Asphalt mixture particle size response simulation method and related device

Abstract

The invention discloses an asphalt mixture particle size response simulation method and a related device. The method comprises the following steps: establishing a finite element model of a tire, and calculating to obtain non-uniform three-dimensional contact stress field data of the tire on a road surface; establishing a discrete element model of the asphalt mixture, and applying the non-uniform three-dimensional contact stress field data as an external load to surface asphalt mixture particles of the discrete element model to obtain an FEM-DEM coupling model; and based on the FEM-DEM coupling model, performing simulation calculation by using a double-layer contact detection algorithm, and dynamically analyzing the size response of the particles in the asphalt mixture. According to the invention, the dynamic simulation of the pavement structure model containing a large number of irregular particles under the real tire load is realized, so that the influence of the factors on the macro-performance of the asphalt mixture is systematically revealed from the micro-scale; the problem that the discontinuous and heterogeneous characteristics of the asphalt mixture are difficult to accurately capture by an existing continuous medium mechanical method is solved.

Description

Technical Field

[0001] This invention belongs to the field of road engineering simulation technology, and relates to a method and related apparatus for simulating the particle size response of asphalt mixtures. Background Technology

[0002] As a major component of modern transportation networks, asphalt pavements face severe challenges to their performance and lifespan due to increasing traffic volume and climate change. Pavement degradation is a major source of road maintenance costs, and this degradation is closely related to the complex interactions between tires and asphalt mixtures. Therefore, a deep understanding of the mechanical response mechanisms of asphalt pavements under rolling tire loads is crucial for improving the durability of road infrastructure.

[0003] Current research on the mechanical properties of asphalt pavements under tire loads primarily employs the finite element method (FEM) based on continuum mechanics. FEM allows for the creation of high-precision tire models that can account for complex conditions such as acceleration and braking, effectively simulating the stress distribution in tire-pavement contact. However, asphalt mixtures are inherently heterogeneous and discontinuous granular materials composed of aggregate particles of varying sizes and shapes and an asphalt matrix. FEM struggles to effectively reveal the microscopic behaviors such as interparticle interactions, reorganization, and stress transfer within these mixtures, which are crucial for understanding the deterioration processes of materials, including fatigue, cracking, and permanent deformation.

[0004] The Discrete Element Method (DEM), as a powerful tool for simulating the behavior of granular materials, has been widely used to study the micromechanical properties of asphalt mixtures. DEM treats the material as a collection of discrete particles, effectively capturing interparticle contact, slippage, and rearrangement phenomena. However, DEM is not suitable for constructing tire models. Current DEM-based pavement mechanics simulations typically employ simplified uniform tire load boundary conditions, failing to reproduce complex, non-uniformly distributed tire loads, thus making it difficult to obtain accurate micromechanical responses.

[0005] Therefore, there is an urgent need for a numerical simulation method that can take into account both the real tire load boundary and the microstructural characteristics of high-fidelity asphalt mixtures, so as to comprehensively study the micromechanical response of asphalt mixtures under tire load conditions and thus guide the intelligent and refined design of road facilities. Summary of the Invention

[0006] The purpose of this invention is to provide a method and related apparatus for simulating the particle size response of asphalt mixtures, which solves the problem that existing technologies cannot simultaneously ensure the realism of tire load and the high-fidelity mapping of the model's microstructural features.

[0007] To achieve the above objectives, the present invention employs the following technical solution: A method for simulating the particle size response of asphalt mixtures includes: A finite element model of the tire was established, and the non-uniform three-dimensional contact stress field data of the tire on the road surface were calculated. A discrete element model of asphalt mixture is established, and non-uniform three-dimensional contact stress field data is applied as an external load to the surface asphalt mixture particles of the discrete element model to obtain the FEM-DEM coupled model. Based on the FEM-DEM coupled model, a dual-layer contact detection algorithm is used for simulation calculation to dynamically analyze the particle-scale response inside the asphalt mixture.

[0008] Furthermore, the discrete element model uses irregularly shaped polyhedral particles to simulate the real form of asphalt mixtures, and the interaction between particles is described by a viscoelastic contact model to simulate the viscoelastic behavior of asphalt mixtures.

[0009] Furthermore, the process of calculating the viscoelastic behavior of asphalt mixtures using the Burgers contact model includes: Dynamic modulus experiments were conducted on asphalt mixture samples to obtain their dynamic modulus and phase angle at different frequencies; Based on the analytical expression of complex compliance of the Burgers contact model, the calculated values ​​are matched with the experimental values ​​through a fitting algorithm, thereby calibrating the macroscopic model parameters. Based on macroscopic parameters and particle contact geometry information, the normal and tangential parameters of the microscopic contact of asphalt mixtures are calculated.

[0010] Furthermore, the analytical expression for the complex compliance of the Burgers contact model is:

[0011]

[0012]

[0013] in, For complex compliance, and These represent the stiffness and viscosity of the macroscopic Maxwell model, respectively. and These represent the stiffness and viscosity of the Kelvin-Voyt model, respectively. and They are respectively The real and imaginary parts, It represents angular frequency.

[0014] Furthermore, the coupling process of the FEM-DEM coupled model includes: Contact detection is performed between the contact stress field nodes of the finite element model and the surface particles of the discrete element model to determine the particles corresponding to each stress field node. The contact force at each stress field node is applied to the center of inertia of the corresponding particle and converted into external force and torque acting on the particle.

[0015] Furthermore, the dual-layer contact detection algorithm includes: Coarse detection based on bounding box algorithm is used to initially screen out particles that may come into contact with stress field nodes; For particles that have been roughly screened out, the cross product method is used for fine detection to accurately locate the particle surface where the stress field nodes are located.

[0016] Furthermore, the dynamic analysis process of the particle-scale response within asphalt mixtures includes: The rolling process of a tire is simulated by moving the position of the contact stress field at a time step; By comparing the particle-scale response under different rolling speeds or different rolling conditions, the influence of tire motion state on the micromechanical behavior of asphalt mixtures is evaluated.

[0017] A particle size response simulation system for asphalt mixtures includes: The calculation module is used to build a finite element model of the tire and calculate the non-uniform three-dimensional contact stress field data of the tire on the road surface. The coupling module is used to establish a discrete element model of asphalt mixture. The non-uniform three-dimensional contact stress field data is used as an external load and applied to the surface asphalt mixture particles of the discrete element model to obtain the FEM-DEM coupled model. The analysis module is used to perform simulation calculations based on the FEM-DEM coupled model and the dual-layer contact detection algorithm to dynamically analyze the particle-scale response inside the asphalt mixture.

[0018] A terminal device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method.

[0019] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method.

[0020] Compared with the prior art, the present invention has the following beneficial effects: This invention provides a method for simulating the particle-scale response of asphalt mixtures. First, a detailed tire model is established using the finite element method to obtain the real non-uniform tire-road contact stress. Then, a microscopic model of the asphalt mixture containing irregular particle morphology and viscoelastic contact is constructed using the discrete element method. Finally, through an efficient coupling algorithm, the macroscopic load obtained from the finite element method is applied to the surface of the DEM model, thereby accurately simulating the internal response of the asphalt mixture under rolling tire load at the particle scale. This invention combines the advantages of the finite element method (FEM) in simulating tire structure and material properties with the advantages of the discrete element method (DEM) in simulating the microscopic and discontinuous structural characteristics of asphalt mixtures. This establishes an effective simulation framework capable of accurately analyzing the particle-scale mechanical response of asphalt mixtures under real tire loads. Through FEM-DEM coupled simulation, it enables dynamic simulation of pavement structure models containing numerous irregular particles under real tire loads. It can conveniently simulate the microscopic mechanical response of asphalt mixtures under various working conditions such as different tire rolling speeds, braking, and acceleration. This systematically reveals the influence of these factors on the macroscopic properties of asphalt mixtures at the microscopic scale, elucidating the evolution of particle displacement and contact force networks. It provides a scientific basis for optimizing pavement design, predicting its service life, and understanding the microscopic mechanisms of rutting, fatigue cracking, and other defects. It offers a powerful microscopic mechanical analysis tool for understanding the degradation mechanism of asphalt pavements and optimizing pavement structure design. This solves the problem that existing continuous medium mechanics methods struggle to accurately capture the discontinuous and heterogeneous characteristics of asphalt mixtures. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart of the particle size response simulation method for asphalt mixtures according to the present invention.

[0023] Figure 2 The figures shown are a schematic diagram of tire-road contact and a numerical model diagram of tire according to the present invention, wherein (a) is a schematic diagram of tire-road contact and (b) is a numerical model diagram of tire.

[0024] Figure 3 This is a tire-road contact stress diagram of the present invention.

[0025] Figure 4 shows the contact stress diagrams of the tire of the present invention in three directions, wherein (a) is the contact stress diagram in the Z direction, (b) is the contact stress diagram in the X direction, and (c) is the contact stress diagram in the Y direction.

[0026] Figure 5 This is a numerical sample modeling diagram of asphalt pavement for the present invention.

[0027] Figure 6 This is an aggregate gradation diagram of the asphalt mixture of the present invention.

[0028] Figure 7 is a comparison diagram of experimental test and numerical simulation of the present invention, wherein (a) is a comparison diagram of dynamic modulus and (b) is a comparison diagram of phase angle.

[0029] Figure 8 This is a schematic diagram of the coupling simulation of FEM and DEM according to the present invention.

[0030] Figure 9 is a schematic diagram of the double-layer contact detection algorithm between finite element mesh elements and discrete element particles of the present invention, wherein (a) is a finite element mesh element diagram and (b) is a schematic diagram of the double-layer contact detection algorithm between discrete element particles.

[0031] Figure 10 is a schematic diagram of the coupling algorithm of the present invention, wherein (a) is a schematic diagram of the xy plane, (b) is a schematic diagram of the yz plane, and (c) is a schematic diagram of the xz plane.

[0032] Figure 11 shows the particle displacement distribution and tire-road contact stress diagram of the present invention, wherein (a) is the particle displacement distribution diagram in the X direction, (b) is the contact stress diagram in the X direction, (c) is the particle displacement distribution diagram in the Y direction, (d) is the contact stress diagram in the Y direction, (e) is the particle displacement distribution diagram in the Z direction, and (f) is the contact stress diagram in the Z direction.

[0033] Figure 12 This is a particle displacement distribution diagram under non-uniform tire load according to the present invention.

[0034] Figure 13 This is a schematic diagram of the structure of the asphalt mixture particle size response simulation system according to a preferred embodiment of the present invention.

[0035] Figure 14 This is a schematic diagram of the electronic device structure according to a preferred embodiment of the present invention. Detailed Implementation

[0036] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of this application, including various details to aid understanding. These should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this application. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0037] Obviously, the described embodiments are only some, not all, of the embodiments in this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0038] It should be noted that the terminals involved in the embodiments of this application may include, but are not limited to, mobile phones, personal digital assistants (PDAs), wireless handheld devices, tablet computers, personal computers (PCs), MP3 players, MP4 players, wearable devices (e.g., smart glasses, smartwatches, smart bracelets), smart home devices, and other smart devices.

[0039] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0040] The present invention will now be described in further detail with reference to the accompanying drawings: See Figure 1 This invention provides a method for simulating the particle size response of asphalt mixtures, specifically including the following steps: Step 1: Establish a three-dimensional finite element model of the tire using the finite element method (FEM). By simulating the contact between the tire and the road surface, accurately calculate the non-uniform contact stress field acting on the road surface under different tire operating conditions (such as static load, free rolling, and braking). This stress field includes three components: vertical, lateral, and longitudinal.

[0041] Step 2: A discrete element model of the asphalt mixture is constructed using the discrete element method (DEM). This model uses irregular polyhedral particles to represent the morphology and gradation of real aggregates. The interactions between particles are defined using the Burgers contact model, which describes the viscoelastic behavior of the material. The parameters of the Burgers contact model are calibrated by performing dynamic modulus experiments on real asphalt mixture specimens and fitting the data.

[0042] To simulate the viscoelasticity of asphalt mixtures, the Burgers contact model was used to simulate the interparticle interactions. This model consists of a Maxwell model and a Kelvin-Voyt model cascaded together, capable of simultaneously describing the creep and relaxation properties of the material. Its complex compliance... It is given by the following formula:

[0043]

[0044]

[0045] in, and These represent the stiffness and viscosity of the macroscopic Maxwell model, respectively. and These represent the stiffness and viscosity of the Kelvin-Voyt model, respectively. and They are respectively The real and imaginary parts, It represents angular frequency.

[0046] The evaluation of the normal composition of microscopic parameters at the particle scale is as follows:

[0047]

[0048]

[0049]

[0050] in, It is the cross-sectional area of ​​the viscous slurry in contact between particles. It is the initial distance between particles. This represents the normal stiffness of the Maxwell model. This represents the normal viscosity in the Maxwell model. This indicates the normal stiffness of the Kelvin-Voyt model. This represents the normal viscosity of the Kelvin-Voyt model.

[0051] By using the above normal parameters, the components of the contact model in the two tangential directions can be calculated:

[0052]

[0053]

[0054]

[0055] in, It is Poisson's ratio. This represents the stiffness in the t-direction of the Maxwell model. This represents the stiffness in the s-direction of the Maxwell model method. This represents the viscosity in the t-direction of the Maxwell model. This represents the viscosity in the s-direction of the Maxwell model. This represents the stiffness in the t-direction of the Kelvin-Voyt model. This represents the stiffness in the s-direction of the Kelvin-Voyt model. This represents the viscosity in the t-direction of the Kelvin-Voyt model. The viscosity in the s-direction is represented by the Kelvin-Voyt model.

[0056] If the material is isotropic, the values ​​of the parameters in the s direction are the same as those in the t direction, which can be written as: This represents the normal tangential stiffness of the Maxwell model. This represents the tangential viscosity in the Maxwell model. This indicates the tangential stiffness of the Kelvin-Voyt model. This represents the tangential viscosity in the Kelvin-Voyt model.

[0057] Step 3: Establish the FEM-DEM coupled model. Apply the non-uniform contact stress field calculated by FEM in Step 1 as a boundary condition to the surface of the DEM asphalt mixture model in Step 2. Based on the dual-layer contact detection algorithm, the nodal forces of the macroscopic stress field are accurately transferred to the corresponding discrete polyhedral particles. The specific process of the dual-layer contact detection algorithm is as follows: Traverse all particles on the surface of the DEM model and use the bounding box algorithm to determine nodal forces. Check if the coordinates of the point of application are within the bounding box of the particle. If so, add the particle to the candidate list. Iterate through the particles in the candidate list matrix. For each particle, determine the nodal forces using the vector cross product algorithm. Does the point of action P fall within any triangular unit (ABC) on its surface?

[0058] if ,So On the surface of particles.

[0059] When the discrete element particle and the finite element element come into contact, the nodal forces of the finite element mesh act on the polyhedral particle, and the nodal forces acting at the contact point P on the particle surface are... This is equivalent to a set of forces and torques acting on the center of inertia of the particle, as shown in Figure 10.

[0060] Will It is decomposed into three components along the coordinate axes and applied directly as an external force to the particle's center of mass:

[0061]

[0062]

[0063] Let the vector pointing from the center of mass to the contact point P be ( , , Then the torque component applied to the particle is:

[0064] Step 4: Within the coupled framework, the movement of tire load on the asphalt mixture surface is simulated through time-history integration. Rolling loading is achieved by updating the stress field position at each time step. The displacement distribution, velocity evolution, and contact force network evolution of particles within the mixture are dynamically analyzed, thereby revealing the material's response and damage mechanisms at the microscopic level.

[0065] The present invention will be further described in detail below through specific embodiments: Example 1: First, a detailed three-dimensional finite element (FEM) model of the tire is established. For example... Figure 2 As shown, this embodiment uses tires with a specification of 185 / 65R15.

[0066] To determine the material properties of the deformable portion of the tire, tire compression tests were conducted. The tire was inflated to 2.2 bar and placed between two rigid plates, and force-displacement data were recorded at different pressure levels of 1 kN, 2 kN, 3 kN, and 4 kN. Subsequently, in the numerical simulation, the deformable portion was assumed to be a homogeneous elastic material, and the material parameters obtained through calibration using the experimental data were: Young's modulus 1.0 MPa, Poisson's ratio 0.36.

[0067] A tire-road contact model was established to obtain the contact stress. The road layer was modeled as a homogeneous elastic body with dimensions of 0.3m × 0.3m × 0.04m. Its material properties were referenced from the dynamic modulus experimental results at 15℃ and 10Hz, and were set to a modulus of 13000 MPa and a Poisson's ratio of 0.35. Figure 3 As shown, the contact between the tire and the road surface is determined using Coulomb's law of friction, with a friction coefficient set to 0.8. Simulations are performed using an implicit contact solution algorithm based on contact dynamics. A vertical load of 5 kN is applied, and the three-dimensional contact stress distribution of the tire on the road surface is obtained, as shown in Figure 4. Based on the stress distribution results, the tire track area size required for subsequent DEM simulation is determined to be 0.135 m × 0.155 m.

[0068] Based on the determined tire footprints, a discrete element model of the asphalt mixture is constructed. For example... Figure 5 As shown, this model represents the asphalt mixture layer beneath the tire tracks. This embodiment uses the aggregate gradation of BBSG (0 / 10) semi-coarse asphalt concrete commonly used in France, and the gradation curve is shown in the figure. Figure 6As shown, approximately 19,000 irregular polyhedral particles were generated using a particle mosaic algorithm to simulate the morphology and size distribution of real aggregates. To balance computational efficiency and accuracy, fine aggregates with a diameter less than 2 mm were considered as part of the asphalt matrix.

[0069] To simulate the viscoelasticity of asphalt mixtures, the Burgers contact model was used to simulate the interparticle interactions. This model consists of a Maxwell model and a Kelvin-Voyt model cascaded together, capable of simultaneously describing the creep and relaxation properties of the material. Its complex compliance... It is given by the following formula:

[0070]

[0071]

[0072] in, and These represent the stiffness and viscosity of the macroscopic Maxwell model, respectively. and These represent the stiffness and viscosity of the Kelvin-Voyt model, respectively. and They are respectively The real and imaginary parts, It represents angular frequency.

[0073] The evaluation of the normal composition of microscopic parameters at the particle scale is as follows:

[0074]

[0075]

[0076]

[0077] in, It is the cross-sectional area of ​​the viscous slurry in contact between particles. It is the initial distance between particles. This represents the normal stiffness of the Maxwell model. This represents the normal viscosity in the Maxwell model. This indicates the normal stiffness of the Kelvin-Voyt model. This represents the normal viscosity of the Kelvin-Voyt model.

[0078] By using the above normal parameters, the components of the contact model in the two tangential directions can be calculated:

[0079]

[0080]

[0081]

[0082] in, It's Poisson's ratio, set to 0.35. This represents the stiffness in the t-direction of the Maxwell model. This represents the stiffness in the s-direction of the Maxwell model method. This represents the viscosity in the t-direction of the Maxwell model. This represents the viscosity in the s-direction of the Maxwell model. This represents the stiffness in the t-direction of the Kelvin-Voyt model. This represents the stiffness in the s-direction of the Kelvin-Voyt model. This represents the viscosity in the t-direction of the Kelvin-Voyt model. The viscosity in the s-direction is represented by the Kelvin-Voyt model.

[0083] To determine the model parameters, dynamic modulus tests were conducted on asphalt mixture samples at 15℃, obtaining experimental data on dynamic modulus and phase angle at different frequencies: 3Hz, 6Hz, 10Hz, 25Hz, and 40Hz. A fitting algorithm developed in Python was used to match the macroscopic parameters of the Burgers model with the experimental data, resulting in good agreement between the numerical simulation results and the experimental data. The average error in dynamic modulus was 4.4%, and the average error in phase angle was 5.6%, as shown in Figure 7. The final determined microscopic contact model parameters are shown in Table 1. Table 1 Parameters of the Microscopic Contact Model

[0084] The non-uniformly distributed tire load obtained from FEM is applied to the DEM model. Since the road surface has a high stiffness relative to the tire, it can be assumed that the contact stress during tire rolling is not affected by the small deformation of the road surface. Therefore, unidirectional coupling can be used to directly apply the stress field calculated by FEM as an external force to the surface particles of the DEM model.

[0085] The key to the coupling algorithm is contact detection and nodal force application, such as Figure 8 As shown in Figure 9. To verify the effectiveness of the coupling algorithm, a static loading simulation was first performed. The loading time was set to 1×10. -2 To ensure numerical stability, the time step for the entire simulation process was maintained at 5 × 10⁻⁶. -5 The static loading results are shown in Figure 11 and... Figure 12 As shown, the displacement distribution cloud map of the particles is highly consistent with the cloud map of the applied contact stress field in terms of shape and direction, proving the accuracy of the coupling method.

[0086] In summary, the FEM-DEM coupled framework proposed in this invention successfully combines the advantages of FEM in capturing real macroscopic loads with the ability of DEM in analyzing the response of microscopic heterogeneous materials. This invention provides an unprecedented perspective for a deeper understanding of the degradation mechanism of asphalt mixtures under real tire loads, and has significant theoretical value and application potential for improving pavement design and enhancing road durability.

[0087] Example 2: This invention also provides a particle size response simulation system for asphalt mixtures, such as... Figure 13 As shown, the system includes: a calculation module, a coupling module, and an analysis module.

[0088] The calculation module is used to build a finite element model of the tire and calculate the non-uniform three-dimensional contact stress field data of the tire on the road surface. The coupling module is used to establish a discrete element model of asphalt mixture. The non-uniform three-dimensional contact stress field data is used as an external load and applied to the surface asphalt mixture particles of the discrete element model to obtain the FEM-DEM coupled model. The analysis module is used to perform simulation calculations based on the FEM-DEM coupled model and the dual-layer contact detection algorithm to dynamically analyze the particle-scale response inside the asphalt mixture.

[0089] It is understood that the asphalt mixture particle size response simulation system provided by the present invention corresponds to the asphalt mixture particle size response simulation method provided in the foregoing embodiments. The relevant technical features of the asphalt mixture particle size response simulation system can be referred to the relevant technical features of the asphalt mixture particle size response simulation method. The system executes the steps of the asphalt mixture particle size response simulation method.

[0090] The method for simulating the particle size response of asphalt mixtures includes the following steps: A finite element model of the tire was established, and the non-uniform three-dimensional contact stress field data of the tire on the road surface were calculated. A discrete element model of asphalt mixture is established, and non-uniform three-dimensional contact stress field data is applied as an external load to the surface asphalt mixture particles of the discrete element model to obtain the FEM-DEM coupled model. Based on the FEM-DEM coupled model, a dual-layer contact detection algorithm is used for simulation calculation to dynamically analyze the particle-scale response inside the asphalt mixture.

[0091] Another object of the present invention is to provide an electronic device, such as... Figure 14As shown, it includes a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor performing the steps of the asphalt mixture particle size response simulation method.

[0092] The method for simulating the particle size response of asphalt mixtures includes the following steps: A finite element model of the tire was established, and the non-uniform three-dimensional contact stress field data of the tire on the road surface were calculated. A discrete element model of asphalt mixture is established, and non-uniform three-dimensional contact stress field data is applied as an external load to the surface asphalt mixture particles of the discrete element model to obtain the FEM-DEM coupled model. Based on the FEM-DEM coupled model, a dual-layer contact detection algorithm is used for simulation calculation to dynamically analyze the particle-scale response inside the asphalt mixture.

[0093] A fourth objective of this invention is to provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the asphalt mixture particle size response simulation method.

[0094] The method for simulating the particle size response of asphalt mixtures includes the following steps: A finite element model of the tire was established, and the non-uniform three-dimensional contact stress field data of the tire on the road surface were calculated. A discrete element model of asphalt mixture is established, and non-uniform three-dimensional contact stress field data is applied as an external load to the surface asphalt mixture particles of the discrete element model to obtain the FEM-DEM coupled model. Based on the FEM-DEM coupled model, a dual-layer contact detection algorithm is used for simulation calculation to dynamically analyze the particle-scale response inside the asphalt mixture.

[0095] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0096] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0097] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0098] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0099] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for simulating the particle size response of asphalt mixtures, characterized in that, include: A finite element model of the tire was established, and the non-uniform three-dimensional contact stress field data of the tire on the road surface were calculated. A discrete element model of asphalt mixture is established, and non-uniform three-dimensional contact stress field data is applied as an external load to the surface asphalt mixture particles of the discrete element model to obtain the FEM-DEM coupled model. Based on the FEM-DEM coupled model, a dual-layer contact detection algorithm is used for simulation calculation to dynamically analyze the particle-scale response inside the asphalt mixture.

2. The method for simulating the particle size response of asphalt mixtures according to claim 1, characterized in that, The discrete element model uses irregularly shaped polyhedral particles to simulate the real form of asphalt mixtures, and the interaction between particles is described by a viscoelastic contact model to simulate the viscoelastic behavior of asphalt mixtures.

3. The method for simulating the particle size response of asphalt mixtures according to claim 2, characterized in that, The process of calculating the viscoelastic behavior of asphalt mixtures using the Burgers contact model includes: Dynamic modulus experiments were conducted on asphalt mixture samples to obtain their dynamic modulus and phase angle at different frequencies; Based on the analytical expression of complex compliance of the Burgers contact model, the calculated values ​​are matched with the experimental values ​​through a fitting algorithm, thereby calibrating the macroscopic model parameters. Based on macroscopic parameters and particle contact geometry information, the normal and tangential parameters of the microscopic contact of asphalt mixtures are calculated.

4. The method for simulating the particle size response of asphalt mixtures according to claim 3, characterized in that, The analytical expression for the complex compliance of the Burgers contact model is: in, For complex compliance, and These represent the stiffness and viscosity of the macroscopic Maxwell model, respectively. and These represent the stiffness and viscosity of the Kelvin-Voyt model, respectively. and They are respectively The real and imaginary parts, It represents angular frequency.

5. The method for simulating the particle size response of asphalt mixtures according to claim 1, characterized in that, The coupling process of the FEM-DEM coupled model includes: Contact detection is performed between the contact stress field nodes of the finite element model and the surface particles of the discrete element model to determine the particles corresponding to each stress field node. The contact force at each stress field node is applied to the center of inertia of the corresponding particle and converted into external force and torque acting on the particle.

6. The method for simulating the particle size response of asphalt mixtures according to claim 1, characterized in that, The dual-layer contact detection algorithm includes: Coarse detection based on bounding box algorithm is used to initially screen out particles that may come into contact with stress field nodes; For particles that have been roughly screened out, the cross product method is used for fine detection to accurately locate the particle surface where the stress field nodes are located.

7. The method for simulating the particle size response of asphalt mixtures according to claim 1, characterized in that, asphalt... The dynamic analysis process of particle size response within the mixture includes: The rolling process of a tire is simulated by moving the position of the contact stress field at a time step; By comparing the particle-scale response under different rolling speeds or different rolling conditions, the influence of tire motion state on the micromechanical behavior of asphalt mixtures is evaluated.

8. A particle-scale response simulation system for asphalt mixtures, characterized in that, include: The calculation module is used to build a finite element model of the tire and calculate the non-uniform three-dimensional contact stress field data of the tire on the road surface. The coupling module is used to establish a discrete element model of asphalt mixture. The non-uniform three-dimensional contact stress field data is used as an external load and applied to the surface asphalt mixture particles of the discrete element model to obtain the FEM-DEM coupled model. The analysis module is used to perform simulation calculations based on the FEM-DEM coupled model and the dual-layer contact detection algorithm to dynamically analyze the particle-scale response inside the asphalt mixture.

9. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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