Method for evaluating mechanical properties of asphalt mixture based on discrete element numerical simulation

Abstract

The invention provides an asphalt mixture mechanical property evaluation method based on discrete element numerical simulation, and relates to the technical field of road materials, and the method comprises the following steps: setting the unit radius and boundary unit radius of component particles of an asphalt mixture to be tested, adjusting the particle size distribution of the component particles and a contact model between different component particles, and calculating the mechanical property of the asphalt mixture to be tested; establishing an initial discrete element model; carrying out a semicircular bending test based on the initial discrete element model to obtain mesomechanical characteristic parameters of the to-be-tested asphalt mixture; sub-index matrixes corresponding to the damage dimension parameters, the force transmission dimension parameters and the structure dimension parameters are determined through an ideal solution sorting method, weighting is conducted on the sub-index matrixes in combination with an objective weighting method, and a comprehensive evaluation index is obtained through weighted fusion; determining the micro-mechanical properties of the to-be-tested asphalt mixture based on the comprehensive evaluation index; the sub-index matrix comprises a damage sub-index, a force transfer sub-index and a structure sub-index.

Description

Technical Field

[0001] This invention relates to the field of road materials technology, and in particular to a method for evaluating the mechanical properties of asphalt mixtures based on discrete element numerical simulation. Background Technology

[0002] Asphalt mixtures are the most critical pavement material in road engineering, and their mechanical properties directly determine the quality, durability, and safety of roads. During road operation, asphalt mixtures must withstand the repeated effects of vehicle loads, thermal expansion and contraction caused by temperature changes, and the combined effects of natural environmental factors such as rainwater erosion and ultraviolet radiation. Good mechanical properties ensure that asphalt pavements remain smooth and skid-resistant during long-term use, effectively resisting the occurrence and development of rutting, cracking, and other defects, thereby reducing road maintenance costs, extending road service life, and ensuring smooth and safe transportation. The mechanical properties of asphalt mixtures are closely related to their internal particle structure, force chain distribution, and bonding characteristics. Traditional methods for evaluating the mechanical properties of asphalt mixtures are mainly based on macroscopic mechanical indicators, such as compressive strength, low-temperature flexural strength, splitting tensile strength, and dynamic stability. These macroscopic indicators are obtained through standard laboratory tests, which are relatively simple to operate and can reflect, to a certain extent, the overall load-bearing capacity and deformation resistance of asphalt mixtures under different stress conditions.

[0003] However, these macroscopic evaluation methods have significant limitations. They can only provide a rough assessment of the overall mechanical properties of the mixture, failing to reveal the in-depth microscopic evolution mechanism of the mixture's internal structure. In actual engineering, the failure of asphalt mixtures often does not stem from uniform failure of the entire material, but rather from the gradual expansion of damage to localized internal structures. Macroscopic indicators struggle to capture this gradual process from microstructural damage to macroscopic failure, thus failing to accurately quantify key microscopic information such as interparticle contact behavior, force chain load-bearing capacity, and crack propagation paths. Furthermore, the mechanical properties of asphalt mixtures are the result of the combined effects of multiple microscopic factors, and a single indicator often cannot comprehensively and accurately reflect the true mechanical state of the mixture. The inability to accurately obtain the mechanical properties of asphalt mixtures makes precise control over pavement operation and maintenance difficult, thereby affecting pavement service life, maintenance costs, and safety. Summary of the Invention

[0004] In view of this, the present invention proposes a method for evaluating the mechanical properties of asphalt mixtures based on discrete element numerical simulation.

[0005] The technical solution of this invention is implemented as follows: The first aspect of this invention provides a method for evaluating the mechanical properties of asphalt mixtures based on discrete element numerical simulation, comprising: Set the element radius and boundary element radius of the component particles of the asphalt mixture to be tested, adjust the particle size distribution of the component particles and the contact model between different component particles, and establish the initial discrete element model. A semi-circular bending test was conducted based on the initial discrete element model to obtain the micromechanical property parameters of the asphalt mixture to be tested; the micromechanical property parameters include damage dimension parameters, force transmission dimension parameters and structural dimension parameters. The damage dimension parameters, force transmission dimension parameters, and structural dimension parameters are determined using the ideal solution ranking method, and the sub-index matrices corresponding to these parameters are obtained. An objective weighting method is then used to assign weights to each sub-index matrix, and a comprehensive evaluation index is obtained through weighted fusion. The micromechanical properties of the asphalt mixture under test are determined based on the comprehensive evaluation index. The sub-index matrix includes damage sub-index, force transmission sub-index, and structural sub-index.

[0006] Based on the above technical solutions, preferably, the component particles include aggregate particles and asphalt mastic particles; the step of setting the element radius and boundary element radius of the component particles of the asphalt mixture to be tested, adjusting the particle size distribution of the component particles and the contact model between different component particles, and establishing an initial discrete element model includes: According to the gradation requirements, aggregate particles and asphalt mortar particles are randomly generated in the space of a pre-set semi-circular specimen; the aggregate particles are represented by irregular polygonal particle clusters, and the asphalt mortar particles are represented by uniformly sized spheres; the contact model between the aggregate particles adopts the contact stiffness model, and the contact model between the aggregate particles and the asphalt mortar particles adopts the parallel bonding model.

[0007] Based on the above technical solutions, preferably, the damage dimension parameters include the bonding failure ratio, fracture energy accumulation, and fracture energy; the force transmission dimension parameters include the force chain variation coefficient, the average force chain length, and the proportion of high-force contact tails; and the structural dimension parameters include the contact anisotropy coefficient, the average length of strong force chains, and the proportion of strong contacts.

[0008] Based on the above technical solutions, preferably, the step of conducting a semi-circular bending test based on the initial discrete element model to obtain the micromechanical property parameters of the asphalt mixture to be tested includes: The bond failure ratio is determined by the proportion of bonds that fail to the total number of bonds. The energy released by multiple bond failures is summed to determine the fracture energy accumulation. The fracture energy is obtained by integrating the loading reaction force and loading displacement. The coefficient of variation of the force chain is determined based on the standard deviation of the force chain strength and the average strength of the force chain. The average length of the force chain is obtained by averaging the lengths of all force chains. The proportion of high-force contact tails is determined based on the proportion of the number of contacts with a high force threshold in the total number of contacts. The contact anisotropy coefficient is calculated based on the principal value of the contact texture tensor. The average length of the strong chains is obtained by averaging the lengths of all strong chains. The proportion of strong contacts is determined based on the ratio of the number of strong contacts to the total number of contacts.

[0009] Based on the above technical solutions, preferably, the step of determining the damage dimension parameters using the ideal solution sorting method, and the sub-index matrices corresponding to the force transmission dimension parameters and the structural dimension parameters respectively, includes: Obtain the original parameter matrix of each parameter in the micromechanical property parameters, and perform standardization processing on the original parameter matrix to obtain the corresponding standardized matrix; Based on the positive and negative ideal values ​​corresponding to the normalized matrix, the distance between each parameter in the normalized matrix and the positive ideal solution and the negative ideal solution is determined, resulting in a positive distance matrix and a negative distance matrix; the positive ideal value is the maximum value of the normalized parameter in the matrix column, and the negative ideal value is the minimum value of the normalized parameter in the matrix column; The sub-index matrix of each parameter in the micromechanical property parameters is calculated based on the positive distance matrix and the negative distance matrix.

[0010] Based on the above technical solutions, preferably, the step of determining the distance between each parameter in the standardized matrix and the positive ideal solution and the negative ideal solution, based on the positive and negative ideal values ​​corresponding to the standardized matrix, to obtain the positive distance matrix and the negative distance matrix, includes: The distance between each parameter in the normalized matrix and the positive ideal solution and the negative ideal solution is calculated using Euclidean distance, resulting in the positive distance matrix and the negative distance matrix.

[0011] Based on the above technical solutions, preferably, the step of combining the objective weighting method to assign weights to each sub-index matrix and obtaining a comprehensive evaluation index through weighted fusion includes: Obtain the standard deviation of all sub-indices in each column of the sub-index matrix to obtain the standard deviation vector, and calculate the correlation coefficient between any two sub-indices in the sub-index matrix to obtain the correlation coefficient matrix; The contrast intensity value of each sub-index is determined based on the standard deviation vector and the correlation coefficient matrix; The contrast intensity values ​​are normalized to obtain the weights corresponding to each sub-index. Based on the weights, the sub-index matrices are weighted and fused to obtain the comprehensive evaluation index.

[0012] Furthermore, a second aspect of the present invention provides a system for evaluating the mechanical properties of asphalt mixtures based on discrete element numerical simulation, comprising: a model creation module, a parameter acquisition module, and a weighted fusion module; wherein, The model creation module is configured to set the unit radius and boundary unit radius of the component particles of the asphalt mixture to be tested, adjust the particle size distribution of the component particles and the contact model between different component particles, and establish an initial discrete element model. The parameter acquisition module is configured to perform a semi-circular bending test based on the initial discrete element model to obtain the micromechanical property parameters of the asphalt mixture to be tested; the micromechanical property parameters include damage dimension parameters, force transmission dimension parameters and structural dimension parameters. The weighted fusion module is configured to determine the damage dimension parameters, the sub-index matrices corresponding to the force transmission dimension parameters and the structural dimension parameters using the ideal solution sorting method, and to assign weights to each sub-index matrix using the objective weighting method, thereby obtaining a comprehensive evaluation index through weighted fusion; and to determine the micromechanical properties of the asphalt mixture to be tested based on the comprehensive evaluation index; the sub-index matrix includes damage sub-index, force transmission sub-index and structural sub-index.

[0013] More preferably, a third aspect of the present invention provides an electronic device, including a processor and a memory; the memory stores a computer program, wherein the computer program, when executed by the processor, implements the method for evaluating the mechanical properties of asphalt mixtures based on discrete element numerical simulation as described in the first aspect.

[0014] More preferably, a fourth aspect of the present invention provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method for evaluating the mechanical properties of asphalt mixtures based on discrete element numerical simulation as described in the first aspect.

[0015] The method for evaluating the mechanical properties of asphalt mixtures based on discrete element numerical simulation of the present invention has the following advantages over the prior art: 1. By comprehensively considering the microscopic parameters of three dimensions—damage, force transmission, and structure—corresponding sub-index matrices were determined, including damage sub-index, force transmission sub-index, and structure sub-index. These three dimensions reflect the internal mechanical properties of the mixture from different perspectives: the damage dimension focuses on structural damage, the force transmission dimension emphasizes force transmission and load-bearing capacity, and the structure dimension focuses on the overall structural stability. A comprehensive evaluation index is obtained by weighted fusion of the sub-index matrices. This comprehensive and systematic consideration of the influence of multiple microscopic factors on the mechanical properties of the mixture avoids the one-sidedness of single-index evaluation, thus more accurately reflecting the true mechanical state of the asphalt mixture under test.

[0016] 2. The sub-index matrix corresponding to each micromechanical property parameter is determined by the ideal solution sorting method, and the weights of each sub-index matrix are assigned by the objective weighting method. Finally, the comprehensive evaluation index is obtained by weighted fusion. The weights can be automatically calculated according to the degree of variation and correlation of the index data itself, avoiding the arbitrariness of subjective weighting, making the weight allocation more scientific and reasonable, and thus more reliably reflecting the micromechanical properties of the asphalt mixture to be tested. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart illustrating a method for evaluating the mechanical properties of asphalt mixtures based on discrete element numerical simulation, provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of a mechanical property evaluation system for asphalt mixtures based on discrete element numerical simulation, provided in an embodiment of the present invention. Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0019] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0020] In some embodiments, such as Figure 1 As shown, Figure 1 This is a flowchart illustrating a method for evaluating the mechanical properties of asphalt mixtures based on discrete element numerical simulation, provided by an embodiment of the present invention. The method includes: S110: Set the element radius and boundary element radius of the component particles of the asphalt mixture to be tested, adjust the particle size distribution of the component particles and the contact model between different component particles, and establish the initial discrete element model.

[0021] In this embodiment, the mixture is decomposed into multiple particles of different components, each particle being considered a rigid or soft unit. A contact model is used to simulate adhesion and friction behavior. The contact forces between particles form a force chain network, and the distribution density, topology, and load-bearing efficiency of these force chains directly affect the overall mechanical response of the mixture. By adjusting particle parameters, such as radius, distribution, and connectivity, structural characteristics such as porosity and aggregate interlocking degree within the mixture can be controlled, thereby influencing macroscopic properties such as strength and deformation characteristics.

[0022] In some embodiments, the component particles include aggregate particles and asphalt mastic particles; the element radius and boundary element radius of the component particles of the asphalt mixture to be tested are set, the particle size distribution of the component particles and the contact model between different component particles are adjusted, and an initial discrete element model is established, including: According to the gradation requirements, aggregate particles and asphalt mortar particles are randomly generated in the space of the pre-set semi-circular specimen; aggregate particles are represented by irregular polygonal particle clusters, and asphalt mortar particles are represented by uniformly sized spheres; the contact model between aggregate particles adopts the contact stiffness model, and the contact model between aggregate particles and asphalt mortar particles adopts the parallel bonding model.

[0023] For example, a computational domain is created using a discrete element method (DEM), within which a semi-circular specimen space with a diameter of 100 mm is generated. Within this semi-circular space, particles are randomly generated according to gradation requirements. Aggregate particles are represented by irregular polygonal particle clusters (clump), and asphalt mastic particles are represented by uniformly sized spheres. Some asphalt mastic particles are randomly deleted to achieve the target porosity. Circular walls are created at the top and bottom of the specimen to simulate the indenter and support.

[0024] S120, based on the initial discrete element model, a semi-circular bending test was conducted to obtain the micromechanical property parameters of the asphalt mixture to be tested; the micromechanical property parameters include damage dimension parameters, force transmission dimension parameters and structural dimension parameters.

[0025] In this embodiment, a semi-circular bending test is conducted based on an initial discrete element model to obtain the fracture energy, a key mechanical property parameter. For example, a downward velocity of 0.015 mm / min is applied to the top wall to simulate loading; the bottom wall of the specimen is fixed as a support, restricting its displacement and rotational degrees of freedom to maintain stability during loading. The bottom wall is fixed as a support with a support spacing of 0.8D, and the virtual test temperature is set to −10℃ to simulate the brittle failure behavior of asphalt mixtures under low-temperature conditions. After loading, the micromechanical property parameters of the asphalt mixture under test are extracted using the FISH script in the discrete element software.

[0026] In some embodiments, the damage dimension parameters include the bond failure ratio, fracture energy accumulation, and fracture energy; the force transmission dimension parameters include the force chain variation coefficient, the average force chain length, and the proportion of high-force contact tails; and the structural dimension parameters include the contact anisotropy coefficient, the average length of strong force chains, and the proportion of strong contacts.

[0027] In some embodiments, a semi-circular bending test is conducted based on an initial discrete element model to obtain the micromechanical property parameters of the asphalt mixture under test, including: The bond failure ratio is determined by the proportion of bonds that fail to the total number of bonds. The energy released by multiple bond failures is summed to determine the fracture energy accumulation. The fracture energy is obtained by integrating the loading reaction force and loading displacement. The coefficient of variation of the force chain is determined based on the standard deviation of the force chain strength and the average strength of the force chain. The average length of the force chain is obtained by averaging the lengths of all force chains. The proportion of high-force contact tails is determined based on the proportion of the number of contacts with a high force threshold in the total number of contacts. The contact anisotropy coefficient is calculated based on the principal value of the contact texture tensor. The average length of the strong chains is obtained by averaging the lengths of all strong chains. The proportion of strong contacts is determined based on the ratio of the number of strong contacts to the total number of contacts.

[0028] In this embodiment, the bond failure ratio is used to characterize the degree of microscopic bond failure, and its calculation formula is as follows: ; in, For the total amount of adhesive, The amount of adhesive that failed.

[0029] Fracture energy accumulation is used to characterize the temporal growth of energy during the failure process, and its calculation formula is as follows: ; in, The energy released during the i-th bond failure.

[0030] Fracture energy is used to characterize the total energy absorbed by a specimen during loading and failure. Its calculation formula is as follows: ; in, To apply reaction force, To apply displacement.

[0031] The force chain variation coefficient is used to characterize the uniformity of contact force distribution, and its calculation formula is as follows: ; in, The standard deviation of the force chain strength, , The average strength of the force chain.

[0032] The average force chain length is used to reflect the integrity of the force chain structure, and its calculation formula is as follows: ; in, For the number of force chains, Let be the length of the i-th force chain.

[0033] The proportion of high-strength contact tails is used to reflect the proportion of high-strength contacts in the overall contact network, and its calculation formula is as follows: ; in, For high force threshold, This represents the total number of contacts.

[0034] The contact anisotropy coefficient is calculated based on the principal values ​​of the contact texture tensor and is defined as follows: ; in, , The two principal values ​​of the contact texture tensor are given by the textural tensor, which is defined as follows: , Let be the component of the unit vector of the i-th contact normal. It is the tensor product.

[0035] The average length of the strong load chain is used to characterize the continuity of the strong load path, and its calculation formula is as follows: ; in, The number of strong chains.

[0036] The percentage of strong contact is used to characterize the concentration of strong load transfer, and its calculation formula is as follows: ; in, For high contact quantity, This represents the total number of contacts.

[0037] S130, the sub-index matrices corresponding to the damage dimension parameters, force transmission dimension parameters and structural dimension parameters are determined by the ideal solution sorting method, and the sub-index matrices are weighted by the objective weighting method. The comprehensive evaluation index is obtained by weighted fusion. The micromechanical properties of the asphalt mixture to be tested are determined based on the comprehensive evaluation index. The sub-index matrix includes damage sub-index, force transmission sub-index and structural sub-index.

[0038] In some embodiments, the ideal solution sorting method is used to determine the damage dimension parameters, the force transmission dimension parameters, and the structural dimension parameters, respectively, and their corresponding sub-index matrices: Obtain the original parameter matrix of each parameter in the micromechanical property parameters, and perform standardization processing on the original parameter matrix to obtain the corresponding standardized matrix; Based on the positive and negative ideal values ​​corresponding to the normalized matrix, the distance between each parameter in the normalized matrix and the positive ideal solution and the negative ideal solution is determined, resulting in the positive distance matrix and the negative distance matrix; the positive ideal value is the maximum value of the normalized parameter in the matrix column, and the negative ideal value is the minimum value of the normalized parameter in the matrix column; The sub-index matrix of each parameter in the micromechanical property parameters is calculated based on the positive distance matrix and the negative distance matrix.

[0039] In this embodiment, the original parameter matrices corresponding to the micromechanical property parameters under the damage dimension, force transmission dimension, and structural dimension are obtained respectively. Each parameter in the original parameter matrix is ​​then standardized sequentially to obtain a standardized matrix. The standardization process includes processing each column of data using a vector normalization method, ensuring that the sum of the squares of all elements in each column of the standardized matrix is ​​1. Based on this, the positive and negative ideal values ​​corresponding to each column of parameters in the standardized matrix are determined. Based on the positive and negative ideal values, the distances between each parameter in the standardized matrix and the positive and negative ideal solutions are calculated, resulting in positive and negative distance matrices. Based on the positive and negative distance matrices, the sub-index corresponding to each micromechanical parameter is calculated, resulting in a sub-index matrix.

[0040] In some embodiments, based on the positive and negative ideal values ​​corresponding to the normalized matrix, the distance between each parameter in the normalized matrix and the positive ideal solution and the distance between each parameter and the negative ideal solution are determined, resulting in a positive distance matrix and a negative distance matrix, including: The distance between each parameter in the normalized matrix and the positive ideal solution and the negative ideal solution is calculated using Euclidean distance, thus obtaining the positive distance matrix and the negative distance matrix.

[0041] In this embodiment, the distance between each parameter in the normalized matrix and the positive ideal solution can be expressed as: ; The distance between each parameter in the normalized matrix and the positive ideal solution can be expressed as: ; in, The parameters in the standardized matrix, For a positive ideal value, It is a negative ideal value.

[0042] Sub-indices are determined by the following formula: ; The initial proximity score, representing the proximity of the i-th sample, is a sub-index. The value ranges from 0 to 1, and is used to characterize the performance level of various micromechanical indicators. The larger the value, the better the micromechanical properties of the asphalt mixture under test in this dimension.

[0043] In some embodiments, the sub-index matrices are weighted using an objective weighting method, and a comprehensive evaluation index is obtained through weighted fusion, including: Obtain the standard deviation of all sub-indices in each column of the sub-index matrix to get the standard deviation vector, and calculate the correlation coefficient between any two sub-indices in the sub-index matrix to get the correlation coefficient matrix; The contrast intensity value of each sub-index is determined based on the standard deviation vector and the correlation coefficient matrix; The contrast intensity values ​​are normalized to obtain the weights corresponding to each sub-index. Based on the weights, the sub-index matrices are weighted and fused to obtain the comprehensive evaluation index.

[0044] Here, the parameter contrast strength is calculated based on the CRITIC (Criteria Importance Through Intercriteria Correlation) method: ; Let j be the contrast intensity of the j-th parameter. Let j be the standard deviation of the j-th parameter. Let be the correlation coefficient between parameter j and parameter k, and m be the total number of parameters.

[0045] Normalize the contrast intensity to obtain objective weights: ; The overall evaluation index is: .

[0046] In an optional embodiment, taking AC-16 type warm-mix steel slag asphalt as a binder as an example, steel slag is used as coarse aggregate, asphalt as a binder, and SDYK warm-mix agent is added. The freeze-thaw cycle conditions are as follows: first, the specimens are vacuum-saturated in a 0% (clean water) and 8% salt solution (maintained at a vacuum of 97.3 kPa for 15 min), and then soaked for another 1 h after returning to normal pressure. A freeze-thaw cycle is defined as freezing at -20℃ for 8 h and thawing at 60℃ for 16 h, with the number of cycles set to 5 and 20. Based on the AC-16 gradation curve, steel slag aggregate clusters with irregular geometric shapes are generated using the "clump" method; particles are randomly filled in a two-dimensional space to form a semi-circular specimen with a diameter of 100 mm. Particles with a diameter greater than 2.36 mm are defined as steel slag aggregate clusters and given a contact stiffness of 55 GPa to simulate the high strength characteristics of steel slag aggregate. The remaining areas are filled with asphalt mortar spheres composed of asphalt powder, warm mix additives, and fine aggregates.

[0047] A linear parallel bond model was used for the interior of the asphalt mortar and the aggregate-mortar interface. The interfacial bond strength and critical displacement parameters were differentiated based on the number of freeze-thaw cycles and the salt solution concentration to reflect the influence of freeze-thaw cycles and salt solution on the interfacial fracture energy. A fixed constraint was applied to the bottom of the model; a constant displacement rate of 0.005 mm / min was applied to the top, and the test ended when the axial strain reached 5%. The stress-strain response and microscopic damage evolution process were recorded during the calculation. The calculation results of the microscopic mechanical properties are shown in Table 1.

[0048] Table 1 Calculation results of micromechanical property parameters The corresponding sub-index calculation results are shown in Table 2: Table 2 Sub-index Calculation Results The weight calculation results for each sub-index are shown in Table 3: Table 3 Sub-index Weights The comprehensive evaluation index under different freeze-thaw cycles and salt solution immersion conditions is shown in Table 4: Table 4. Comprehensive evaluation index under different freeze-thaw cycles and salt solution immersion conditions The larger the value, the better the micromechanical properties of the asphalt mixture.

[0049] In some embodiments, please refer to Figure 2 , Figure 2This is a schematic diagram of a mechanical property evaluation system for asphalt mixtures based on discrete element numerical simulation, provided in an embodiment of the present invention. The present invention provides a mechanical property evaluation system 200 for asphalt mixtures based on discrete element numerical simulation, comprising: a model creation module 210, a parameter acquisition module 220, and a weighted fusion module 230; wherein,

[0050] The model creation module 210 is configured to set the element radius and boundary element radius of the component particles of the asphalt mixture to be tested, adjust the particle size distribution of the component particles and the contact model between different component particles, and establish an initial discrete element model. The parameter acquisition module 220 is configured to conduct a semi-circular bending test based on the initial discrete element model to obtain the micromechanical property parameters of the asphalt mixture to be tested; the micromechanical property parameters include damage dimension parameters, force transmission dimension parameters and structural dimension parameters; The weighted fusion module 230 is configured to use the ideal solution sorting method to determine the sub-index matrices corresponding to the damage dimension parameters, force transmission dimension parameters and structural dimension parameters, and to combine the objective weighting method to assign weights to each sub-index matrix, and obtain the comprehensive evaluation index through weighted fusion; the micromechanical properties of the asphalt mixture to be tested are determined based on the comprehensive evaluation index; the sub-index matrix includes damage sub-index, force transmission sub-index and structural sub-index.

[0051] In some embodiments, the component particles include aggregate particles and asphalt mastic particles; the model creation module 210 is specifically configured as follows: According to the gradation requirements, aggregate particles and asphalt mortar particles are randomly generated in the space of the pre-set semi-circular specimen; aggregate particles are represented by irregular polygonal particle clusters, and asphalt mortar particles are represented by uniformly sized spheres; the contact model between aggregate particles adopts the contact stiffness model, and the contact model between aggregate particles and asphalt mortar particles adopts the parallel bonding model.

[0052] In some embodiments, the damage dimension parameters include the bond failure ratio, fracture energy accumulation, and fracture energy; the force transmission dimension parameters include the force chain variation coefficient, the average force chain length, and the proportion of high-force contact tails; and the structural dimension parameters include the contact anisotropy coefficient, the average length of strong force chains, and the proportion of strong contacts.

[0053] In some embodiments, the parameter acquisition module 220 is specifically configured as follows: The bond failure ratio is determined by the proportion of bonds that fail to the total number of bonds. The energy released by multiple bond failures is summed to determine the fracture energy accumulation. The fracture energy is obtained by integrating the loading reaction force and loading displacement. The coefficient of variation of the force chain is determined based on the standard deviation of the force chain strength and the average strength of the force chain. The average length of the force chain is obtained by averaging the lengths of all force chains. The proportion of high-force contact tails is determined based on the proportion of the number of contacts with a high force threshold in the total number of contacts. The contact anisotropy coefficient is calculated based on the principal value of the contact texture tensor. The average length of the strong chains is obtained by averaging the lengths of all strong chains. The proportion of strong contacts is determined based on the ratio of the number of strong contacts to the total number of contacts.

[0054] In some embodiments, the weighted fusion module 230 is specifically configured as follows: Obtain the original parameter matrix of each parameter in the micromechanical property parameters, and perform standardization processing on the original parameter matrix to obtain the corresponding standardized matrix; Based on the positive and negative ideal values ​​corresponding to the normalized matrix, the distance between each parameter in the normalized matrix and the positive ideal solution and the negative ideal solution is determined, resulting in the positive distance matrix and the negative distance matrix; the positive ideal value is the maximum value of the normalized parameter in the matrix column, and the negative ideal value is the minimum value of the normalized parameter in the matrix column; The sub-index matrix of each parameter in the micromechanical property parameters is calculated based on the positive distance matrix and the negative distance matrix.

[0055] In some embodiments, the weighted fusion module 230 is specifically configured as follows: The distance between each parameter in the normalized matrix and the positive ideal solution and the negative ideal solution is calculated using Euclidean distance, thus obtaining the positive distance matrix and the negative distance matrix.

[0056] In some embodiments, the weighted fusion module 230 is specifically configured as follows: Obtain the standard deviation of all sub-indices in each column of the sub-index matrix to get the standard deviation vector, and calculate the correlation coefficient between any two sub-indices in the sub-index matrix to get the correlation coefficient matrix; The contrast intensity value of each sub-index is determined based on the standard deviation vector and the correlation coefficient matrix; The contrast intensity values ​​are normalized to obtain the weights corresponding to each sub-index. Based on the weights, the sub-index matrices are weighted and fused to obtain the comprehensive evaluation index.

[0057] It should be noted that the mechanical property evaluation system for asphalt mixtures based on discrete element numerical simulation provided in this application embodiment and the mechanical property evaluation method for asphalt mixtures based on discrete element numerical simulation provided in this application embodiment are based on the same application concept. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned mechanical property evaluation method for asphalt mixtures based on discrete element numerical simulation, and the repeated parts will not be described again.

[0058] In some embodiments, please refer to Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device 300 provided in this embodiment includes a processor 310 and a memory 320; the memory 320 stores a computer program, wherein the computer program, when executed by the processor, implements the aforementioned method for evaluating the mechanical properties of asphalt mixtures based on discrete element numerical simulation.

[0059] Specifically, processor 310 may include, for example, a general-purpose microprocessor, an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. Processor 310 may also include onboard memory for caching purposes. Processor 310 may be a single processing unit or multiple processing units for performing different actions of the method flow according to embodiments of this application.

[0060] The memory 320 may be any medium capable of containing, storing, transmitting, propagating, or transmitting instructions. For example, the memory 320 may include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, apparatuses, or propagation media. Specific examples of the memory 320 include: magnetic storage devices such as magnetic tape or hard disk drives (HDDs); optical storage devices such as optical discs (CD-ROMs); and may also be random access memory (RAM) or flash memory; and / or wired / wireless communication links.

[0061] This application also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, this program implements the aforementioned method for evaluating the mechanical properties of asphalt mixtures based on discrete element numerical simulation. This computer-readable medium may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into that device / apparatus / system. The aforementioned computer-readable medium carries one or more programs, which, when executed, implement the method according to the embodiments of this application.

[0062] According to embodiments of this application, a computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium 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 or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wired, optical fiber, radio frequency signals, etc., or any suitable combination thereof.

[0063] Those skilled in the art will understand that the features described in the various embodiments and / or claims of this application can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in this application. In particular, the features described in the various embodiments and / or claims of this application can be combined and / or combined in various ways without departing from the spirit and teachings of this application. All such combinations and / or combinations fall within the scope of this application. Therefore, the scope of this application should not be limited to the above embodiments, but should be defined not only by the appended claims, but also by their equivalents. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this invention should be included within the protection scope of this invention.

Claims

1. A method for evaluating the mechanical properties of asphalt mixtures based on discrete element numerical simulation, characterized in that, include: Set the element radius and boundary element radius of the component particles of the asphalt mixture to be tested, adjust the particle size distribution of the component particles and the contact model between different component particles, and establish the initial discrete element model. A semi-circular bending test was conducted based on the initial discrete element model to obtain the micromechanical property parameters of the asphalt mixture to be tested; the micromechanical property parameters include damage dimension parameters, force transmission dimension parameters and structural dimension parameters. The damage dimension parameters, force transmission dimension parameters, and structural dimension parameters are determined using the ideal solution ranking method, and the sub-index matrices corresponding to these parameters are obtained. An objective weighting method is then used to assign weights to each sub-index matrix, and a comprehensive evaluation index is obtained through weighted fusion. The micromechanical properties of the asphalt mixture under test are determined based on the comprehensive evaluation index. The sub-index matrix includes damage sub-index, force transmission sub-index, and structural sub-index.

2. The method for evaluating the mechanical properties of asphalt mixtures based on discrete element numerical simulation as described in claim 1, characterized in that, The component particles include aggregate particles and asphalt mastic particles; the process of setting the element radius and boundary element radius of the component particles of the asphalt mixture to be tested, adjusting the particle size distribution of the component particles and the contact model between different component particles, and establishing an initial discrete element model includes: According to the gradation requirements, aggregate particles and asphalt mortar particles are randomly generated in the space of a pre-set semi-circular specimen; the aggregate particles are represented by irregular polygonal particle clusters, and the asphalt mortar particles are represented by uniformly sized spheres; the contact model between the aggregate particles adopts the contact stiffness model, and the contact model between the aggregate particles and the asphalt mortar particles adopts the parallel bonding model.

3. The method for evaluating the mechanical properties of asphalt mixtures based on discrete element numerical simulation as described in claim 1, characterized in that, The damage dimension parameters include the proportion of bond failure, fracture energy accumulation, and fracture energy; the force transmission dimension parameters include the force chain variation coefficient, the average force chain length, and the proportion of high-force contact tails; and the structural dimension parameters include the contact anisotropy coefficient, the average length of strong force chains, and the proportion of strong contacts.

4. The method for evaluating the mechanical properties of asphalt mixtures based on discrete element numerical simulation as described in claim 3, characterized in that, The semi-circular bending test based on the initial discrete element model is used to obtain the micromechanical property parameters of the asphalt mixture under test, including: The bond failure ratio is determined by the proportion of bonds that fail to the total number of bonds. The energy released by multiple bond failures is summed to determine the fracture energy accumulation. The fracture energy is obtained by integrating the loading reaction force and loading displacement. The coefficient of variation of the force chain is determined based on the standard deviation of the force chain strength and the average strength of the force chain. The average length of the force chain is obtained by averaging the lengths of all force chains. The proportion of high-force contact tails is determined based on the proportion of the number of contacts with a high force threshold in the total number of contacts. The contact anisotropy coefficient is calculated based on the principal value of the contact texture tensor. The average length of the strong chains is obtained by averaging the lengths of all strong chains. The proportion of strong contacts is determined based on the ratio of the number of strong contacts to the total number of contacts.

5. The method for evaluating the mechanical properties of asphalt mixtures based on discrete element numerical simulation as described in claim 1, characterized in that, The method of determining the damage dimension parameters using the ideal solution sorting method, and the sub-index matrices corresponding to the force transmission dimension parameters and the structural dimension parameters respectively, include: Obtain the original parameter matrix of each parameter in the micromechanical property parameters, and perform standardization processing on the original parameter matrix to obtain the corresponding standardized matrix; Based on the positive and negative ideal values ​​corresponding to the normalized matrix, the distance between each parameter in the normalized matrix and the positive ideal solution and the negative ideal solution is determined, resulting in a positive distance matrix and a negative distance matrix; the positive ideal value is the maximum value of the normalized parameter in the matrix column, and the negative ideal value is the minimum value of the normalized parameter in the matrix column; The sub-index matrix of each parameter in the micromechanical property parameters is calculated based on the positive distance matrix and the negative distance matrix.

6. The method for evaluating the mechanical properties of asphalt mixtures based on discrete element numerical simulation as described in claim 5, characterized in that, The step of determining the distance between each parameter in the standardized matrix and the positive ideal solution and the negative ideal solution, based on the positive and negative ideal values ​​corresponding to the standardized matrix, to obtain the positive distance matrix and the negative distance matrix, includes: The distance between each parameter in the normalized matrix and the positive ideal solution and the negative ideal solution is calculated using Euclidean distance, resulting in the positive distance matrix and the negative distance matrix.

7. The method for evaluating the mechanical properties of asphalt mixtures based on discrete element numerical simulation as described in claim 1, characterized in that, The method of combining objective weighting to assign weights to each sub-index matrix, and obtaining a comprehensive evaluation index through weighted fusion, includes: Obtain the standard deviation of all sub-indices in each column of the sub-index matrix to obtain the standard deviation vector, and calculate the correlation coefficient between any two sub-indices in the sub-index matrix to obtain the correlation coefficient matrix; The contrast intensity value of each sub-index is determined based on the standard deviation vector and the correlation coefficient matrix; The contrast intensity values ​​are normalized to obtain the weights corresponding to each sub-index. Based on the weights, the sub-index matrices are weighted and fused to obtain the comprehensive evaluation index.

8. A mechanical property evaluation system for asphalt mixtures based on discrete element numerical simulation, characterized in that, include: The module includes a model creation module, a parameter acquisition module, and a weighted fusion module; among them, The model creation module is configured to set the unit radius and boundary unit radius of the component particles of the asphalt mixture to be tested, adjust the particle size distribution of the component particles and the contact model between different component particles, and establish an initial discrete element model. The parameter acquisition module is configured to perform a semi-circular bending test based on the initial discrete element model to obtain the micromechanical property parameters of the asphalt mixture to be tested; the micromechanical property parameters include damage dimension parameters, force transmission dimension parameters and structural dimension parameters. The weighted fusion module is configured to determine the damage dimension parameters, the sub-index matrices corresponding to the force transmission dimension parameters and the structural dimension parameters using the ideal solution sorting method, and to assign weights to each sub-index matrix using the objective weighting method, thereby obtaining a comprehensive evaluation index through weighted fusion; and to determine the micromechanical properties of the asphalt mixture to be tested based on the comprehensive evaluation index; the sub-index matrix includes damage sub-index, force transmission sub-index and structural sub-index.

9. An electronic device comprising a processor and a memory; said memory storing a computer program, wherein, When the computer program is executed by the processor, it implements the method for evaluating the mechanical properties of asphalt mixtures based on discrete element numerical simulation as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that, It stores a computer program, wherein when the computer program is executed by a processor, it implements the method for evaluating the mechanical properties of asphalt mixtures based on discrete element numerical simulation as described in any one of claims 1 to 7.

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