steps S110 to S140, which are described in detail as follows.

[0036] Step S110 , obtaining roadbed filler information corresponding to the roadbed, where the roadbed filler information includes a particle system corresponding to multiple layers of different filler materials.

[0037] For example, in the complex scenarios of road construction and maintenance, accurately understanding the roadbed conditions is a key prerequisite for ensuring road safety and durability. When conducting research or maintenance work on the roadbed, a comprehensive and detailed on-site survey and sample collection must be carried out first. Professional technicians will drill and sample at different depths based on the layered structure of the roadbed to ensure that the original samples of each layer of roadbed filler can be obtained. These samples cover multiple layers of different filler materials, because during the construction process of the roadbed, a layered filling method is often used according to geological conditions and design requirements. Different layers may use various fillers such as gravel, clay, crushed stone, etc. After collecting the samples, a particle system analysis is performed on each layer of filler samples. Through screening tests, the distribution ratio of particles of different particle sizes can be determined, and the composition of coarse and fine particles in the filler can be understood. With the help of microscopic observation and image analysis technology, the shape, surface texture and other microscopic characteristics of the particles are further studied. At the same time, the physical properties of the filler, such as density and water content, and mechanical properties, such as compression modulus and shear strength, are also measured. By combining these analysis results, the roadbed filler information corresponding to the roadbed can be fully obtained, and the particle system characteristics corresponding to each layer of different filler materials can be clarified, including the size, shape, gradation of the particles and the physical and mechanical properties of the filler, etc., providing a solid data foundation for the subsequent performance analysis and evaluation of the roadbed under various loads.

[0038] Step S120 , determining the stress and strain corresponding to the structure of the particle system under the intermittent load, and establishing a state evolution model of the roadbed based on the stress and strain.

[0039] For example, intermittent loading scenarios were simulated in the laboratory. Using advanced geotechnical testing equipment, such as a dynamic triaxial tester, intermittent loading was applied to roadbed specimens containing different filler particle systems, precisely controlling parameters such as load magnitude, frequency, and intermittent duration, in accordance with the intermittent loading characteristics generated by train and vehicle traffic in real-world projects. During the test, high-precision sensors and a data acquisition system were used to accurately monitor and record stress and strain data of the particle system structure at different times in real time. Stress data reflects the internal forces experienced by the particle system under intermittent loading, while strain data reflects the deformation of the particle system. The two are interrelated and together describe the mechanical response of the particle system under intermittent loading. Subsequently, the extensive amount of collected stress and strain data was subjected to in-depth analysis. Mathematical modeling and statistical analysis methods were used to uncover the underlying patterns in the data and explore the inherent relationship between stress and strain. Given the unique characteristics of intermittent loading, the analysis fully considered the impact of intermittent loading on the stress and strain of the particle system, such as stress relaxation and strain recovery during periods of loading pauses. Based on these analysis results, a model was constructed that accurately describes the evolution of the subgrade's state under intermittent loading. This model uses stress and strain as key variables, comprehensively considering the characteristics of the filler particle system, the parameters of the intermittent loading, and time factors. It can dynamically simulate the evolution of the subgrade's internal stress and strain over time, starting from its initial state and under the repeated action of intermittent loading, and thus predict the evolutionary trend of the subgrade's state.

[0040] Step S130 : acquiring historical strain parameters of the roadbed, and determining characteristic strains of the particle system based on the historical strain parameters.

[0041] For example, in the long-term operation and maintenance of road projects, accurately understanding the deformation of the roadbed during past use plays a key role in assessing its current condition and predicting future development trends. To obtain historical roadbed strain parameters, it is first necessary to collect roadbed inspection and monitoring data conducted at different time periods since the road was completed and opened to traffic. This data comes from a variety of sources. For one thing, regular professional roadbed inspection reports are an important basis. Inspectors use professional measuring instruments such as high-precision levels and total stations to conduct on-site measurements of roadbed deformation indicators such as settlement and horizontal displacement. After compilation and analysis, these measurement data can directly or indirectly reflect the roadbed's strain status. Furthermore, if a road is equipped with a long-term monitoring system, such as strain sensors and settlement plates deployed within the roadbed, they will continuously record roadbed strain data under different operating conditions. This real-time data is stored in a dedicated database, providing a rich and continuous source of information for obtaining historical strain parameters. After collecting sufficient and comprehensive historical strain data, the data was systematically collated and preprocessed to eliminate abnormal data caused by instrument failures, human errors, and other factors to ensure data accuracy and reliability. Statistical analysis was then used to analyze the processed data. Strain versus time curves were plotted to observe the growth trends and fluctuations of strain at different stages. Furthermore, the causes and patterns of the historical strain data were analyzed in depth, taking into account actual road operating conditions, such as changes in traffic volume, heavy vehicle traffic, and environmental influences (such as rainfall and earthquakes). Based on this detailed analysis of historical strain parameters, the characteristic strain of the granular system was determined. Considering that the roadbed is composed of multiple layers of different filler materials, the mechanical properties and deformation characteristics of different fillers vary. Therefore, based on the strain at different depths and locations reflected in the historical strain data, combined with the filler type and distribution, characteristic parameters were selected to represent the typical deformation behavior of the granular system under actual operating conditions, such as intermittent loading.

[0042] Step S140 , correcting the state evolution model based on the characteristic strain, so as to determine the state evolution variables of the roadbed under the intermittent load through the corrected state evolution model.

[0043] For example, while the initially established subgrade state evolution model was based on certain theoretical assumptions and preliminary data, it inevitably has limitations when faced with the complex and variable intermittent loading conditions found in actual projects. This is because actual subgrades are subject to the intertwined influence of multiple factors, such as traffic flow fluctuations, vehicle load variations, and changes in ambient temperature and humidity. These factors cause the magnitude, frequency, and duration of intermittent loads to continuously vary, resulting in the stress-strain relationship in the subgrade not fully conforming to the model's initial assumptions. Therefore, the state evolution model is modified using the determined characteristic strain as a "yardstick." Specifically, the deformation patterns of the subgrade particle system, as reflected by the characteristic strain, are incorporated into the adjustment of key model parameters. For example, if the characteristic strain indicates that the subgrade undergoes plastic deformation faster than initially predicted under a specific intermittent loading frequency, the model's parameters related to plastic deformation are adjusted accordingly to more accurately reflect this actual deformation trend. Furthermore, the model is modified layer by layer to account for differences in characteristic strain at different subgrade depths, ensuring that the stress-strain relationship at each layer closely matches the actual situation. After such fine-tuning, the state evolution model seems to be endowed with a more acute "perception", and can more realistically simulate the dynamic changes of the roadbed under intermittent loads.

[0044] In some embodiments of the present application, by obtaining roadbed filler information comprising a multi-layer particle system of different filler materials, determining the stress and strain of the particle system under intermittent loads to establish a state evolution model, and then combining historical strain parameters to determine the characteristic strain to correct the model, the state evolution variables of the roadbed under intermittent loads can be accurately determined, providing a reliable basis for accurately evaluating roadbed performance and stability.

[0045] Further, based on the above embodiment, please refer to Figure 2 In one of the exemplary embodiments provided in this application, the specific implementation process of the above-mentioned roadbed state evolution method under intermittent loads may further include steps S210 to S230, which are described in detail as follows:

[0046] Step S210 , under the action of intermittent loads, obtaining the phase change characteristics of the particle system when subjected to force, and determining the state evolution variables of the particle system based on the phase change characteristics.

[0047] Step S220 , determining the steady-state conditions corresponding to the state evolution variables and the non-equilibrium potential function of the non-equilibrium state, and determining the dynamic equilibrium relationship corresponding to the particle system based on the steady-state conditions and the non-equilibrium potential function.

[0048] Step S230: constructing a state evolution model corresponding to the state evolution variable based on the dynamic equilibrium relationship, wherein the state evolution model includes an explicit expression of the state evolution variable.

[0049] For example, in practical scenarios involving the study of roadbed and soil particle systems, such as road engineering and geotechnical mechanics, accurately understanding the behavior of particle systems under load is crucial for the safety and stability of engineering structures. To determine the phase transition characteristics of a particle system under load, a specialized laboratory test platform is required to simulate the complex load conditions experienced by a roadbed in practice. For example, dynamic triaxial testing equipment can be used to apply intermittent and cyclic loading. During the test, high-precision sensors and data acquisition systems are used to monitor changes in parameters such as stress, strain, and pore water pressure in the particle system in real time. By analyzing the curves of these parameters as they change during the load process, the critical points where the particle system transitions from one stable state to another, such as from a loose to a dense state or from elastic to plastic deformation, can be identified. This allows the phase transition characteristics to be clarified, including the conditions under which the phase transition occurs and the energy changes during the phase transition. Based on these acquired phase transition characteristics, the state evolution variables of the particle system are further determined. These variables, such as the particle arrangement structure, porosity, and effective stress, can fully describe the state changes of the particle system under load. The determination of state evolution variables provides a key indicator for a deeper understanding of the dynamic behavior of particle systems. Subsequently, the corresponding steady-state conditions are analyzed for the determined state evolution variables. Steady-state conditions refer to the physical constraints satisfied when a particle system reaches a stable state under a specific stress environment. For example, under a constant load, the strain of the particle system no longer changes with time. At this time, the corresponding combination of stress, porosity, and other parameters is the steady-state condition. At the same time, for non-equilibrium states, the concept of non-equilibrium potential function is introduced. The non-equilibrium potential function is a measure of the degree to which a particle system deviates from the steady state. By establishing an appropriate non-equilibrium potential function, the evolution trend of the particle system in a non-equilibrium state can be quantified.

[0050] Finally, based on steady-state conditions and nonequilibrium potential functions, and drawing on relevant theories such as thermodynamics and statistical mechanics, the corresponding dynamic equilibrium relationship for the particle system is derived. This dynamic equilibrium relationship reflects the balance and transformation between various forces acting on the particle system during its stress process. It comprehensively considers factors such as inter-particle interactions, external forces, and energy dissipation within the system, and is the core equation describing the dynamic behavior of the particle system. Finally, based on the determined dynamic equilibrium relationship, a state evolution model corresponding to the state evolution variables is constructed through mathematical derivation and simplification, and explicit expressions for the state evolution variables are obtained.

[0051] In some embodiments provided in the present application, the state evolution variables are determined by obtaining the phase change characteristics of the particle system when it is subjected to force, and then the dynamic equilibrium relationship is clarified based on its steady-state conditions and non-equilibrium potential function, and then a state evolution model containing explicit expressions of the state evolution variables is constructed, which can accurately predict and describe the state change law of the particle system during the force process.

[0052] Further, based on the above embodiment, please refer to Figure 3 In one exemplary embodiment provided in this application, the specific implementation process of obtaining the phase change characteristics of the particle system when subjected to force and determining the state evolution variables of the particle system based on the phase change characteristics may further include steps S310 and S320, which are described in detail as follows:

[0053] Step S310 , performing a force analysis on the particle system, and determining the phase change characteristics of the particle system when subjected to force based on the analysis results, where the phase change characteristics include a solid phase, a liquid phase, and a critical state.

[0054] Step S320 : determining a quantitative index of non-equilibrium thermodynamics of the particle system based on the phase change characteristics, and using the quantitative index as a state evolution variable of the particle system.

[0055] For example, a detailed stress analysis can be conducted on specific particle systems, such as soil-rock mixed fillers in roadbeds or loose rock and soil on slopes. Advanced geotechnical testing equipment, such as dynamic triaxial apparatus and direct shear apparatus, can be used in a laboratory environment to simulate the complex stress conditions that particle systems experience in actual engineering projects, such as intermittent cyclic stresses generated by road traffic loads and random dynamic stresses under earthquakes. During the test, high-precision sensors are used to monitor key parameters such as the stress-strain relationship and pore water pressure changes of the particle system in real time. At the same time, numerical simulation methods, such as the discrete element method (DEM), are used to further analyze the microscopic stress conditions of the particle system, observe the contact force distribution between particles, the motion trajectory of particles, etc., and through a combination of experiments and simulations, comprehensive and in-depth information on the mechanical response of the particle system under stress can be obtained.

[0056] Based on the above force analysis results, the phase transition characteristics of the particle system under stress are determined. When the stress in the particle system is low, the relative positions of the particles are relatively fixed, and stress is transmitted primarily through interparticle contact forces. At this point, the particle system exhibits solid-like properties, with high stiffness and strength, capable of withstanding a certain external force without significant deformation. As the stress gradually increases, once a critical value is reached, the contact between the particles begins to loosen, some particles begin to slide relative to each other, and the fluidity of the particle system gradually increases, entering a critical state. In this state, the particle system exhibits both certain solid-state characteristics and some liquid-like properties, and its mechanical properties become extremely complex. As the stress increases further, exceeding the stress level corresponding to the critical state, the relative movement of the particles becomes free, and the particle system exhibits distinct liquid-like properties, with significantly enhanced fluidity and difficulty withstanding large shear stresses. After determining the phase transition characteristics of the particle system, quantitative indices of the non-equilibrium thermodynamics of the particle system can be determined based on these characteristics. Taking these quantitative indicators as state evolution variables of the particle system, they can comprehensively and dynamically describe the evolution process of the particle system from solid phase to critical state and then to liquid phase during the stress process, providing an important quantitative basis for in-depth understanding of the mechanical behavior and thermodynamic properties of the particle system.

[0057] In some embodiments of the present application, by performing force analysis on the particle system, its phase change characteristics including solid phase, liquid phase and critical state are clarified, and based on this, quantitative indicators of non-equilibrium thermodynamics are determined as state evolution variables, which can accurately quantify the dynamic changes of the particle system during the force process, providing a key basis for in-depth understanding of its mechanical behavior and state evolution laws.

[0058] Further, based on the above embodiment, please refer to Figure 4 In one of the exemplary embodiments provided in this application, the specific implementation process of determining the steady-state conditions corresponding to the state evolution variables and the non-equilibrium potential function of the non-equilibrium state, and determining the dynamic equilibrium relationship corresponding to the particle system based on the steady-state conditions and the non-equilibrium potential function may further include steps S410 to S430, which are described in detail as follows:

[0059] Step S410 , establishing a state evolution equation of the state evolution variable by combining the steady-state condition and the non-equilibrium potential function.

[0060] Step S420 , solving the state evolution equation to obtain a steady-state solution corresponding to the state evolution equation and a recovery condition corresponding to the steady-state solution.

[0061] Step S430 : determining a dynamic equilibrium relationship corresponding to the particle system based on the steady-state solution and the recovery condition corresponding to the steady-state solution.

[0062] For example, based on the steady-state conditions and non-equilibrium potential functions in the above-mentioned embodiments, a state evolution equation can be established for the state evolution variables. These state evolution variables are key parameters that can comprehensively describe the state of the particle system, such as the particle arrangement structure, effective stress, and pore water pressure. Then, by applying relevant theories such as thermodynamics and statistical mechanics, combined with the system equilibrium characteristics reflected by the steady-state conditions and the dynamic process of the system deviating from equilibrium described by the non-equilibrium potential function, a differential equation can be constructed that accurately reflects the time-varying changes in the state evolution variables. However, the state evolution equation is typically complex, making it difficult to directly obtain an analytical solution. Therefore, numerical methods such as the finite difference method and the finite element method can be used to solve the state evolution equation. During the solution process, appropriate initial and boundary conditions are set to simulate the initial state and external constraints of the particle system in actual engineering. Further, computer simulation calculations are performed to obtain the steady-state solution corresponding to the state evolution equation. The steady-state solution represents the stable state ultimately reached by the particle system after a long period of evolution and reflects the equilibrium characteristics of the system under specific conditions. At the same time, the solution process is analyzed to determine the recovery conditions corresponding to the steady-state solution. That is, when the particle system is disturbed and deviates from the steady state, under what conditions can it return to the steady state. The recovery conditions may involve factors such as the magnitude of the disturbance, the duration of the disturbance, and the inherent characteristics of the system. Finally, based on the obtained steady-state solution and the corresponding recovery conditions, the corresponding dynamic equilibrium relationship of the particle system is further determined.

[0063] In some embodiments of the present application, by combining steady-state conditions and non-equilibrium potential functions to construct and solve the state evolution equation of the state evolution variable, its steady-state solution and recovery condition are obtained, and then the dynamic equilibrium relationship of the particle system is accurately determined, which provides strong theoretical support for in-depth exploration of the dynamic behavior and stability mechanism of the particle system under complex forces.

[0064] Further, based on the above embodiment, please refer to Figure 5 In one of the exemplary embodiments provided in this application, after constructing the state evolution model corresponding to the state evolution variable based on the dynamic equilibrium relationship, and the state evolution model includes the explicit expression of the state evolution variable, the specific implementation process of the above-mentioned roadbed state evolution method under intermittent loads may further include steps S510 and S520, which are described in detail as follows:

[0065] Step S510 , determining the real-time stress and real-time load change rate corresponding to the structure of the particle system under the intermittent load, and introducing the real-time stress and real-time load change rate into the explicit expression to obtain an updated explicit expression.

[0066] Step S520: determining a state evolution model of the roadbed under the action of intermittent loads based on the updated explicit expression.

[0067] For example, the most notable feature of high-speed rail intermittent loads is their discontinuity. During the intervals between trains, the roadbed bears almost no direct load from the trains. Therefore, the prediction of the cumulative strain of the roadbed under high-speed rail intermittent loads usually requires more complex dynamic analysis and model simulation to clearly distinguish between intermittent loads and continuous loads in order to accurately capture the dynamic characteristics of the load and its impact on the roadbed. Based on the state evolution model, a state evolution model of the cumulative settlement of the roadbed under long-term cyclic loads was successfully constructed. The establishment of this state evolution model fully considers the input of cyclic dynamic loads, that is, the size of the real-time load and the rate of load change.

[0068] Therefore, if the intermittent load input can be accurately simulated in the model, the cumulative strain of the roadbed under the intermittent load can be predicted. In some feasible embodiments, the updated explicit expression of the state evolution model can be expressed as:

[0069]

[0070] Where, and They are Stress and strain at all times; for The stress change rate at the moment; is the elastic modulus of the roadbed; for i State variables of the roadbed at time Δ t is the calculation step length; is the characteristic coefficient, where , is an undetermined coefficient, which is affected by the soil state. is the reference strain rate introduced for dimensional consistency, is the characteristic strain. To accurately simulate intermittent load input, the real-time stress and real-time load change rate corresponding to the structure of the particle system under intermittent load can be introduced into the above explicit expression to obtain an updated explicit expression. This updated explicit expression can then be used to determine the state evolution model of the roadbed under intermittent load.

[0071] In some embodiments of the present application, an updated version is obtained by introducing the real-time stress and real-time load change rate of the particle system structure under intermittent load into an explicit expression, and then a state evolution model is accurately constructed that can reflect the dynamic change law of the roadbed when intermittent load is actually applied, providing a reliable basis for roadbed performance evaluation and prediction.

[0072] Further, based on the above embodiment, please refer to Figure 6In one of the exemplary embodiments provided in this application, the specific implementation process of the above-mentioned roadbed state evolution method under intermittent loads may further include steps S610 to S630, which are described in detail as follows:

[0073] Step S610: Under the action of intermittent load, a sinusoidal wave load is used as the input form of the load in the loading stage.

[0074] Step S620 : determining the real-time stress of the particle system in the intermittent phase and the real-time stress of the particle system in the loading phase based on the sinusoidal wave load and the explicit expression.

[0075] Step S630 : determining the real-time stress under the intermittent load based on the real-time stress in the intermittent stage and the real-time stress in the loading stage.

[0076] For example, to achieve accurate simulation of intermittent load input, the intermittent load input is divided into a loading stage and an intermittent stage in the state evolution model. The load input form in the loading stage (taking a sine wave load as an example) is:

[0077]

[0078] Where, is the load in the loading stage, is the load change rate during the loading phase; is the load cycle, is the time step of the calculation; is the number of calculation steps in the loading phase, where , is the duration of the loading phase, and when hour, .

[0079] After entering the intermittent stage, the roadbed no longer bears the load generated by the train, but only the static load of the roadbed superstructure. Therefore, the load in this stage is a certain value. In order to connect with the load in the loading stage, the load in the intermittent stage is set as:

[0080]

[0081] in, The load during the intermittent phase, is the load at the initial moment of the intermittent stage, is the load at the last moment of the loading phase, is the static stress generated by the subgrade superstructure, is the number of calculation steps in the intermittent phase, where , is the duration of the intermittent phase. Further, the load change rate during the intermittent phase can be expressed as follows:

[0082]

[0083] Since the load on the roadbed in the intermittent stage is significantly less than that in the loading stage, and experimental analysis shows that the roadbed state variable will be a minimum value in the intermittent stage, in order to simplify the complexity of the model, it can be assumed that at the initial moment of entering the intermittent stage, the roadbed state variable , and the subsequent values ​​can be calculated using explicit expressions, and the cumulative strain of the subgrade at the moment when the subgrade enters the intermittent stage is equal to the cumulative strain of the subgrade at the last moment of the loading stage, that is, , whose subsequent values ​​can also be calculated using explicit expressions.

[0084] In addition, in some feasible embodiments, Matlab is used to write calculation codes according to the above ideas, and the load and its change rate, strain, and state variables obtained after calculation are as follows: Figure 7 As shown. Figure 7 In (a), we can see that the state evolution model accurately reproduces the characteristics of intermittent load, that is, the load changes from dynamic load in the loading stage to static load in the intermittent stage. Figure 7 The cumulative strain curve of the roadbed calculated by this model shown in (b) shows a clear rebound effect of strain in the intermittent stage, which is consistent with the roadbed settlement data observed under intermittent loading in the model test. Figure 7 The results shown in (c) of Figure 3 indicate that the subgrade state variables remain extremely low during the intermittent phase, which is consistent with the assumptions made when the model was established and reflects the flow characteristics of the actual subgrade system. Based on the above analysis, the state evolution model demonstrates good accuracy in simulating the subgrade response during the transition from the loading phase to the intermittent phase.

[0085] In some embodiments of the present application, in the intermittent load scenario, a sinusoidal wave load is used as the input in the loading stage, and the real-time stress of the particle system in the intermittent and loading stages is clarified respectively in combination with explicit expressions, thereby accurately determining the real-time stress under the entire intermittent load, providing key data support for in-depth analysis of the mechanical response of the particle system and the evolution of the roadbed state.

[0086] Further, based on the above embodiment, please refer to Figure 8 In one of the exemplary embodiments provided in this application, the specific implementation process of the above-mentioned roadbed state evolution method under intermittent loads may further include steps S710 to S730, which are described in detail as follows:

[0087] Step S710: After the roadbed enters the intermittent stage, the first stage load is determined based on the static load of the upper structure of the roadbed.

[0088] In step S720, the first stage load is connected with the second stage load to obtain a connected load, where the second stage load is the load corresponding to the loading stage.

[0089] Step S730 : determining a real-time load change rate corresponding to the structure of the particle system based on the connection load.

[0090] For example, following the above embodiment, the above embodiment simulates the situation where the intermittent load enters the intermittent stage from the loading stage, and the feasibility of the model is also illustrated by the calculation results of a simple example. In this embodiment, the situation where the intermittent load enters the loading stage from the intermittent stage will be further described. Specifically, after re-entering the loading stage, the roadbed will again bear the load generated by the train. Also taking the sine wave load as an example, in order to connect with the load in the intermittent stage, the load when re-entering the loading stage is:

[0091]

[0092] Where, is the load in the reloading stage, is the load at the initial moment of this loading stage, is the load at the last moment of the previous intermittent period; The static stress generated by the subgrade superstructure; is the dynamic stress amplitude, is the number of calculation steps in the intermittent phase, , is the duration of the intermittent phase, and the load change rate in the reloading phase can be further obtained:

[0093]

[0094] Similarly, the accumulated strain of the roadbed at the initial moment of the re-entry loading phase is equal to the accumulated strain of the roadbed at the last moment of the previous intermittent phase: , and its subsequent values ​​are still calculated using the above-mentioned display expression. The difference from the above embodiment is that the roadbed state variable at the initial moment of re-entering the loading phase is equal to the roadbed state variable at the last moment of the previous loading phase: , its subsequent values ​​can still be calculated using the above explicit expression.

[0095] Optionally, in some feasible embodiments, the calculation code can be written using Matlab according to the ideas of the above embodiments, and the load and its change rate, strain, and state variables obtained after calculation are as follows: Figure 9 As shown, from Figure 9 (a) shows that the load input of the state evolution model accurately reproduces the situation in which the intermittent load changes from the static load in the intermittent stage to the dynamic load in the loading stage; Figure 9The roadbed cumulative strain curve presented in (b) shows that when entering the loading stage again, the cumulative strain returns to the state of the previous loading stage, which is consistent with the roadbed settlement data observed in the model test; Figure 9 The results shown in (c) show that after re-entering the loading phase, the subgrade state variables return to the state of change under dynamic load. Based on the above analysis, the state evolution model provided by the above embodiment can effectively simulate the subgrade response under intermittent load.

[0096] In some embodiments of the present application, when the roadbed enters the intermittent stage, the first-stage load is first determined based on the static load of the superstructure, and then connected with the second-stage load of the loading stage to obtain the connection load, and then based on the connection load, the real-time load change rate of the particle system structure is accurately determined, which provides key parameters for accurately analyzing the mechanical properties of the particle system during the intermittent and loading conversion process.

[0097] Furthermore, based on the above embodiment, in one of the exemplary embodiments provided in this application, the specific implementation process of the above characteristic strain-based state evolution model correction may further include steps S810 to S830, which are described in detail as follows:

[0098] Step S810 , obtaining historical strain parameters of the roadbed under the action of intermittent loads, wherein the historical strain parameters include the strain state of the state evolution variable in the transition state between the loading state and the intermittent state.

[0099] Step S820 : determining the characteristic strain of the roadbed based on the strain state, where the characteristic strain includes the relevant historical strain range of the state evolution variable in the connection state.

[0100] Step S830: introducing an expression of a state evolution variable based on the characteristic strain to obtain a revised state evolution model.

[0101] For example, in actual engineering application scenarios for roadbed performance evaluation and prediction, when the roadbed is in a specific working condition of intermittent loading, high-precision strain monitoring equipment can be used to continuously collect strain data of the roadbed at different times to obtain its historical strain parameters. Among them, the focus is on the moment of connection between the loading state and the intermittent state, and the strain state corresponding to the state evolution variable in the connection state is accurately recorded. This strain state can accurately reflect the mechanical response characteristics of the roadbed during the transition between these two states. Subsequently, based on the obtained strain state data, professional data analysis algorithms and engineering experience are used to deeply analyze and determine the characteristic strain of the roadbed. Among them, the characteristic strain covers the historical strain range related to the state evolution variable in the connection state. This range can effectively summarize the strain change law of the roadbed under different intermittent loads, and provide a key basis for subsequent model correction. Finally, based on the determined characteristic strain, combined with the mechanical properties of the roadbed material and the actual stress conditions, the expression of the state evolution variable was introduced through a combination of theoretical deduction and numerical simulation. This expression was integrated into the original state evolution model to obtain a revised state evolution model. This model can more accurately and comprehensively reflect the actual mechanical behavior and state changes of the roadbed under intermittent loads, providing more reliable technical support for roadbed maintenance, reinforcement and service life prediction.

[0102] In some embodiments of the present application, under the action of intermittent loads, the characteristic strain is determined by obtaining historical strain parameters such as the strain state of the state evolution variables of the roadbed in the connection state when the loading and intermittent states are connected, and then the state evolution variable expression is introduced based on this to obtain a revised state evolution model, which can more accurately simulate and predict the mechanical behavior and state evolution of the roadbed under complex intermittent loads.

[0103] Furthermore, based on the above embodiment, in one of the exemplary embodiments provided in this application, the specific implementation process of determining the characteristic strain of the roadbed based on the strain state may further include step S910 and step S920, which are described in detail as follows:

[0104] Step S910: defining the state evolution variable in the connected state as the weighted average of the historical strain paths.

[0105] Step S920 : establishing an exponential decay weight function between the length of the historical strain path and the weighted average value, so as to determine the characteristic strain of the roadbed based on the exponential decay weight function.

[0106] For example, in actual engineering scenarios where the long-term performance and stability of the roadbed are evaluated under complex intermittent load environments, in order to accurately characterize the changes in the mechanical state of the roadbed, the state evolution variables under the connection state can be scientifically defined and set as the weighted average of the historical strain path. This setting fully considers the comprehensive impact of the strain history experienced by the roadbed at different times on its current state, so that the state evolution variables can more comprehensively and accurately reflect the mechanical memory characteristics of the roadbed.

[0107] Next, considering that strain information at different stages of the historical strain path has varying degrees of influence on the current state, and that the influence of earlier strain information on the current state gradually weakens over time, an exponentially decaying weight function is established between the length of the historical strain path and the state evolution variables in the connected state. By introducing an exponential decay factor, this function rationally allocates the weights of historical strains at different times when calculating the state evolution variables in the connected state. This ensures that historical strains closer to the current moment have greater weights, while the weights of older historical strains gradually decrease, thus better conforming to the actual laws of subgrade mechanical state evolution.

[0108] Finally, based on the established exponential decay weight function, the strains at each point on the historical strain path are weighted and calculated to determine the characteristic strain corresponding to the state evolution variable under the connection state. This characteristic strain can highlight the key mechanical characteristics of the roadbed under the influence of the state evolution variable under the connection state, providing important data support and theoretical basis for the subsequent in-depth analysis of the mechanical behavior of the roadbed, the prediction of its performance changes, and the formulation of scientific and reasonable maintenance strategies.

[0109] In some embodiments of the present application, by defining the state evolution variable in the connected state as the weighted average of the historical strain path, and establishing an exponential decay weight function of the historical strain path length and the state evolution variable in the connected state to determine the characteristic strain, the influence of the historical strain on the current state can be considered more scientifically and reasonably, thereby providing a reliable basis for accurately describing the state evolution of the roadbed particle system under intermittent loads.

[0110] See also Figure 10In another exemplary embodiment of the present application, a system for the evolution of roadbed states under intermittent loads is provided. In the system, an input device, a processor, an output device, and a memory are interconnected. The memory is used to store a computer program, which includes program instructions. The processor is configured to call the program instructions and execute the specific steps of the embodiments of the method for the evolution of roadbed states under intermittent loads provided by the present invention. The system for the evolution of roadbed states under intermittent loads of the present invention is structurally complete, objectively stable, and capable of efficiently executing the method for the evolution of roadbed states under intermittent loads of the present invention, thereby enhancing the overall applicability and practical application capabilities of the present invention.

[0111] It should be noted that the subgrade state evolution system under intermittent loads provided in the above-mentioned embodiment and the subgrade state evolution method under intermittent loads provided in the above-mentioned embodiment are based on the same concept. The specific manner in which each module and unit performs operations has been described in detail in the method embodiment and will not be repeated here. In actual applications, the subgrade state evolution system under intermittent loads provided in the above-mentioned embodiment can allocate the above-mentioned functions to different functional modules as needed, that is, divide the internal structure of the system into different functional modules to complete all or part of the functions described above, and this is not limited here.

[0112] An embodiment of the present application also provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by one or more processors, the electronic device implements the method for evolution of subgrade state under intermittent loads provided in the above-mentioned embodiments.

[0113] It should be noted that the computer-readable medium described in the embodiments of this application may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may, for example, be an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying a computer-readable computer program. This propagated data signal may take a variety of forms, including, but not limited to, an electromagnetic signal, an optical signal, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. A computer program embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, or any suitable combination thereof.

[0114] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. Among them, each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0115] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. In some cases, the names of these units do not constitute limitations on the units themselves.

[0116] Another aspect of the present application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned method for the evolution of roadbed conditions under intermittent loading. The computer-readable storage medium may be included in the electronic device described in the above embodiments, or may exist independently and not be incorporated into the electronic device.

[0117] Another aspect of the present application provides a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method for evolving a subgrade state under intermittent loading provided in each of the above-described embodiments.

[0118] The above content is only a preferred exemplary embodiment of the present application and is not intended to limit the implementation scheme of the present application. Ordinary technicians in this field can easily make corresponding changes or modifications based on the main ideas and spirit of the present application. Therefore, the scope of protection of the present application shall be based on the scope of protection required by the claims.

Claims

1. A method for the evolution of roadbed state under intermittent load, characterized in that: include: Acquire roadbed filler information corresponding to the roadbed, wherein the roadbed filler information includes particle systems corresponding to multiple layers of different filler materials; determining stress and strain corresponding to the structure of the particle system under intermittent load, and establishing a state evolution model of the roadbed based on the stress and strain; Acquiring historical strain parameters of the roadbed, and determining characteristic strain of the particle system based on the historical strain parameters; Modifying the state evolution model based on the characteristic strain to determine the state evolution variables of the roadbed under intermittent load through the modified state evolution model; The method further comprises: Under the action of intermittent loads, obtaining phase change characteristics of the particle system when subjected to stress, and determining state evolution variables of the particle system based on the phase change characteristics; Determining a steady-state condition corresponding to the state evolution variable and a non-equilibrium potential function of a non-equilibrium state, and determining a dynamic equilibrium relationship corresponding to the particle system based on the steady-state condition and the non-equilibrium potential function; A state evolution model corresponding to the state evolution variable is constructed based on the dynamic equilibrium relationship, and the state evolution model includes an explicit expression of the state evolution variable.

2. The method according to claim 1, wherein The obtaining of the phase change characteristics of the particle system when subjected to force, and determining the state evolution variables of the particle system based on the phase change characteristics, includes: Performing a force analysis on the particle system, and determining phase change characteristics of the particle system when subjected to force based on the analysis results, wherein the phase change characteristics include a solid phase, a liquid phase, and a critical state; A quantitative index of the non-equilibrium thermodynamics of the particle system is determined based on the phase change characteristics, and the quantitative index is used as a state evolution variable of the particle system.

3. The method according to claim 1, wherein The determining of the steady-state condition corresponding to the state evolution variable and the non-equilibrium potential function of the non-equilibrium state, and determining the dynamic equilibrium relationship corresponding to the particle system based on the steady-state condition and the non-equilibrium potential function, includes: Establishing a state evolution equation of the state evolution variable in combination with the steady-state condition and the non-equilibrium potential function; Solving the state evolution equation to obtain a steady-state solution corresponding to the state evolution equation and a recovery condition corresponding to the steady-state solution; The dynamic equilibrium relationship corresponding to the particle system is determined based on the steady-state solution and the recovery condition corresponding to the steady-state solution.

4. The method according to claim 1, wherein After constructing the state evolution model corresponding to the state evolution variable based on the dynamic equilibrium relationship, wherein the state evolution model includes an explicit expression of the state evolution variable, the method further includes: determining a real-time stress and a real-time load change rate corresponding to the structure of the particle system under the intermittent load, and introducing the real-time stress and the real-time load change rate into the explicit expression to obtain an updated explicit expression; A state evolution model of the roadbed under the action of intermittent loads is determined based on the updated explicit expression.

5. The method according to claim 4, wherein The method further comprises: Under intermittent load, the sinusoidal load is used as the input form of the load in the loading stage; Determining the real-time stress of the particle system in the intermittent phase and the real-time stress of the particle system in the loading phase based on the sinusoidal wave load and the explicit expression; The real-time stress under the intermittent load is determined based on the real-time stress in the intermittent stage and the real-time stress in the loading stage.

6. The method according to claim 5, wherein The method further comprises: After the roadbed enters the intermittent stage, determining the first stage load based on the static load of the superstructure of the roadbed; The first stage load is connected with the second stage load to obtain a connected load, and the second stage load is the load corresponding to the loading stage; A real-time load change rate corresponding to the structure of the particle system is determined based on the joint load.

7. The method according to claim 1, wherein The modifying the state evolution model based on the characteristic strain includes: Under the action of intermittent load, obtaining historical strain parameters of the roadbed, wherein the historical strain parameters include the strain state of the state evolution variable in the connection state between the loading state and the intermittent state; determining a characteristic strain of the roadbed based on the strain state, wherein the characteristic strain includes a relevant historical strain range of a state evolution variable under the connection state; An expression of a state evolution variable is introduced based on the characteristic strain to obtain a revised state evolution model.

8. The method according to claim 7, wherein The determining the characteristic strain of the roadbed based on the strain state includes: The state evolution variable in the connection state is defined as the weighted average of the historical strain paths; An exponential decay weight function is established between the length of the historical strain path and the weighted average value, so as to determine the characteristic strain of the roadbed based on the exponential decay weight function.

9. A roadbed state evolution system under intermittent load, characterized in that: The system includes a processor, an input device, an output device and a memory, and the processor, input device, output device and memory are interconnected, wherein the memory is used to store a computer program, and the computer program includes program instructions. The processor is configured to call the program instructions to execute the method for evolution of subgrade state under intermittent loads as described in any one of claims 1 to 8.

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