Near-field dynamic simulation method for multi-phase mesoscopic fatigue damage of track slab SCC

Abstract

The present application relates to the field of civil engineering material simulation technology, and provides a kind of track slab SCC multi-phase mesoscopic fatigue damage near-field dynamics simulation method, comprising: according to four-point bending fatigue test to establish two-dimensional mesoscopic near-field dynamics model;Meshless discretization is carried out to the model;Define the material parameters of cement mortar, coarse aggregate and interface transition zone;Set boundary conditions;Random polygon aggregate is generated by taking and placing method to simulate mesoscopic heterogeneous structure;Mark particle and key type;Apply cyclic loading;Damage evolution calculation is carried out based on the maximum key elongation criterion and fatigue life model;Finally, the calculation is terminated by particle damage index judgment.The present application can realize the accurate simulation of the whole process from crack initiation to expansion of CRTS III type track slab self-compacting concrete, provide effective numerical analysis tool for revealing the influence mechanism of aggregate distribution randomness on fatigue performance, and thus provide theoretical basis for track structure durability design and maintenance.

Description

Technical Field

[0001] This invention relates to the field of civil engineering material simulation technology, and more specifically, to a near-field dynamic simulation method for SCC multiphase microscopic fatigue damage of track slabs. Background Technology

[0002] As a core component of high-speed railway infrastructure, CRTS III slab track widely utilizes self-compacting concrete (SCC) as the infill material for its track slab. SCC possesses excellent flowability and self-compacting properties, effectively filling the gaps between the track slab and the base plate, ensuring the smoothness and durability of the track structure. However, under the long-term cyclic loading of high-speed trains, the SCC layer is prone to progressive fatigue damage, leading to degradation of the track slab's structural performance and threatening the operational safety and service life of high-speed railways. In actual engineering projects, damage phenomena such as micro-fatigue cracks, spalling, and drying shrinkage cracks have appeared in the SCC layer, highlighting the urgent need for in-depth research into its fatigue damage mechanism.

[0003] From a microscale perspective, self-compacting concrete (SCC) is a highly non-homogeneous multiphase composite material, mainly composed of cement mortar, coarse aggregate, and interfacial transition zones. Its microstructure has a decisive influence on its macroscopic mechanical properties and fatigue behavior. Due to factors such as fluctuations in construction quality and variations in material mix proportions during on-site casting, SCC often contains initial defects and exhibits uneven distribution of fatigue resistance, leading to significant dispersion in experimental data. Existing numerical simulation studies often simplify the material as a macroscopically homogeneous medium. While this simplifies the analysis process, it fails to accurately reflect the local damage evolution mechanism and non-homogeneous fatigue behavior, especially failing to reveal the controlling effect of random aggregate distribution on crack initiation and propagation paths.

[0004] At the experimental research level, scholars have systematically explored the fatigue performance of self-compacting concrete through methods such as four-point bending fatigue tests. For example, a fatigue model of the interface bond between self-compacting concrete and track slabs was proposed based on fatigue tensile tests; fatigue damage evolution equations were established through constant and variable amplitude loading tests; static and fatigue test data of self-compacting concrete under different stress levels were systematically provided; and the enhancing effect of nano-silica on the fatigue strength of materials was also confirmed. Although these experimental results provide important evidence for understanding fatigue behavior, fatigue tests themselves are time-consuming and labor-intensive, and laboratory conditions cannot fully reproduce the actual service environment. In particular, it is impossible to quantitatively reveal the intrinsic mechanism of damage evolution and the fundamental reasons for data dispersion at the microscale.

[0005] In the development of numerical simulation technology, the finite element method (FEM) has been widely used in the macroscopic fatigue analysis of self-compacting concrete. For example, a finite element model of a self-compacting concrete layer was established to analyze its fatigue behavior; the influence of train load variations and initial defects on performance degradation was studied based on a damage constitutive model; crack propagation law was analyzed through a vehicle-track coupled dynamics model; and a fatigue bond model for the self-compacting concrete-track interface under cyclic thermal loading was proposed. However, the traditional finite element method is based on classical continuum mechanics theory, and its governing equations fail when discontinuities such as cracks appear in the material. Although the extended finite element method can simulate crack propagation, it requires pre-setting damage criteria and mesh refinement at the crack tip, making the calculation complex and difficult to efficiently handle the micro-interface problems within multiphase materials.

[0006] To overcome the limitations of classical continuum mechanics in damage and fracture simulation, peridynamics theory was proposed. This theory describes the nonlocal interactions between material points through integral equations of motion, naturally avoiding numerical singularities at discontinuities. This theory naturally describes material damage through bond fracture, without pre-setting crack paths or re-meshing, making it particularly suitable for simulating the microscopic damage evolution of non-homogeneous materials such as concrete. In recent years, peridynamics has made significant progress in areas such as concrete microscopic fracture analysis and rail damage simulation. For example, a three-dimensional microscopic peridynamic model of concrete has been established, successfully predicting dynamic impact failure; the fracture behavior of ultra-high performance concrete has been simulated using peridynamics; and the method has been applied to the thermal damage analysis of wheel-rail rolling contact. Furthermore, fatigue damage models based on bond strain provide an effective tool for simulating macroscopic fatigue crack propagation and have been successfully applied to the fatigue analysis of rail and concrete materials.

[0007] While existing fatigue damage analysis methods for self-compacting concrete (SCC) in railway tracks have been applied to some extent in engineering practice, their reliance on classical continuum mechanics theory and the assumption of displacement field continuity in the governing equations makes numerical convergence difficult when discontinuous phenomena such as cracks or damage occur. This makes it challenging to naturally describe the crack initiation and propagation process. Furthermore, macroscopic homogenization models fail to reflect the non-uniform structural characteristics of SCC at the microscale, composed of cement mortar, coarse aggregate, and interfacial transition zone (ITZ), neglecting the crucial influence of aggregate distribution randomness on material mechanical behavior. Consequently, they cannot explain the underlying mechanism of fatigue test data dispersion. Although improved techniques such as the extended finite element method (XFEM) can simulate crack propagation, they require pre-setting crack paths or introducing complex enrichment functions. This significantly increases computational complexity when simulating interfacial failure within multiphase materials, and the prediction accuracy for the microscopic fatigue damage evolution process is limited, making it difficult to effectively guide the durability design and maintenance of SCC layers in railway tracks. Summary of the Invention

[0008] The present invention provides a near-field dynamic simulation method for multiphase microscopic fatigue damage of track slabs in SCC (substrate cavitation cracking). This method can solve the key technical defects of existing macroscopic finite element methods, which are based on classical continuum mechanics theory and are difficult to effectively simulate discontinuous material behavior, reflect microscopic non-uniform structural characteristics, and explain the dispersion of experimental data.

[0009] The near-field dynamic simulation method for multiphase micro-fatigue damage of track slab SCC according to the present invention includes the following steps: S1. Model Establishment: Based on the configuration of the four-point bending fatigue test, a two-dimensional mesoscopic near-field dynamic (PD) model of the self-compacting concrete (SCC) specimen was established; the model was based on the cross-section of the central region of the specimen, and its length... l 400 mm, height h It is 100 mm; S2. Model Discretization: The specimen model is uniformly discretized into PD particles using a meshless method, with particle spacing... Δ x The value is 0.5 mm, and the horizon radius of each particle is defined. δ 4 Δx ; S3. Material Parameter Definition: Define material parameters for each component of self-compacting concrete. The components include cement mortar, coarse aggregate, and interfacial transition zone (ITZ). The material parameters include at least Young's modulus, Poisson's ratio, and energy release rate. S4. Boundary condition settings: Add a layer with a thickness of [value missing] at the bottom of the model. The virtual boundary region is defined, and the downward vertical displacement of particles within this region is constrained. S5. Construct multiphase microstructures; Non-overlapping polygonal aggregate regions were randomly generated within the specimen model using a pick-and-place method to simulate the non-uniform microstructure of self-compacting concrete; the aggregate had a volume fraction of 30% and a radius distribution range of 2.5 mm to 8 mm. S6. Particle and Bond Type Marking: Traverse all particles, mark particles located within the polygonal aggregate area as aggregate particles, and mark the remaining particles as mortar particles; according to the particle type, define the bonds formed between aggregate particles as aggregate bonds, the bonds formed between mortar particles as mortar bonds, and the bonds formed between aggregate particles and mortar particles as interface transition zone bonds. S7. Applying Cyclic Load: Apply cyclic load to the preset loading area at the top of the model. F It is converted into a force density form and applied uniformly to all surface particles in the region; S8. Initial Data Setting: Initialize the number of steady-state calculation steps. i Define a flag variable to indicate whether the maximum bond elongation criterion is satisfied. ; S9. Apply loads to the model step by step, and calculate particle displacement and bond elongation at each calculation step. s If it is determined that there is bond elongation s Reaching or exceeding the critical elongation threshold corresponding to its material Then disconnect the key and set the marker variable. Set to 1; S10. After each load cycle, calculate the bond strain of all unbroken bonds. And according to the bond strain The fatigue cycle count required for the key to fracture is calculated using a preset fatigue life model. ΔN Based on the fatigue cycle number ΔN Update the remaining lifetime variable for all keys. and disconnect the remaining lifespan. The key; S11. Calculate the damage index of each particle in the model. If a particle damage index exists Reaching or exceeding the set damage threshold Or the total number of calculation steps reaches the preset target. If the result is positive, end the calculation; otherwise, update the number of calculation steps. Then return to step S9 to continue execution.

[0010] Preferably, in step S5, the number of sides of the polygonal aggregate is randomly generated between 4 and 9, and the radius of each aggregate is generated by the Fuller gradation curve and the Walvin formula.

[0011] Preferably, in step S6, the interface transition zone is not explicitly geometrically modeled, and its mechanical behavior is indirectly characterized by assigning material parameters to the interface transition zone that distinguish it from aggregate bonds and mortar bonds.

[0012] Preferably, in steps S8 and S9, the critical elongation threshold is... Based on the energy release rate of the material to which the corresponding bond belongs The calculation yields the following formula:

[0013] In the formula It is the bulk modulus of the material.

[0014] Preferably, in step S10, the bond strain ε is defined as the maximum elongation of the bond during one load cycle. With minimum elongation The difference is:

[0015] In the formula, R is the stress ratio under fatigue loading.

[0016] Preferably, in step S10, the fatigue life model is expressed as: the remaining life variable λ and the number of load cycles. N f The relationship satisfies the formula:

[0017] in A and M For material parameters, This is the fatigue limit value; when the bond strain is less than the limit value, the material will not suffer fatigue damage. The bond breaking condition is when λ decreases to 0.

[0018] Preferably, in step S10, the critical bond breakage number method is used to perform fatigue simulation: after one cycle, the fatigue life of all unbroken bonds is calculated, and the minimum value among them is selected as the increment of the cycle step, i.e., the fatigue cycle number. ΔN Used for global update of remaining lifetime; fatigue cycles ΔN The formula is:

[0019] according to Update the remaining lifespan of all keys:

[0020] Preferably, in step S10, as fatigue damage progresses, some bonds will experience elongation exceeding their critical value during a single loading cycle. At this point, these bonds are broken according to the maximum bond elongation criterion. Instead of calculating fatigue life, the number of fatigue cycles is taken. Conversely, if the elongation of a bond exceeds its critical value, the bond strain of each unfailed bond in the steady-state deformation calculation is obtained, and the fatigue life required for bond breakage is calculated. The minimum value is then assigned to the [value / value]. .

[0021] Preferably, in step S11, the damage index at particle x is... Used to quantify the bond breakage rate and damage severity at the particle:

[0022] in For particles volume, Defined as being located at a distance The specified distance All particles inside The clan:

[0023] t For time, It is the initial bond vector:

[0024] The key state function has a value of 1 when the key is intact and a value of 0 when the key is broken.

[0025] The beneficial effects of this invention are as follows: By establishing a mesoscale numerical model based on near-field dynamics theory, a precise simulation of the fatigue damage evolution process of self-compacting concrete track slabs was successfully achieved. This method can naturally describe the entire process from crack initiation to propagation, effectively overcoming the numerical convergence difficulties caused by geometric discontinuities in traditional finite element methods, and significantly improving computational efficiency compared to traditional methods. Simultaneously, by explicitly characterizing the three-phase composition of cement mortar, aggregate, and the interface transition zone, the model realistically reflects the non-uniform structural characteristics of the material, resulting in a 15%-25% improvement in fatigue life prediction accuracy compared to traditional macroscopic methods, with a consistency rate exceeding 90% with experimental data.

[0026] This invention represents a significant breakthrough in elucidating the damage mechanism of materials. By generating various random aggregate distribution models, the influence of microstructural inhomogeneity on the static and dynamic mechanical properties and fatigue life dispersion of self-compacting concrete was systematically analyzed. For the first time, it reveals at the microscale that the randomness of aggregate distribution is the fundamental source of the dispersion in fatigue test data. This discovery provides a new theoretical perspective for understanding the fatigue failure mechanism of self-compacting concrete for railway tracks and offers a more in-depth micromechanical basis for the durability design and maintenance of self-compacting concrete layers in railway tracks.

[0027] The technical effects of this invention have significant value in engineering applications. The established near-field dynamics simulation method not only provides a reliable numerical analysis tool for evaluating the fatigue performance of self-compacting concrete for CRTS III type track slabs, but also provides a scientific basis for durability design and maintenance decisions for ballastless track structures in high-speed railways. This method can guide material proportion optimization, structural design improvement, and service life prediction in engineering practice, helping to reduce track structure maintenance costs and improve operational safety. It has broad application prospects and significant socio-economic value in the field of high-speed railway engineering. Attached Figure Description

[0028] Figure 1 The diagram shows a microscopic PD model of the SCC specimen 4PBT in the embodiment, (a) 4PBT setup; (b) 2D PD model; (c) microstructure representation; Figure 2 This is a schematic diagram of the microstructure of the SCC specimen generated by the program in the embodiment. Figure 3 This is a schematic diagram illustrating the evolution of the damage distribution of the specimen during the monotonic fracture test loading process in the embodiment. Detailed Implementation

[0029] To further understand the content of this invention, a detailed description of the invention will be provided in conjunction with the accompanying drawings and embodiments. It should be understood that the embodiments are merely illustrative and not limiting of the invention.

[0030] Example This embodiment provides a near-field dynamic simulation method for multiphase micro-fatigue damage in track slabs during spontaneous combustion (SCC), which includes the following steps: S1. Model Establishment: Based on the configuration of the four-point bending fatigue test (4PBT), a two-dimensional mesoscopic near-field dynamic (PD) model of the self-compacting concrete (SCC) specimen was established, as follows: Figure 1 As shown in section (a); the length of the three-dimensional specimen. Hekuan and high for Vertical loads and displacement constraints symmetrical about the z-axis were applied to the top and bottom of the specimen, respectively. Each loading and constraint region was along... x Length of shaft The span between the two supports The distance between the two loading points is 300mm. It is 100mm.

[0031] The model is established based on the xz plane of the central region of the specimen, such as Figure 1 As shown in section (b), its length l It is 400mm high. h It is 100 mm; S2. Model Discretization: The specimen model is uniformly discretized into PD particles using a meshless method, with particle spacing... Δ x The diameter is 0.5 mm. According to the nonlocality of PD, any particle... The motion of a (matter point) is influenced not only by its nearest neighbors, but also by what is called its horizon. The influence of all other points within a finite spatial region. For located at distance The specified distance All particles inside A family of (matter points), with a set view radius. . The formula is as follows:

[0032] S3. Material Parameter Definition: Define material parameters for each component of self-compacting concrete. The components include cement mortar, coarse aggregate, and interfacial transition zone (ITZ). The material parameters include at least Young's modulus, Poisson's ratio, and energy release rate.

[0033] As shown in the table below: ; S4. Boundary condition settings: Add a layer with a thickness of [value missing] at the bottom of the model. A virtual boundary region is defined, and the downward vertical displacement of particles within this region is constrained; therefore, a dimension of [missing information] is added to the bottom of the specimen. Virtual boundary region , The internal particles utilize mortar material parameters. In real-world loading scenarios, the bottom support can only provide vertical support to the specimen, thus only constraining... The particles can move vertically downwards, and are allowed to move upwards and to the left and right.

[0034] S5. Construct the multiphase microstructure in SCC; Non-overlapping polygonal aggregate regions were randomly generated within the specimen model using a pick-and-place method to simulate the non-uniform microstructure of self-compacting concrete; the number of sides of the polygonal aggregates was randomly generated between 4 and 9. Figure 1 As shown in section (c). The aggregate has a volume fraction of 30% and a radius distribution ranging from 2.5 mm to 8 mm; the radius of each aggregate is generated by the Fuller gradation curve and the Walvin formula.

[0035] S6. Particle and Bond Type Labeling: Traverse all particles, labeling particles located within the polygonal aggregate region as aggregate particles, and the remaining particles as mortar particles; for example... Figure 2 The microstructure of SCC concrete generated by the program is shown, where gray particles represent aggregate particles and blue particles represent mortar particles. Based on particle type, the bonds formed between aggregate particles are defined as aggregate bonds, the bonds formed between mortar particles as mortar bonds, and the bonds formed between aggregate and mortar particles as ITZ bonds. Therefore, the SCC sample model contains two types of particles and three types of bonds. Material parameters for the SCC composition are assigned to these particles and bonds according to their types.

[0036] The thickness of the ITZ is typically 20 to 100 micrometers. For accurate characterization of the ITZ, the interparticle spacing needs to be 20 micrometers, at which point the computational scale of the PD model reaches [a specific value]. Individual particles would lead to excessively high computational costs. Therefore, the model does not explicitly set the ITZ, but instead represents the ITZ indirectly through the interfacial interaction between aggregate and mortar.

[0037] S7. Applying Cyclic Load: Apply cyclic load to the preset loading area at the top of the model. F It is converted into force density form and applied uniformly to all surface particles in the region.

[0038] refer to Figure 1 The loading conditions in section (a) are defined. Figure 1 The loading area shown in section (b) It contains only surface particles. Applying force Distributed uniformly in the form of force density The particles in the middle, the external force density applied to each particle Expressed as:

[0039] S8. Initial Data Setting: Initialize the number of steady-state calculation steps. i Define a flag variable to indicate whether the maximum bond elongation criterion is satisfied. .

[0040] The bond elongation s is defined as:

[0041] In the formula, t is time. It is a relative displacement vector, representing the difference between the displacement vectors of the two particles:

[0042] in, For external force density Under the action, particles and The displacement that occurs over time.

[0043] It is the initial bond vector:

[0044] S9. Apply loads to the model step by step, and calculate the particle displacement at each calculation step. and bond elongation s If it is determined that there is bond elongation s Reaching or exceeding the critical elongation threshold corresponding to its material Then disconnect the key and set the marker variable. Set to 1.

[0045] Critical elongation threshold Based on the energy release rate of the material to which the corresponding bond belongs The calculation yields the following formula:

[0046] In the formula It is the bulk modulus of the material.

[0047] S10. After each load cycle, calculate the bond strain of all unbroken bonds. And according to the bond strain The fatigue cycle count required for the key to fracture is calculated using a preset fatigue life model. ΔN Based on the fatigue cycle number ΔN Update the remaining lifetime variable for all keys. and disconnect the remaining lifespan. The key.

[0048] The bond strain ε is defined as the maximum elongation of the bond during one load cycle. With minimum elongation The difference is:

[0049] In the formula R It is the stress ratio under fatigue loading.

[0050] The fatigue life model is expressed as: the remaining life variable λ and the number of load cycles. N f The relationship satisfies the formula:

[0051] in A and M For material parameters, The fatigue limit value is the value at which the material will not experience fatigue damage when the bond strain is less than the limit value; the remaining life variable... The remainder is a function of key strain and load cycles, initially set to 1. For each unfailed key, the remaining lifetime decreases with increasing load cycles.

[0052] The bond breaking condition is λ as a function of λ. N f The value drops to 0. Bond breakage is represented as:

[0053] Fatigue simulation was performed using the critical bond breakage number method: After one load cycle, the fatigue life of all unbroken bonds was calculated, and the minimum value was selected as the increment for that cycle step, i.e., the fatigue cycle number. ΔN Used for global update of remaining lifetime; fatigue cycles ΔN The formula is:

[0054] according to Update the remaining lifespan of all keys:

[0055] As fatigue damage progresses, some bonds will exceed their critical elongation value during a single loading cycle. At this point, these bonds are broken according to the maximum bond elongation criterion. Instead of calculating fatigue life, the number of fatigue cycles is taken. Conversely, if the elongation of a bond exceeds its critical value, the bond strain of each unfailed bond in the steady-state deformation calculation is obtained, and the fatigue life required for bond breakage is calculated. The minimum value is then assigned to the [value / value]. .

[0056] S11. Calculate the damage index of each particle in the model. If a particle damage index exists Reaching or exceeding the set damage threshold Or the total number of calculation steps reaches the preset target. If the result is positive, end the calculation; otherwise, update the number of calculation steps. Then return to step S9 to continue execution.

[0057] Damage modeling (PD) describes material damage through bond breakage. When bonds are intact, they can generate forces to resist deformation; once bonds break, they can no longer withstand external forces. A direct way to represent this damage model is to introduce bond state functions. The value is 1 when the bond is intact and 0 when the bond is broken.

[0058] Damage index at particle x Used to quantify the bond breakage rate and damage severity at the particle:

[0059] in For particles The volume.

[0060] Considering the internal forces generated by the spatial integral of all bond interactions, the effects of bond damage, and the external body force density Matter point The equation of motion can be expressed as:

[0061] in For material density, The bond density is expressed as:

[0062] Where s is the bond elongation, and the micromodulus c is defined according to the material parameters, horizontal dimensions, and model dimension:

[0063] in and These are Young's modulus and Poisson's ratio of the rail material, respectively.

[0064] The crack propagation process of the specimen obtained by the model is as follows: Figure 3 Analysis reveals that the ITZ (internal zone of fracture), being the weakest link in the composite material, is damaged first, initiating macroscopic cracks. Notably, this damage does not occur at the bottom of the specimen—the point of theoretical maximum bending stress—but rather within the interface near the specimen. Subsequently, the crack propagates in both positive and negative z-directions, traversing the bottom surface of the specimen. With continued loading, the crack propagates upwards until it reaches the top surface, leading to eventual structural failure. As the crack develops, it bypasses stronger aggregates and preferentially advances along surrounding interfaces, creating a tortuous rather than straight fracture path. Furthermore, crack bifurcation was observed in the upper middle part of the specimen.

[0065] The present invention and its embodiments have been described above illustratively. This description is not restrictive, and the figures shown are only one embodiment of the present invention; the actual structure is not limited thereto. Therefore, if those skilled in the art are inspired by this description and design similar structures and embodiments without departing from the spirit of the present invention, such designs should fall within the protection scope of the present invention.

Claims

1. A near-field dynamic simulation method for multiphase micro-fatigue damage of track slab SCC, characterized in that: Includes the following steps: S1. Model Establishment: Based on the configuration of the four-point bending fatigue test, a two-dimensional mesoscopic near-field dynamic (PD) model of the self-compacting concrete (SCC) specimen was established; the model was based on the cross-section of the central region of the specimen, and its length... l 400 mm, height h It is 100 mm; S2. Model Discretization: The specimen model is uniformly discretized into PD particles using a meshless method, with particle spacing... Δx The value is 0.5 mm, and the horizon radius of each particle is defined. δ 4 Δx ; S3. Material Parameter Definition: Define material parameters for each component of self-compacting concrete. The components include cement mortar, coarse aggregate, and interfacial transition zone (ITZ). The material parameters include at least Young's modulus, Poisson's ratio, and energy release rate. S4. Boundary condition settings: Add a layer with a thickness of [value missing] at the bottom of the model. The virtual boundary region is defined, and the downward vertical displacement of particles within this region is constrained. S5. Construct multiphase microstructures; Non-overlapping polygonal aggregate regions were randomly generated within the specimen model using a pick-and-place method to simulate the non-uniform microstructure of self-compacting concrete; the aggregate had a volume fraction of 30% and a radius distribution range of 2.5 mm to 8 mm. S6. Particle and Bond Type Marking: Traverse all particles, mark particles located within the polygonal aggregate area as aggregate particles, and mark the remaining particles as mortar particles; according to the particle type, define the bonds formed between aggregate particles as aggregate bonds, the bonds formed between mortar particles as mortar bonds, and the bonds formed between aggregate particles and mortar particles as interface transition zone bonds. S7. Applying Cyclic Load: Apply cyclic load to the preset loading area at the top of the model. F It is converted into a force density form and applied uniformly to all surface particles in the region; S8. Initial Data Setting: Initialize the number of steady-state calculation steps. i Define a flag variable to indicate whether the maximum bond elongation criterion is satisfied. ; S9. Apply loads to the model step by step, and calculate particle displacement and bond elongation at each calculation step. s If it is determined that there is bond elongation s Reaching or exceeding the critical elongation threshold corresponding to its material Then disconnect the key and set the marker variable. Set to 1; S10. After each load cycle, calculate the bond strain of all unbroken bonds. And according to the bond strain The fatigue cycle count required for the key to fracture is calculated using a preset fatigue life model. ΔN ; Based on the fatigue cycle number ΔN Update the remaining lifetime variable for all keys. and disconnect the remaining lifespan. The key; S11. Calculate the damage index of each particle in the model. If a particle damage index exists Reaching or exceeding the set damage threshold Or the total number of calculation steps reaches the preset target. If the result is positive, end the calculation; otherwise, update the number of calculation steps. Then return to step S9 to continue execution.

2. The near-field dynamic simulation method for SCC multiphase micro-fatigue damage of track slabs according to claim 1, characterized in that: In step S5, the number of sides of the polygonal aggregate is randomly generated between 4 and 9, and the radius of each aggregate is generated by the Fuller gradation curve and the Walvin formula.

3. The near-field dynamic simulation method for SCC multiphase micro-fatigue damage of track slabs according to claim 2, characterized in that: In step S6, the interface transition zone is not explicitly geometrically modeled. Its mechanical behavior is indirectly characterized by assigning material parameters to the interface transition zone that distinguish it from aggregate bonds and mortar bonds.

4. The near-field dynamic simulation method for SCC multiphase micro-fatigue damage of track slabs according to claim 3, characterized in that: In steps S8 and S9, the critical elongation threshold Based on the energy release rate of the material to which the corresponding bond belongs The calculation yields the following formula: ； In the formula It is the bulk modulus of the material.

5. The near-field dynamic simulation method for SCC multiphase micro-fatigue damage of track slabs according to claim 4, characterized in that: In step S10, the bond strain ε Defined as the maximum elongation of the bond during one load cycle. With minimum elongation The difference is: ； In the formula R It is the stress ratio under fatigue loading.

6. The near-field dynamic simulation method for SCC multiphase micro-fatigue damage of track slabs according to claim 5, characterized in that: In step S10, the fatigue life model is expressed as: remaining life variable λ With load cycle number N f The relationship satisfies the formula: ； in A and M For material parameters, This is the fatigue limit value; when the bond strain is less than the limit value, the material will not suffer fatigue damage. The bond breaking condition is when λ decreases to 0.

7. The near-field dynamic simulation method for multiphase micro-fatigue damage of track slab SCC according to claim 6, characterized in that: In step S10, fatigue simulation is performed using the critical bond breakage number method: after one cycle, the fatigue life of all unbroken bonds is calculated, and the minimum value is selected as the increment for that cycle step, i.e., the fatigue cycle number. ΔN Used for global update of remaining lifetime; fatigue cycles ΔN The formula is: ；； according to Update the remaining lifespan of all keys:

8. The near-field dynamic simulation method for SCC multiphase micro-fatigue damage of track slabs according to claim 7, characterized in that: In step S10, as fatigue damage progresses, some bonds will experience elongation exceeding their critical values ​​during a single loading cycle. At this point, these bonds are broken according to the maximum bond elongation criterion. Instead of calculating fatigue life, the number of fatigue cycles is taken. Conversely, if the elongation of a bond exceeds its critical value, the bond strain of each unfailed bond in the steady-state deformation calculation is obtained, and the fatigue life required for bond breakage is calculated. The minimum value is then assigned to the [value / value]. .

9. The near-field dynamic simulation method for SCC multiphase micro-fatigue damage of track slabs according to claim 8, characterized in that: In step S11, the damage index at particle x Used to quantify the bond breakage rate and damage severity at the particle: ； in For particles volume, Defined as being located at a distance The specified distance All particles inside The clan: ； t For time, It is the initial bond vector: ； The key state function has a value of 1 when the key is intact and a value of 0 when the key is broken.

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