Thermal recycled asphalt mixture functional reinforcement phase optimization design method based on discrete element simulation

Abstract

The invention discloses a thermal regeneration asphalt mixture functional reinforcement phase optimization design method based on discrete element simulation in the technical field of thermal regeneration road engineering material optimization, and the method comprises the steps: constructing a discrete element model of an asphalt mixture, extracting skeleton gap characteristic parameters, including the skeleton gap size, the volume ratio and the distribution condition, and obtaining a discrete element model of the asphalt mixture; according to the optimization design method, the mixing amount, the diameter range and the length parameters of the functional reinforcing material are optimized according to the characteristic parameters, the blindness of a traditional experiment depending on experience is avoided, and the design efficiency and performance of the functional asphalt mixture are improved. According to the method, the microstructure characteristics of the thermally recycled asphalt mixture are accurately quantified through the discrete element technology, the correlation model of the functional reinforced phase parameters and the skeleton gaps is established, the problems that a traditional test depends on experience and is low in efficiency are solved, and a high-performance material solution is provided for a functional asphalt pavement.

Description

Technical Field

[0001] The present invention relates to the technical field of optimized thermal regeneration road engineering materials, and particularly to an optimized design method for functional enhancement phases of recycled asphalt mixtures based on discrete element simulation, which is used to improve the functionality and mechanical properties of recycled asphalt mixtures. Background Art

[0002] Recycled asphalt mixtures achieve resource recycling by recovering asphalt pavement materials (RAP). However, during the recycling process, problems such as aging of the asphalt film on the surface of old aggregates, poor compatibility between new and old asphalt, and deterioration of the skeleton structure exist, resulting in a decline in functional properties such as crack resistance and durability of the mixture.

[0003] Currently, for the functional enhancement design of recycled asphalt mixtures (such as microcapsule self-healing agents, carbon nanotubes, etc.), it still relies on empirical tests and lacks quantitative analysis of the distribution laws of skeleton gaps and enhancement phases in the mesoscopic structure of recycled materials. For example, changes in the surface roughness of recycled aggregates may affect the interlocking effect of microcapsules, and differences in the residual viscosity of old asphalt may hinder the dispersion of carbon nanotubes. Traditional methods are difficult to dynamically adjust the adaptability between enhancement phase parameters and the mesoscopic structure of recycled mixtures. In addition, existing discrete element simulation technologies mostly focus on ordinary asphalt mixtures and have not been used to analyze the correlation between enhancement phases and skeletons in recycled materials, resulting in low design efficiency and difficulty in synergistically optimizing functional and mechanical properties. Therefore, there is an urgent need for a design method based on quantitative analysis of mesoscopic structures to break through the technical bottlenecks in the optimization of functional enhancement phases of recycled asphalt mixtures. Summary of the Invention

[0004] The purpose of the present invention is to overcome the defects in the prior art and provide an optimized design method for functional enhancement phases of recycled asphalt mixtures based on discrete element simulation. By constructing a discrete element model of asphalt mixtures, characteristic parameters of skeleton gaps are extracted, such as size, volume ratio, and distribution, and based on these characteristic parameters of skeleton gaps, parameters such as the dosage, diameter range, and length of functional enhancement phase materials are optimized, avoiding the blindness of traditional tests and significantly improving the design efficiency and performance of functional asphalt mixtures.

[0005] The purpose of the present invention is achieved as follows: An optimized design method for functional enhancement phases of recycled asphalt mixtures based on discrete element simulation includes the following steps:

[0006] Step 1, construct a two-dimensional discrete element model of recycled asphalt mixture:

[0007] (1) Coarse aggregate image acquisition and processing: Use a digital camera with a resolution of not less than 1200×1024 to take images of the coarse aggregates of recycled asphalt mixtures, and the image bit depth is 2 24To ensure high definition and fast processing; perform grayscale conversion, noise reduction, and binarization processing through MATLAB to extract the two-dimensional surface contour model of the recycled aggregate in STL format; regarding the influence of the aged asphalt film on the old aggregate surface on contour extraction, use the adaptive threshold segmentation method to optimize edge recognition;

[0008] (2) Extract contour points and generate the STL model:

[0009] Read the binarized image matrix data, select the edge contour points of the aggregate, generate the two-dimensional coordinate values of the points according to the following formula and store them to obtain the set of all two-dimensional coordinate lattices of the coarse aggregate contour pixel points;

[0010] x = (2i - 1)×d / 2,

[0011] y = 1024d - (2j - 1),

[0012] where x and y are the horizontal and vertical coordinates respectively; i and j are the row and column numbers of the matrix respectively; d refers to the length of the point; read the binarized image matrix data and screen the edge contour points of the coarse aggregate; establish a rectangular coordinate system with the centroid as the origin, read the contour points counterclockwise, and only retain the pixel points whose included angle between the line connecting to the origin and the positive direction of the x-axis is an integer multiple of 1°; connect the screened contour points into a triangular mesh diagram to generate the STL format model of the two-dimensional surface contour of the coarse aggregate;

[0013] (3) Construct the discrete element model:

[0014] In the discrete element software PFC 5.0, combine the irregular contours of the recycled aggregate, generate Clump particles and spherical particles of the new aggregate through the BubblePack algorithm to generate a two-dimensional discrete element model. The density difference between the new and old asphalt needs to be considered in the model, and the calculation formula of the voids in mineral aggregate (VMA) is corrected. The voids in mineral aggregate of the hot recycled asphalt mixture are calculated by the following formula:

[0015]

[0016] where VMA is the voids in mineral aggregate of the hot recycled asphalt mixture, ν_new and ν_old are the volumes of the new and old aggregates respectively, V is the total volume of the asphalt mixture specimen, VV is the designed void ratio, α is the asphalt-aggregate ratio of the asphalt mixture, β is the blending ratio of the old aggregate, ρ b ,new, ρ b ,old are the densities of the new and old aggregates respectively, ρ a is the asphalt density; integrate the parameters of the coarse and fine aggregates to generate a two-dimensional discrete element model.

[0017] Step 2, extract the skeleton gap characteristic parameters:

[0018] Use Image Pro Plus software to extract the skeleton characteristic parameters in the two-dimensional discrete element model of hot recycled asphalt mixture, including the size, volume ratio and distribution of skeleton gaps, specifically including:

[0019] (1) Perform spatial calibration on the two-dimensional discrete element model of asphalt mixture and set the scale;

[0020] (2) Select the skeleton characteristic parameters to be measured, including the size, volume ratio and distribution of skeleton gaps;

[0021] (3) Separate the adhesions at the image edges, manually add the selected objects missed by automatic recognition, and merge and remove the small particles with blurred pixels in the image;

[0022] (4) Export the size, volume ratio and distribution of skeleton gaps and conduct analysis.

[0023] Step 3, optimization design of the reinforcing phase material:

[0024] Determine the parameters of the functional reinforcing phase material: According to the size, volume ratio and distribution of the skeleton gaps, optimize the dosage, diameter range and length parameters of the functional reinforcing phase material; The functional reinforcing materials include self-healing microcapsules and carbon nanotubes. The diameter range of the self-healing microcapsules is 50 - 500 μm to match the gaps of recycled aggregates. To reduce the limitation of the viscosity of old asphalt on the dispersion of the capsules, the dosage of the self-healing microcapsules is 0.5% - 5%. The diameter of the carbon nanotubes is 10 - 50 nm and the length is 1 - 20 μm to overcome the interference of the old asphalt residue on the dispersibility, and the dosage is 0.1% - 1%.

[0025] Step 4, performance verification:

[0026] For the microcapsule self-healing asphalt mixture, design self-healing performance tests, including crack healing rate tests and fatigue life evaluations, to verify whether the anti-cracking and durability mechanical properties of the optimized mixture meet the requirements; For the carbon nanotube asphalt mixture, design conductivity tests for resistivity tests and mechanical property tests for tensile strength and anti-cracking performance to verify whether the comprehensive performance of the optimized mixture meets the requirements of functional pavements such as snow-melting pavements and intelligent pavements.

[0027] When the present invention works, by constructing a discrete element model of asphalt mixture, extracting the skeleton gap characteristic parameters, including the size, volume ratio and distribution of skeleton gaps, and optimizing the dosage, diameter range and length parameters of the functional reinforcing materials (such as self-healing microcapsules in self-healing asphalt mixture, carbon nanotubes in conductive or snow-melting asphalt mixture) according to the characteristic parameters, the blindness of traditional empirical tests is avoided, and the design efficiency and performance of the functional asphalt mixture are improved.

[0028] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0029] First, the optimization design method provided by the present invention accurately extracts the characteristic parameters of the skeleton gap through a discrete element model, quantifies the mesoscopic structure, and establishes a mathematical correlation between the parameters of the reinforcing phase material and the skeleton gap, breaking through the limitations of traditional empirical design, and can realize the scientific proportioning of the grading of the reinforcing phase material, improving the performance of the hot recycled asphalt mixture.

[0030] Second, through the optimization design method of the present invention, a large number of repeated experiments are avoided, the design cycle is shortened, and at the same time, the functional, mechanical and durability properties of the asphalt mixture can be significantly improved.

[0031] Third, the optimization design method of the present invention is applicable to different grading types, such as AC, SMA and OGFC grading types, and has wide engineering applicability. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a schematic flow chart of an optimization design method for a functional reinforcing phase of a hot recycled asphalt mixture based on discrete element simulation of the present invention.

[0033] Figure 2 It is a discrete element model of an AC-13 graded hot recycled asphalt mixture constructed by an optimization design method for a functional reinforcing phase of a hot recycled asphalt mixture based on discrete element simulation of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0034] Example 1: Taking the hot recycled asphalt mixture with AC-13 grading as an example, its specific grading is shown in Table 1:

[0035] Table 1

[0036]

[0037] Such as Figure 1As shown in the flow chart for constructing the two-dimensional discrete element model of AC-13 asphalt mixture, first, several coarse aggregates are selected from the four gradations of coarse aggregates with particle sizes of 16 mm - 13.2 mm, 13.2 mm - 9.5 mm, 9.5 mm - 4.75 mm, and 4.75 mm - 2.36 mm. After washing and drying them, they are placed on the workbench, and the distance between the control camera and the plane is set to 50 cm to obtain photos of each gradation of coarse aggregates in the AC-13 graded hot recycled asphalt mixture. Secondly, according to the obtained photos of each gradation of coarse aggregates in the AC-13 graded hot recycled asphalt mixture, a program is written using Matlab software to obtain the STL format model of the two-dimensional surface contour of the coarse aggregates in the AC-13 graded hot recycled asphalt mixture. Then, in the discrete element software PFC 5.0, based on the STL model, an irregular Clump particle template library is generated using the Bubble Pack filling algorithm to represent the coarse aggregates; the fine aggregates are represented by ideal spherical particles.

[0038] Calculate the voids in mineral aggregate (VMA) of the AC-13 graded hot recycled asphalt mixture. The particle size of the coarse aggregate is 2.36 mm - 16 mm, the particle size of the fine aggregate is 0.075 mm - 2.36 mm, and the asphalt density is ρ a = 1.038 g / cm 3 , and the densities of the new and old aggregates are both ρ b = 2.7 g / cm 3 , the blending ratio of the old aggregate β = 30%, the total volume of the asphalt mixture specimen is V = 100×150 = 15000 mm 3 , the designed void ratio is VV = 5.05%, the volume of the coarse and fine aggregates is v, and the asphalt-aggregate ratio is α = 4.9%. According to the calculation formula, the voids in mineral aggregate are as follows:

[0039]

[0040] In the discrete element software PFC 5.0, aggregate templates are randomly taken from the coarse aggregate template library to generate a two-dimensional discrete element mesoscopic model of the AC-13 graded hot recycled asphalt mixture. The Image Pro Plus software is used to extract the characteristic parameters of the two-dimensional discrete element model, and the characteristics of the AC-13 graded skeleton voids are obtained as follows:

[0041] Size distribution of the skeleton voids: Through statistical analysis, the sizes of the skeleton voids are mainly concentrated in 50 - 200 μm (accounting for 65%), 200 - 400 μm (accounting for 25%), and 400 - 600 μm (accounting for 10%). Volume ratio of the skeleton voids: The total void volume accounts for 4.8% of the total volume of the mixture. Void distribution characteristics: The voids are unevenly distributed, and there is a coexistence phenomenon of dense small voids (<100 μm) and sparse large voids (>400 μm) in local areas. Based on the above characteristics, the logical basis for optimizing the functional reinforcement phase parameters is as follows:

[0042] Principle of microcapsule diameter matching: To effectively fill gaps of different sizes and form a self-healing network, microcapsules with four diameters of 50μm, 150μm, 300μm, and 500μm are selected. Among them, 50μm microcapsules (accounting for 20%) are used to fill small gaps (<100μm) to improve local compactness; 150μm and 300μm microcapsules (each accounting for 30%) cover the main gap range (100 - 400μm) to ensure the main filling efficiency; 500μm microcapsules (accounting for 10%) are used for local repair of some large gaps (>400μm).

[0043] Optimization of blending ratio: According to the proportion of the total gap volume (4.8%), the total dosage of microcapsules is set at 3% (slightly higher than 60% of the gap volume) to ensure that the microcapsules can fully fill the gaps and avoid a decrease in mechanical properties caused by excessive accumulation. Distribution adaptability: Through discrete element simulation verification, the above diameter combination (2:3:3:1) can enable the microcapsules to form a uniform three-dimensional distribution network in the mixture.

[0044] Through the above quantitative analysis, the optimal blending ratio of microcapsules is finally determined to be 3%, the diameter combination is 50μm, 150μm, 300μm, 500μm, and the ratio is 2:3:3:1. Comparing the performance with the traditional empirical design (dosage 5%, random diameter distribution), the optimized scheme improves the distribution efficiency of the functional phase while reducing the dosage by precisely matching the characteristics of the skeleton gaps, providing a scientific basis for subsequent performance verification.

[0045] To verify the performance of the functional enhancement phase of the hot recycled asphalt mixture optimized based on discrete element simulation, the crack healing rate test, anti-cracking test, durability test, and fatigue life evaluation were carried out respectively. The above tests all adopt international standard methods to ensure the scientificity and comparability of the test results; by comparing the test data of the optimized scheme and the traditional scheme, the optimized hot recycled asphalt mixture shows significant improvements in various performance indicators; the specific test scheme and evaluation results are shown in Table 2:

[0046] Table 2

[0047]

[0048] By testing the crack healing rate, anti-cracking property, durability, and fatigue life of the hot recycled asphalt mixture obtained from the optimized scheme and the traditional scheme, the crack healing rate of the optimized scheme reaches 92.5%, which is 18% higher than 78.3% of the traditional scheme, indicating that the distribution of the optimized microcapsules is more uniform and the healing effect is more significant. The fracture energy of the optimized scheme is 1245J / m 2 which is higher than 856J / m of the traditional scheme 2It has increased by 45%, indicating that the optimized mixture has better crack resistance in low-temperature environments. The freeze-thaw splitting strength ratio (TSR) of the optimized scheme is 89.7%, which is 24% higher than 72.4% of the traditional scheme, indicating that the optimized mixture has stronger durability and water damage resistance. The fatigue life of the optimized scheme is 1.8×106 times, which is 100% longer than 0.9×106 times of the traditional scheme, indicating that the optimized mixture has a longer service life under long-term load.

[0049] Example 2:

[0050] Using an optimization design process similar to that of AC-graded hot recycled asphalt mixture, the optimal blending ratios of microcapsules for SMA-13 and OGFC-13 graded hot recycled asphalt mixtures were designed. The optimal blending ratios of microcapsules for SMA-13 and OGFC-13 graded hot recycled asphalt mixtures were determined to be 2.5% and 2% respectively. The diameters of the microcapsules were selected as 50μm, 150μm, 300μm, and 500μm, and the ratios of the four were 1:2:3:2 and 1:4:4:2. Performance comparison was carried out with the traditional empirical design (SMA-13 gradation dosage 4%, OGFC-13 gradation dosage 3.5%, random diameter distribution). The specific test scheme and evaluation results are shown in Table 3:

[0051] Table 3

[0052]

[0053] For the two gradations of SMA-13 and OGFC-13, the crack healing rate, crack resistance, durability, and fatigue life under the two schemes were tested. The crack healing rate of the optimized scheme for SMA-13 gradation reached 91.2%, which was 19% higher than 76.8% of the traditional scheme. The crack healing rate of the optimized scheme for OGFC-13 gradation reached 90.5%, which was 20% higher than 75.3% of the traditional scheme. The fracture energy of the optimized scheme for SMA-13 gradation was 1280 J / m 2 , which was 45% higher than 880 J / m 2 of the traditional scheme. The fracture energy of the optimized scheme for OGFC-13 gradation was 1220 J / m 2 , which was 45% higher than 820 J / m 2It has increased by 49%. The freeze-thaw splitting strength ratio (TSR) of the optimized SMA-13 gradation scheme is 88.5%, which is 24% higher than 71.2% of the traditional scheme. The freeze-thaw splitting strength ratio (TSR) of the optimized OGFC-13 gradation scheme is 87.8%, which is 25% higher than 70.5% of the traditional scheme. The fatigue life of the optimized SMA-13 gradation scheme is 1.9×106 times, which is 100% longer than 0.95×106 times of the traditional scheme. The fatigue life of the optimized OGFC-13 gradation scheme is 1.85×106 times, which is 106% longer than 0.9×106 times of the traditional scheme.

[0054] Through the self-healing microcapsule optimization scheme determined by the functional enhancement phase optimization design method of the hot recycled asphalt mixture of the present invention, the improvement effects on the crack healing rate, crack resistance, durability and fatigue life of the self-healing asphalt mixture have all reached the best, providing a high-performance material solution for the functional asphalt mixture.

[0055] The present invention is not limited to the above embodiments. Based on the technical solutions disclosed in the present invention, those skilled in the art can make some substitutions and deformations to some technical features without creative labor according to the disclosed technical content, and these substitutions and deformations are all within the protection scope of the present invention.

Claims

1. A functional enhancement phase optimization design method for hot-regenerated asphalt mixture based on discrete element simulation, characterized in that: The steps include: Step 1, construct a two-dimensional discrete element model of hot-recycled asphalt mixture: use a digital camera to take an image of the coarse aggregate of the hot-recycled asphalt mixture, use MATLAB to digitally process the coarse aggregate image to obtain an STL format model of the two-dimensional surface contour of the coarse aggregate of the hot-recycled asphalt mixture, then generate the corresponding irregular coarse aggregate particle template library in the discrete element software PFC 5.0 based on the contour of the real aggregate, and generate a two-dimensional discrete element model containing coarse aggregate and fine aggregate in combination with the grading parameters of the actual asphalt mixture; Step 2, extracting contour points and generating STL models: Use Image Pro Plus software to extract skeleton characteristic parameters in the two-dimensional discrete element model of hot recycled asphalt mixture, including the size, volume proportion and distribution of skeleton gaps; Step 3, determine the parameters of the functional reinforcement phase material: optimize the dosage, diameter range and length parameters of the functional reinforcement phase material according to the size, volume proportion and distribution of the skeleton gap; Step 4, verify the optimization results: add the optimized reinforcement phase material back to the generated two-dimensional discrete element model, and adjust the template particles in the model according to the type of reinforcement phase material. Use spherical particle templates to simulate the random distribution of self-healing microcapsules in the mixture; use slender particle templates to simulate the dispersion and conductive network formation of carbon nanotubes in the mixture; finally, design the corresponding hot-regenerated asphalt mixture performance test, compare the optimized reinforcement phase incorporation scheme with other schemes, and verify the feasibility of the scheme.

2. The method for optimizing the functional enhancement of hot-regenerated asphalt mixture based on discrete element simulation according to claim 1 is characterized in that: In the process of digital processing of the coarse aggregate image using MATLAB described in step 1, the acquired coarse aggregate color image needs to be grayed out first. The resolution of the digital camera used for taking pictures is not less than 1200×1024, and the image bit depth is 2 24 To ensure high definition and fast processing; then the image enhancement processing is performed based on the histeq function of MATLAB software to improve the problems of unclear image grayscale and uneven distribution; then, median filtering denoising is performed based on the medfilt2 function in Matlab software to reduce the noise points and blurred details generated during the camera shooting process; finally, binarization processing is performed based on threshold segmentation to obtain a binary image of coarse aggregate.

3. The method for optimizing the functional enhancement of hot-regenerated asphalt mixture based on discrete element simulation according to claim 2 is characterized in that: The binary image matrix data is read, and the edge contour point of the aggregate is selected, and the two-dimensional coordinate value of the point is generated and stored according to the following formula to obtain all the two-dimensional coordinate dot matrix sets of the coarse aggregate contour pixel points; x=(2i-1)×d / 2, y=1024d-(2j-1), Among them, x and y are the horizontal and vertical coordinates respectively; i and j are the row and column numbers of the matrix respectively; d refers to the length of the point.

4. The method for optimizing the functional enhancement of hot-regenerated asphalt mixture based on discrete element simulation according to claim 3 is characterized in that: For the obtained two-dimensional coordinate point array set, all coordinate points need to be screened. The specific steps include: The centroid of the two-dimensional cross-section of the coarse aggregate is taken as the center point O, and a rectangular coordinate system is established. Starting from the coarse aggregate contour point on the x-axis, the coarse aggregate contour points in the image are read counterclockwise. If and only if the straight line connecting the pixel point with point O and the positive direction of the x-axis is an integer multiple of 1°, the pixel point is selected as one of the contour points of the coarse aggregate. Finally, the screened contour points are connected into a triangular mesh diagram to establish a two-dimensional surface contour model of coarse aggregate of hot recycled asphalt mixture in STL format.

5. The method for optimizing the functional enhancement of hot-regenerated asphalt mixture based on discrete element simulation according to claim 1 is characterized in that: When the discrete element software PFC 5.0 is used to generate the corresponding irregular coarse aggregate particle template library as described in step 1, the coarse aggregate is generated into irregular Clump particles through the Bubble Pack filling algorithm, and the fine aggregate is characterized by ideal spherical particles.

6. The method for optimizing the functional enhancement of hot-regenerated asphalt mixture based on discrete element simulation according to claim 1 is characterized in that: The two-dimensional discrete element model described in step 1 needs to consider the density difference between new and old asphalt, and modify the calculation formula of mineral void ratio. The mineral void ratio of hot recycled asphalt mixture is calculated by the following formula: Among them, VMA is the mineral void ratio of hot recycled asphalt mixture, νnew and νold are the volumes of new and old aggregates respectively, V is the total volume of asphalt mixture specimen, VV is the designed void ratio, α is the asphalt-stone ratio of asphalt mixture, β is the mixing ratio of old aggregate, ρ b , new, ρ b , old are the densities of new and old aggregates respectively, ρ a is the density of asphalt.

7. The method for optimizing the functional enhancement of hot-regenerated asphalt mixture based on discrete element simulation according to claim 1 is characterized in that: The steps of extracting the skeleton characteristic parameters in the two-dimensional discrete element model of hot recycled asphalt mixture using Image Pro Plus software as described in step 2 include: (1) Perform spatial calibration on the two-dimensional discrete element model of asphalt mixture and set the scale; (2) Select the skeleton characteristic parameters to be measured, including skeleton gap size, volume proportion, and distribution; (3) Separate the adhered parts of the image edges, manually add the selected objects that are missed by automatic identification, and merge and remove the small particles with blurred pixels in the image; (4) Derive the skeleton gap size, volume percentage, and distribution, and analyze them.

8. The method for optimizing the functional enhancement of hot-regenerated asphalt mixture based on discrete element simulation according to claim 1 is characterized in that: The functional reinforcing material described in step 3 includes self-healing microcapsules and carbon nanotubes. The diameter of the self-healing microcapsules ranges from 50 to 500 μm, and the doping amount is 0.5% to 5%. The diameter of the carbon nanotubes ranges from 10 to 50 nm, the length ranges from 1 to 20 μm, and the doping amount is 0.1% to 1%.

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