A quantitative study method for the competitive interaction between fly ash and filler and asphalt

Abstract

The present invention discloses a quantitative research method for the competitive interaction behavior of garbage fly ash and filler with asphalt, and the main steps include: preparing competitive interaction characterization specimens of garbage fly ash and filler with asphalt binder; identifying garbage fly ash and mineral powder filler particles and their interaction areas, and calibrating them; proposing a quantitative index system for competitive interaction behavior, and evaluating the superiority and effectiveness of competitive interaction behavior. The quantitative research method for the competitive interaction behavior of garbage fly ash and filler in asphalt binder involved in the present invention can realize quantitative research on the degree of interaction between garbage fly ash, filler and asphalt, as well as the competitiveness of the interaction. This method will provide a scientific basis for the resource application of garbage fly ash in asphalt pavement materials.

Description

Technical Field

[0001] The invention relates to the technical field of road asphalt interaction analysis, and in particular to a method for quantifying and evaluating the interaction between filler and asphalt binder using a competitive interaction specimen model. Background Art

[0002] The application of fly ash as a substitute for mineral powder filler in asphalt mixtures has attracted extensive research attention in recent years. As a byproduct from coal-fired power plants, fly ash has a good filling effect and can partially or completely replace traditional mineral powder fillers. However, at the same time, mineral powder, as another filler option, remains one of the main ingredients in asphalt mixtures due to its wide source and stable properties.

[0003] At present, the research on the interaction between mineral powder filler powder and garbage fly ash powder and asphalt binder has been relatively complete. For example, in a laboratory environment, the rheological properties at different temperatures and shear rates are determined by the rotational viscosity test to characterize the interaction strength between the asphalt binder and the particles; the morphology of the contact surface between the particles and asphalt can be directly observed by scanning electron microscopy (SEM) to intuitively evaluate the interaction strength between the particles and the asphalt binder from a microscopic level; the chemical composition of the particles and asphalt and the reactions occurring during their interaction can also be analyzed by XRD and FTIR to characterize their interaction strength. However, all previous studies were aimed at the interaction between a single particle component and the asphalt binder, and there was no research on the competitive interaction between garbage fly ash and mineral powder filler powder when they coexist in the asphalt binder. It is impossible to know which of the interaction strengths between the garbage fly ash powder particles and the mineral powder filler powder particles and the asphalt binder in a single particle is stronger or weaker. Therefore, it is still urgent to propose a reasonable and effective quantitative research method for the competitive interaction between garbage fly ash and filler in asphalt binder, so as to provide economy and accuracy for the selection of fillers in actual production. Summary of the invention

[0004] The purpose of the present invention is to provide a quantitative research method for the competitive interaction behavior between garbage fly ash and filler and asphalt. Compared with the previous research on the interaction between a single particle component and asphalt binder, the present invention provides a method for simultaneously studying the interaction strength between garbage fly ash powder particles and mineral powder filler powder particles and asphalt binder, and provides a new idea for the study of the interaction between powder and asphalt binder by intuitive interaction. At the same time, on the basis of the traditional evaluation method, it also adds a more comprehensive evaluation system, proposes a new evaluation method, and considers the influencing factors of various indicators, which can accurately and comprehensively provide relevant basis for the study of the interaction strength between garbage fly ash powder and mineral powder filler powder and asphalt binder. The specific scheme is as follows:

[0005] A quantitative research method for the competitive interaction behavior between garbage fly ash and filler and asphalt comprises the following steps:

[0006] S1. Use nanoparticles to specifically label landfill fly ash and mineral fillers, and use staggered molds to prepare cylindrical competitive interactive powder material specimens;

[0007] S2. Slowly pour asphalt along the inner wall of the heating barrel, keep it warm at high temperature, and start the interactive auxiliary device to stimulate the composite interactive melting of asphalt, mineral powder filler and fly ash;

[0008] S3. Cut the competitive interaction specimen to be evaluated according to the preset scheme to obtain thin slice specimens, prepare competitive interactive asphalt specimens, and use fluorescence microscopy to identify and calibrate the interaction area and characteristics of fly ash and mineral powder filler;

[0009] S4. With the help of the quantitative index system of the competitive interaction between fly ash and filler and asphalt binder, the advantages and effectiveness of the competitive interaction are evaluated.

[0010] The research method involved in the present invention is mainly based on the systematic study of the interaction between asphalt binder and filler powder material. A quantitative index system of the interaction behavior between powder material and asphalt binder is introduced to conduct a unified quantitative analysis of the intensity of their interaction. The analysis results are highly accurate, and the strength of the interaction can be compared and quantitatively analyzed through the quantitative results, providing a new research and quantitative evaluation method for the comparative study of the interaction intensity between garbage fly ash powder, mineral powder filler powder and asphalt binder, and providing relevant basis for improving the actual road performance of asphalt mixture in actual production.

[0011] The present invention relates to a cylindrical competitive interactive powdery material specimen; a cylindrical staggered mold is used, and the specific structure of the mold is that the central circular area is filled with mineral powder filler, the first annular area is filled with fly ash, the second annular area is filled with mineral powder filler, and the third annular area is filled with fly ash, and each area is isolated by an interval separation partition.

[0012] The invention relates to specific marking of garbage fly ash and mineral powder filler, which is characterized in that nanoparticles doped with rare earth elements are selected to fluorescently mark the garbage fly ash and mineral powder filler; YVO4:Eu is selected as the powder of the mineral powder filler. 3+ Nanoparticles are used for labeling, which can emit red light; LaPO4:Ce is used for waste fly ash powder 3+ , Tb 3+ The nanoparticles can be labeled to emit green light; the labeled fly ash powder and mineral powder filler powder can be directly observed to emit fluorescence of different colors under a fluorescence microscope.

[0013] The selected inorganic nanoparticle dye is surface treated to improve its adsorption capacity. The specific steps are: adding nanoparticles to anhydrous ethanol to prepare a nanoparticle dispersion suspension; adding trichloromethylsilane coupling agent to anhydrous ethanol to prepare a treatment solution; slowly adding the prepared silane coupling agent treatment solution to the nanoparticle dispersion, and stirring with a magnetic stirring bar to ensure that the two are fully mixed. The mixed solution is reacted at a temperature of 50 to 60°C, and the reaction time is generally set at 4 to 6 hours. Finally, it is dried to obtain a surface-treated fluorescent inorganic nanoparticle dye.

[0014] The invention relates to the use of electrophoretic deposition to adsorb nanoparticles on garbage fly ash powder and mineral powder filler powder. The steps of electrophoretic deposition are: dispersing a nanoparticle dye into ethanol with a mass fraction of 95% to prepare a nanoparticle dispersion, and adding a proper amount of PVP surfactant to improve dispersibility; treating the mineral powder filler powder and the garbage fly ash powder with a surface conductive coating; adding the mineral powder filler powder and the garbage fly ash powder into the nanoparticle dispersion, inserting electrodes, activating a direct current power supply to start electrophoretic deposition, and setting the deposition time at 10 to 20 minutes; filtering and drying after the deposition to obtain specifically labeled garbage fly ash powder and mineral powder filler powder.

[0015] The present invention relates to a method for preparing a competitive interactive test piece to be evaluated, which is specifically as follows: the heating barrel used in the preparation is cylindrical, with specific dimensions of 22 cm in diameter and 30 cm in height; a prefabricated specifically marked powder test piece is placed in an immersed cylindrical groove at the bottom of the cylindrical heating barrel, and a heating thermal resistance wire and heat transfer oil are present at the bottom and wall of the barrel to quantitatively supply heat to stimulate the composite interactive melting of asphalt, mineral powder filler and fly ash; the inner liner of the heating barrel used to hold asphalt is 316 stainless steel, and the inner wall of the heating barrel is coated with an oleophobic barrier; along the cylindrical Slowly pour hot asphalt into the inner walls of both ends of the heating barrel until the asphalt surface reaches the calibration line marked on the inner barrel, then turn on the heating device, heat the asphalt together with the specifically marked powdery specimen to 170°C and keep it warm at high temperature for 20 to 30 minutes; during the insulation period, stir with a magnetic stirring bar from both sides of the heating barrel, and set the speed of the magnetic stirring bar to 500 to 700 r / min; after the specified test time is reached, put the insulation barrel into the freezer, use liquid nitrogen to flash freeze the specimen, and then keep it warm at -10 to 20°C.

[0016] The present invention relates to cutting a competitive interaction specimen to be evaluated according to a preset scheme to obtain a thin sheet specimen; setting an interactive quantitative reference plane on the specimen, the reference plane in the vertical direction is set at the bottom of the specimen, and the reference plane in the horizontal direction is set at the central axis position of the specimen; taking the specimen out of a freezer, using a blade to cut with the edge point of the interactive specimen mold to be evaluated as the starting point, cutting the competitive interaction specimen to be evaluated horizontally and vertically to form a competitive interaction characterization thick sheet specimen; horizontal cutting is performed in a direction perpendicular to the generatrix of the cylindrical specimen to be evaluated, and the cutting interval thickness is 1 cm; vertical cutting is performed in a direction perpendicular to the upper surface of the cylindrical specimen to be evaluated, and the cutting interval thickness is 1 cm; according to this setting, two specimens are cut to obtain 6 pie-shaped sections in the horizontal direction, which are 5 characterization surfaces in total, and 6 rectangular columnar sections in the vertical direction, which are 5 characterization surfaces in total, and after cutting, the thick sheet specimen is wrapped with silicone oil paper and placed in a freezer for cold storage.

[0017] The present invention involves preparing competitive interactive asphalt specimens and using a fluorescent microscope to identify and calibrate the interactive area and characteristics of fly ash and mineral powder filler; taking out thick sheet specimens and then using a low-temperature precision cutting process to obtain thin sheet specimens, the thin sheet specimens are surface slices of each thick sheet specimen for characterizing the particle migration of the cutting surface, one thick sheet specimen cuts one thin sheet specimen, that is, two cut specimens obtain a total of 10 thin sheet specimens of characterization surface; the thickness of the thin sheet specimen is controlled to be 30 μm for easy observation; to calibrate the interactive characterization area, a coordinate system is set with the centroid of each thin sheet specimen as the coordinate origin, the coordinate system divides the thin sheet specimen into four equal parts, and on each cut surface, a 10×10 square grid surface is constructed with the coordinate system as the center and the centroid coincides with the center of the coordinate system, the four endpoints of the square grid surface are distributed on the arc of the thin sheet specimen, and the size of each grid on the grid surface is the same;

[0018] The specific calibrated powdery material in the thin slice specimen is identified and its coordinates are determined by using a fluorescence microscope. The specific method is as follows: the processed thin slice specimen is placed on a glass slide, covered with a cover glass and dripped with a sealing agent. According to the fluorescent nanoparticles doped with rare earth elements, specifically: YVO4:Eu 3+ Nanoparticles and LaPO4:Ce 3+ , Tb 3+ Excitation and emission spectra of nanoparticles, select the corresponding excitation filter and emission filter, specifically YVO4:Eu 3+ Nanoparticles select the excitation filter with wavelength of 365nm and the emission filter with wavelength of 545nm; LaPO4:Ce 3+ , Tb 3+For the nanoparticles, select an excitation filter with a wavelength of 365nm and an emission filter with a wavelength of 615nm; fix the glass slide and use a low-power objective lens with a specific magnification of 10×. First, find the sample area and roughly adjust the focus to make the sample clearly visible; then switch to a high-power objective lens with a specific magnification of 40×, 60× or 100× for fine focusing, and adjust the light intensity of the fluorescence microscope and the exposure time of the camera to obtain the best image contrast and brightness, and determine the coordinates of the fly ash and mineral powder filler in the picture; mark the fly ash and mineral powder filler of each grid while ensuring the clarity of the image, digitize the marked image, count the particles through the coordinates of the fly ash and mineral powder filler, and calculate the distance between each particle, and record the number of mineral powder particles and garbage fly ash particles in each grid as well as the distance data between the particles, and perform corresponding operations on each section.

[0019] The present invention relates to a quantitative index system for competitive interaction between garbage fly ash and filler and asphalt binder to evaluate the dominant side and efficiency of the competitive interaction; the quantitative index coefficient of variation and aggregation index are used to evaluate the degree of interaction between mineral powder particles and garbage fly ash particles and asphalt, and the calculation of the coefficient of variation and aggregation index is based on the identification of the interaction area and characteristics of the fly ash and the mineral powder filler by using a fluorescent microscope, wherein the number of mineral powder particles and garbage fly ash particles in the grid of each section is identified; the coefficient of variation and aggregation index of the indicators characterizing the competitive interaction between the mineral powder filler and the garbage fly ash and the asphalt binder are applicable to both transversely cut specimens and longitudinally cut specimens, and the two specimens are calculated and evaluated using the same evaluation system;

[0020] The application of the coefficient of variation is that in image analysis, the coefficient of variation can be used to quantify the uniformity of the distribution of fluorescent labeled particles in a two-dimensional plane. If the coefficient of variation is low, it means that the particles are distributed more evenly; if the coefficient of variation is high, it means that the particles are aggregated or unevenly distributed.

[0021] Define the coefficient of variation B v , the calculation process is: based on the number of particles in a 10×10 grid, calculate the mean μ of the number of particles in all grid cells. The specific calculation formula is:

[0022]

[0023] The meanings of the parameters are as follows: μ is the average number of particles per grid unit; n i is the number of particles in each grid, i is the number of the grid; N is the total number of grids;

[0024] After obtaining the mean μ, the standard deviation of the number of particles contained in each grid is calculated. The specific calculation formula is:

[0025]

[0026] The meanings of the parameters are as follows: δ is the standard deviation of the number of particles contained in each cell; k is the sample capacity, and the number of grid divisions for each section is 10×10, that is, k=100; n i is the number of particles in each grid, i is the number of the grid, where i = 1, 2, 3, …, k; μ is the mean number of particles in all grid cells;

[0027] The calculation formula of the coefficient of variation of the particle statistics of the section grid is:

[0028]

[0029] Among them B v is the coefficient of variation of the particle statistics of the section grid; δ is the standard deviation of the number of particles contained in each cell; μ is the average number of particles per unit grid cell; the coefficient of variation B v That is, as a characterization indicator of the uniformity of particles when interacting with asphalt;

[0030] The coefficient of variation value range can be used to know its discrete degree and analyze the characteristics of the uniformity of particles when interacting with asphalt; the coefficient of variation B of the statistical data of the cross-section grid particles v The coefficient of variation reflects the degree of data dispersion. A small dispersion indicates that the particles in the cut specimen are evenly distributed, while a large dispersion indicates that the particles in the cut specimen are unevenly distributed. The coefficient of variation range can be used to determine the degree of dispersion and analyze the particle distribution characteristics of the cut specimen. The coefficient of variation range is divided and evaluated as follows, with B v The coefficient of variation representing the particle statistics of the slice mesh:

[0031] (1) When the coefficient of variation B v When the absolute value is in the interval [0,0.1], it means that the data fluctuates less, has a lower degree of discreteness, and the data is relatively stable, indicating that the interactive particles in the section specimen present a uniform distribution characteristic;

[0032] It is specially noted that when the coefficient of variation B v When the absolute value is in the interval (0.1, 0.3], the fluctuation of the data is at a medium level and has a certain degree of discreteness; this indicates that the interactive particles in the section specimen have the characteristics of cluster distribution and the interactive morphology characteristics of the interactive particle clusters appear in the specimen;

[0033] (2) When the coefficient of variation B v When the absolute value is in the interval (0.3, 1), it means that the data fluctuates greatly, has a high degree of discreteness, and is relatively unstable, indicating that the interacting particles in the section specimen present a random distribution morphology.

[0034] The present invention relates to a quantitative index system for the competitive interaction between garbage fly ash and filler and asphalt binder to evaluate the dominance and effectiveness of the competitive interaction; wherein the aggregation index is used to measure the degree of aggregation of particles and to determine whether there is significant aggregation of particles.

[0035] Define the convergence index C, and use the nearest neighbor distance method to calculate the convergence index C. The calculation process is as follows: based on the distance statistics of particles in a 10×10 grid, record the data between each migrating particle and its nearest neighbor, average the nearest neighbor distances of all points, and get the average nearest neighbor distance The calculation formula is:

[0036]

[0037] The meaning of each parameter is: represents the average nearest neighbor distance of the migrating particles under the section; d i represents the distance between each migrating particle and its nearest neighbor, i is the number of each migrating particle, i = 1, 2, 3, 4, ... n; n represents the total number of migrating particles involved in the counting under this section;

[0038] Then calculate the expected nearest neighbor distance The calculation formula is:

[0039]

[0040] The meaning of each parameter is: represents the expected nearest neighbor distance of the migrating particles under the section; ρ represents the point density of the migrating particles under the section; n represents the total number of migrating particles involved in the counting under the section; A represents the area of ​​the section;

[0041] The cumulative function A(d) is defined as the number of point pairs within the detection circle with a radius of d minus the expected number of point pairs, where d represents an adjustable spatial scale. The distance between the data points of the migrated particles at this scale is used to analyze and understand the spatial properties and patterns of the data. When using the circle controlled by d to calculate the cumulative function A(d) or the convergence index C, it is not necessarily required that all data points are completely included in the circle. The main purpose of selecting d is to define a distance threshold to determine whether the point pairs within the threshold are taken into account. In mathematics, 3 times the expected nearest neighbor distance is often selected as d to calculate the cumulative function, that is,

[0042] Therefore, the cumulative function A(d) can be expressed as:

[0043]

[0044] The meanings of the parameters are as follows: A(d) represents the cumulative function; ρ represents the density of the migrating particles under the section; n represents the total number of migrating particles involved in the counting under the section; i and j both represent the number of migrating particles under the section, where d ij represents the distance from the i-th migrating particle to the j-th migrating particle; 1(d ij ≤d) is the indicator function, that is, if d is satisfied ij 1 if ≤d, otherwise 0;

[0045] Therefore, the average nearest neighbor distance and expected nearest neighbor distance The convergence index C can be obtained, and its calculation formula is:

[0046]

[0047] The meanings of the parameters are as follows: C represents the migration particle aggregation index at a distance scale of d; A(d) represents the cumulative function; d is the distance scale, which is also the radius of the detection circle, and the value of 3 times the expected nearest neighbor distance d is selected;

[0048] The aggregation degree of particles can be known from the value range of the aggregation index C to characterize the characteristics of particles when interacting with asphalt. The aggregation index C of the particle statistics of the section can be used to evaluate the aggregation of migrating particles according to its value range:

[0049] (1) When the aggregation index C satisfies C≈0, it means that the migrating particles are closer to the characteristics of random distribution, and the reference value of aggregation and dispersion uniformity is not great;

[0050] (2) When the aggregation index C satisfies C>0, it means that the distribution of migrating particles shows aggregation, indicating that there will be particle clustering in some areas, and the larger the absolute value of C, the stronger the aggregation;

[0051] (3) When the convergence index C satisfies C < 0, it means that the distribution of migrating particles is dispersed, indicating that the distances between migrating particles in the entire cross-sectional area are far apart and more dispersed, and the larger the absolute value of C, the stronger its dispersion.

[0052] The present invention relates to the advantages and effectiveness of evaluating competitive interaction behavior, wherein the comprehensive coefficient of variation B v The coefficient of variation is used to evaluate the overall distribution of the migrating particles after interaction with asphalt, and the aggregation index is used to evaluate the degree of interaction between the migrating particles and asphalt. The two indicators are used to comprehensively evaluate the competitive interaction between the two particles and asphalt:

[0053] (1) When the migrating particles show a coefficient of variation B vWhen the value is (0, 0.3] and the aggregation index C>0, the comprehensive evaluation shows that the particles show high aggregation and uniform distribution, indicating that there is a strong particle-asphalt interaction in some areas. The interaction degree between the particles and the asphalt in this interactive state is the best.

[0054] (2) When the migrating particles show a coefficient of variation B v The value is (0,0.3], and the aggregation index C is less than 0; the comprehensive evaluation is that the particles are evenly distributed but the interaction strength with asphalt is weak, indicating that the particles are evenly distributed after interacting with asphalt, but the interaction strength is limited;

[0055] (3) When the migrating particles show a coefficient of variation B v When the value is (0.3, 1) and the aggregation index C>0, the comprehensive evaluation is that the particles show high aggregation but uneven distribution, indicating that there is a local concentrated interaction between the particles and the asphalt;

[0056] (4) When the migrating particles show a coefficient of variation B v When the value is (0.3, 1) and the aggregation index C is less than 0, the comprehensive evaluation shows that the particles are unevenly distributed and the interaction is weak, indicating that there are randomly distributed interference factors in the interaction area, which leads to weak interaction between particles and asphalt. The interaction degree between the particles and asphalt in this interactive state is the worst.

[0057] The above evaluation criteria can provide an advantageous effectiveness basis for the competitive interaction between fly ash powder particles and mineral powder filler powder particles and asphalt, thereby determining which particle has a stronger interaction with asphalt. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 Schematic diagram of the powder characterization specimen;

[0059] Figure 2 Schematic diagram of the heating barrel for specimen preparation;

[0060] Figure 3 Top view of the heating barrel for specimen preparation;

[0061] Figure 4 Schematic diagram of the internal details of the heating barrel prepared for the specimen;

[0062] Main component symbols: 1. Asphalt binder (flowing state); 2. Heat transfer oil; 3. Powder characterization specimen container; 4. Heating resistance wire; 5. Insulation layer made of glass fiber and rock wool; 6. Oleophobic layer;

[0063] Figure 5 Schematic diagram of cutting characterization specimen. DETAILED DESCRIPTION

[0064] The present invention is further described below with reference to specific examples, but the examples do not limit the present invention in any form. Unless otherwise specified, the reagents, methods and equipment used in the present examples are conventional reagents, methods and equipment in the art.

[0065] Unless otherwise specified, the reagents and materials used in the following examples are commercially available.

[0066] A quantitative research method for the competitive interaction between fly ash and filler and asphalt, including:

[0067] S1. Use nanoparticles to specifically label landfill fly ash and mineral fillers, and use staggered molds to prepare cylindrical competitive interactive powder material specimens;

[0068] S2. Slowly pour asphalt along the inner wall of the heating barrel, keep it warm at high temperature, and start the interactive auxiliary device to stimulate the composite interactive melting of asphalt, mineral powder filler and fly ash;

[0069] S3. Cut the competitive interaction specimen to be evaluated according to the preset scheme to obtain thin slice specimens, prepare competitive interactive asphalt specimens, and use fluorescence microscopy to identify and calibrate the interaction area and characteristics of fly ash and mineral powder filler;

[0070] S4. With the help of the quantitative index system of the competitive interaction between fly ash and filler and asphalt binder, the advantages and effectiveness of the competitive interaction are evaluated.

[0071] The quantitative research method for the competitive interaction between garbage fly ash and filler in asphalt binder proposed in this embodiment is as follows:

[0072] S1: Cylindrical competitive interactive powder material specimen; a cylindrical staggered mold is used, and the specific structure of the mold is that the central circular area is filled with mineral powder filler, the first annular area is filled with fly ash, the second annular area is filled with mineral powder filler, and the third annular area is filled with fly ash. Each area is isolated by a spacer.

[0073] The waste fly ash and mineral powder filler are specifically marked, characterized in that nanoparticles doped with rare earth elements are selected to fluorescently mark the waste fly ash and mineral powder filler; YVO4:Eu is selected as the mineral powder filler powder 3+ Nanoparticles are used for labeling, which can emit red light; LaPO4:Ce is used for waste fly ash powder 3+ , Tb 3+ The nanoparticles can be labeled to emit green light; the labeled fly ash powder and mineral powder filler powder can be directly observed to emit fluorescence of different colors under a fluorescence microscope.

[0074] The selected inorganic nanoparticle dye was surface treated to improve its adsorption capacity. The specific steps were as follows: adding nanoparticles to anhydrous ethanol to prepare a nanoparticle dispersion suspension; adding trichloromethylsilane coupling agent to anhydrous ethanol to prepare a treatment solution; slowly adding the prepared silane coupling agent treatment solution to the nanoparticle dispersion, and stirring with a magnetic stirring bar to ensure that the two were fully mixed. The mixed solution was reacted at a temperature of 55°C, the reaction time was set at 5h, and finally dried to obtain a surface-treated fluorescent inorganic nanoparticle dye.

[0075] Electrophoretic deposition is used to adsorb nanoparticles on the garbage fly ash powder and the mineral powder filler powder. The steps of electrophoretic deposition are as follows: disperse the nanoparticle dye in 95% by mass ethanol to prepare a nanoparticle dispersion, and add an appropriate amount of PVP surfactant to improve the dispersibility; treat the mineral powder filler powder and the garbage fly ash powder with a surface conductive coating; add the mineral powder filler powder and the garbage fly ash powder to the nanoparticle dispersion, insert electrodes, enable a DC power supply to start electrophoretic deposition, and set the deposition time to 15 minutes; filter and dry after the deposition to obtain specifically labeled garbage fly ash powder and mineral powder filler powder.

[0076] S2: The preparation method of the competitive interaction specimen to be evaluated is as follows: the heating barrel used in the preparation is cylindrical, with specific dimensions of 22 cm in diameter and 30 cm in height;

[0077] The prefabricated specifically marked powdery specimen is placed in the immersed cylindrical groove at the bottom of the cylindrical heating barrel. There are heating resistance wires and heat transfer oil at the bottom and wall of the barrel, which are used to quantitatively supply heat to stimulate the composite interactive melting of asphalt, mineral powder filler and fly ash. The inner liner of the heating barrel used to hold the asphalt is 316 stainless steel, and the inner wall of the heating barrel is coated with an oleophobic barrier.

[0078] Slowly pour hot asphalt along the inner walls of both ends of the cylindrical heating barrel until the asphalt surface reaches the calibration line marked on the inner barrel, then turn on the heating device, heat the asphalt together with the specifically marked powdery specimen to 170°C and keep it warm for 25 minutes; during the insulation period, stir with a magnetic stirring bar from both sides of the inner barrel of the heating barrel, and set the speed of the magnetic stirring bar to 600r / min; after the specified test time is reached, put the insulation barrel into the freezer, use liquid nitrogen to flash freeze the specimen, and then store it at -5°C.

[0079] S3: Cut the competitive interaction specimen to be evaluated according to the preset plan to obtain a thin sheet specimen; set an interactive quantization reference plane on the specimen, the reference plane in the vertical direction is set at the bottom of the specimen, and the reference plane in the horizontal direction is set at the center axis position of the specimen; take the specimen out of the freezer, use a blade to cut with the edge point of the interactive specimen mold to be evaluated as the starting point, cut the competitive interaction specimen to be evaluated horizontally and vertically to form a competitive interaction characterization thick sheet specimen; horizontal cutting is performed in a direction perpendicular to the generatrix of the cylindrical specimen to be evaluated, and the cutting interval thickness is 1 cm; vertical cutting is performed in a direction perpendicular to the upper surface of the cylindrical specimen to be evaluated, and the cutting interval thickness is 1 cm; according to this setting, two specimens are cut to obtain 6 pie-shaped sections in the horizontal direction, a total of 5 characterization surfaces, and 6 rectangular columnar sections in the vertical direction, a total of 5 characterization surfaces. After cutting, the thick sheet specimen is wrapped with silicone oil paper and placed in a freezer for refrigeration.

[0080] A fluorescence microscope was used to identify and calibrate the interaction area and characteristics of fly ash and mineral powder filler; thick sheet specimens were taken out and then a low-temperature precision cutting process was used to obtain thin sheet specimens. The thin sheet specimens were surface slices of each thick sheet specimen used to characterize the particle migration of the cutting surface. One thick sheet specimen was cut into one thin sheet specimen, that is, two cut specimens obtained a total of 10 thin sheet specimens with characterization surfaces; the thickness of the thin sheet specimen was controlled to be 30 μm for easy observation; to calibrate the interaction characterization area, a coordinate system was set with the centroid of each thin sheet specimen as the coordinate origin. The coordinate system divided the thin sheet specimen into four equal parts. On each section, a 10×10 square grid surface was constructed with the coordinate system as the center and the centroid coincided with the center of the coordinate system. The four endpoints of the square grid surface were distributed on the arc of the thin sheet specimen, and the size of each grid on the grid surface was the same;

[0081] The specific calibrated powdery material in the thin slice specimen is identified and its coordinates are determined by using a fluorescence microscope. The specific method is as follows: the processed thin slice specimen is placed on a glass slide, covered with a cover glass and dripped with a sealing agent. According to the fluorescent nanoparticles doped with rare earth elements, specifically: YVO4:Eu 3+ Nanoparticles and LaPO4:Ce 3+ , Tb 3+ Excitation and emission spectra of nanoparticles, select the corresponding excitation filter and emission filter, specifically YVO4:Eu 3+ Nanoparticles select the excitation filter with wavelength of 365nm and the emission filter with wavelength of 545nm; LaPO4:Ce 3+ , Tb 3+For the nanoparticles, select an excitation filter with a wavelength of 365nm and an emission filter with a wavelength of 615nm; fix the glass slide and use a low-power objective lens with a specific magnification of 10×. First, find the sample area and roughly adjust the focus to make the sample clearly visible; then switch to a high-power objective lens with a specific magnification of 40×, 60× or 100× for fine focusing, and adjust the light intensity of the fluorescence microscope and the exposure time of the camera to obtain the best image contrast and brightness, and determine the coordinates of the fly ash and mineral powder filler in the picture; mark the fly ash and mineral powder filler of each grid while ensuring the clarity of the image, digitize the marked image, count the particles through the coordinates of the fly ash and mineral powder filler, and calculate the distance between each particle, and record the number of mineral powder particles and garbage fly ash particles in each grid as well as the distance data between the particles, and perform corresponding operations on each section.

[0082] S4: With the help of the quantitative index system of the competitive interaction between garbage fly ash and filler and asphalt binder, the dominant side and efficiency of the competitive interaction behavior are evaluated; the quantitative index coefficient of variation and aggregation index are used to evaluate the degree of interaction between mineral powder particles and garbage fly ash particles and asphalt, and the calculation of the coefficient of variation and aggregation index is based on the identification of the interaction area and characteristics of the fly ash and mineral powder filler by fluorescence microscopy, in which the number of mineral powder particles and garbage fly ash particles in the grid of each section is identified; the coefficient of variation and aggregation index of the indicators characterizing the competitive interaction between mineral powder filler and garbage fly ash and asphalt binder are applicable to both transversely cut specimens and longitudinally cut specimens, and the two specimens are calculated and evaluated using the same evaluation system;

[0083] The number of the two types of particles in the two types of cut specimens is counted, and the following table is obtained:

[0084] Table 1 Statistics of particle number in longitudinal section

[0085]

[0086] Table 2 Statistics of particle numbers in transverse sections

[0087]

[0088] The coefficient of variation of the two powder particles in the transverse and longitudinal sections of the test specimen is calculated as follows: based on the number of particles in a 10×10 grid, the mean μ of the number of particles in all grid cells is calculated. The specific calculation formula is:

[0089]

[0090] The meanings of the parameters are as follows: μ is the average number of particles per grid unit; n i is the number of particles in each grid, i is the number of the grid; N is the total number of grids;

[0091] After obtaining the mean μ, the standard deviation of the number of particles contained in each grid is calculated. The specific calculation formula is:

[0092]

[0093] The meanings of the parameters are as follows: δ is the standard deviation of the number of particles contained in each cell; k is the sample size. The number of grid divisions for each section in this patent is 10×10, that is, k=100; n i is the number of particles in each grid, i is the number of the grid, where i = 1, 2, 3, …, k; μ is the mean number of particles in all grid cells;

[0094] The calculation formula of the coefficient of variation of the particle statistics of the section grid is:

[0095]

[0096] Among them B v is the coefficient of variation of the particle statistics of the section grid; δ is the standard deviation of the number of particles contained in each cell; μ is the mean number of particles in all grid cells; the coefficient of variation B v That is, as a characterization indicator of the uniformity of particles when interacting with asphalt, the final results are shown in the following table:

[0097] Table 3. Statistical results of longitudinal section interviews

[0098]

[0099] Table 4 Statistical results of cross-sectional interviews

[0100]

[0101] From the result summary table, we can get the average values ​​of the longitudinal sections of the fly ash powder and the mineral powder powder: the longitudinal average coefficient of variation of the fly ash powder is 9.26%, and the longitudinal average coefficient of variation of the mineral powder is 16.76%;

[0102] Taking the average values ​​of the transverse sections of the garbage fly ash powder and the mineral powder powder, we can obtain: the transverse average coefficient of variation of the garbage fly ash powder is 9.59%, and the transverse average coefficient of variation of the mineral powder is 22.29%.

[0103] The nearest neighbor distance method is used to calculate the convergence index C. The calculation process is as follows: based on the distance statistics of particles in a 10×10 grid, the data between each migrating particle and its nearest neighbor is recorded, and the nearest neighbor distances of all points are averaged to obtain the average nearest neighbor distance. The calculation formula is:

[0104]

[0105] The meaning of each letter is: represents the average nearest neighbor distance of the migrating particles under the section; d i represents the distance between each migrating particle and its nearest neighbor, i is the number of each migrating particle, i = 1, 2, 3, 4, ... n; n represents the total number of migrating particles involved in the counting under this section;

[0106] Then calculate the expected nearest neighbor distance The calculation formula is:

[0107]

[0108] The meaning of each parameter is: represents the expected nearest neighbor distance of the migrating particles under the section; ρ represents the point density of the migrating particles under the section; n represents the total number of migrating particles involved in the counting under the section; A represents the area of ​​the section;

[0109] The cumulative function A(d) is defined as the number of point pairs within the detection circle with a radius of d minus the expected number of point pairs, where d represents an adjustable spatial scale. The distance between the data points of the migrated particles at this scale is used to analyze and understand the spatial properties and patterns of the data. When using the circle controlled by d to calculate the cumulative function A(d) or the convergence index C, it is not necessarily required that all data points are completely included in the circle. The main purpose of selecting d is to define a distance threshold to determine whether the point pairs within the threshold are taken into account. In mathematics, 3 times the expected nearest neighbor distance is often selected as d to calculate the cumulative function, that is,

[0110] Therefore, the cumulative function A(d) can be expressed as:

[0111]

[0112] The meanings of the letters are as follows: A(d) represents the cumulative function; ρ represents the density of the migrating particles under the section; n represents the total number of migrating particles involved in the counting under the section; i and j both represent the number of migrating particles under the section, where d ij represents the distance from the i-th migrating particle to the j-th migrating particle; 1(d ij ≤d) is the indicator function, that is, if d is satisfied ij ≤d is 1, otherwise it is 0; the cumulative function value of the migrating particles within the detection circle can be directly obtained through computer recognition technology.

[0113] Therefore, the average nearest neighbor distance and expected nearest neighbor distance The convergence index C can be obtained, and its calculation formula is:

[0114]

[0115] The meanings of the letters are as follows: C represents the migration particle aggregation index at a distance scale of d; A(d) represents the cumulative function; d is the distance scale, which is also the radius of the detection circle, and a value of 3 times the expected nearest neighbor distance d is selected; the final results are shown in the following table:

[0116] Table 5 Calculation results of the aggregation index of the longitudinal section of mineral powder

[0117]

[0118] Table 6 Calculation results of the aggregation index of the transverse section of mineral powder

[0119]

[0120] Table 7 Calculation results of the longitudinal section aggregation index of fly ash

[0121]

[0122]

[0123] Table 8 Calculation results of the aggregation index of the horizontal section of garbage fly ash

[0124]

[0125] It can be seen from the result summary table that the fly ash powder particles show data characteristics greater than 0 in both the transverse and longitudinal section specimens, while the mineral powder particles show data characteristics close to 0 or less than 0 in the transverse and longitudinal section specimens.

[0126] Evaluate the advantages and effectiveness of competitive interaction behavior; comprehensive coefficient of variation B v The aggregation index C is used to comprehensively evaluate the two types of migrating particles: mineral powder filler powder particles and garbage fly ash powder particles:

[0127] The migration particles in the longitudinal section test specimen were evaluated, and the migration particles of the fly ash powder showed a coefficient of variation B v When the value is (0,0.3] and the aggregation index C>0, the comprehensive evaluation is that the particles show high aggregation and uniform distribution, indicating that there is a strong particle-asphalt interaction in some areas; the mineral powder particles show a coefficient of variation B v The value is (0,0.3], and the aggregation index C≈0 or C<0. The comprehensive evaluation is that the particles are evenly distributed but the interaction intensity with asphalt is weak, indicating that the particles are evenly distributed after interacting with asphalt, but the interaction intensity is limited;

[0128] The migration particles in the transverse section specimens were evaluated, and the migration particles of the fly ash showed a coefficient of variation B v When the value is (0,0.3] and the aggregation index C>0, the comprehensive evaluation is that the particles show high aggregation and uniform distribution, indicating that there is a strong particle-asphalt interaction in some areas; the mineral powder particles show a coefficient of variation B v The value is (0,0.3], and the aggregation index C≈0 or C<0. The comprehensive evaluation is that the particles are evenly distributed but the interaction intensity with asphalt is weak, indicating that the particles are evenly distributed after interacting with asphalt, but the interaction intensity is limited;

[0129] In summary, quantitative results can be obtained through calculation. Analysis of the migrating particles in the transverse and longitudinal specimens shows that the spatial distribution of fly ash powder evaluated by the coefficient of variation and the bonding strength with the asphalt binder evaluated by the aggregation index are better than those of mineral powder particles. Therefore, in this section specimen, the interaction strength between fly ash particles and asphalt binder is stronger than that between mineral powder particles, which is the advantage of the competitive interaction specimen.

[0130] The quantitative research method of the competitive interaction behavior between garbage fly ash and filler in asphalt binder involved in the present invention has relevant reference basis and foundation for evaluating and analyzing the competitive interaction behavior between different powder migration particles and asphalt binder. It is applied to the selection of fillers in actual asphalt mixtures and the research and analysis of road performance, and the quantitative analysis of the competitive interaction behavior between powder specimens and asphalt binder is realized based on index analysis. The analysis results are highly accurate, and the characteristics of the competitive interaction behavior within powder specimens and asphalt binder can be evaluated and determined through the quantitative results, which will provide relevant basis for improving the road performance of the selection of fillers in asphalt mixtures.

[0131] As described above, the quantitative research method for the competitive interaction behavior between fly ash and filler in asphalt binder provided by the present invention is introduced in detail. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; any simple modifications, changes and equivalent structural changes made to the above embodiments based on the essence of the invention technology are still within the protection scope of the technical solution of the present invention.

Claims

1. A quantitative research method for the competitive interaction between garbage fly ash and filler and asphalt, characterized in that: The determination method mainly includes the following steps: S1. Use nanoparticles to specifically label landfill fly ash and mineral fillers, and use staggered molds to prepare cylindrical competitive interactive powder material specimens; S2. Slowly pour asphalt along the inner wall of the heating barrel, keep it warm at high temperature, and start the interactive auxiliary device to stimulate the composite interactive melting of asphalt, mineral powder filler and fly ash; S3. Cut the competitive interaction specimen to be evaluated according to the preset scheme to obtain thin slice specimens, prepare competitive interactive asphalt specimens, and use fluorescence microscopy to identify and calibrate the interaction area and characteristics of fly ash and mineral powder filler; S4. With the help of the quantitative index system of the competitive interaction between fly ash and filler and asphalt binder, the advantages and effectiveness of the competitive interaction are evaluated.

2. The method for quantitatively studying the competitive interaction behavior between garbage fly ash, filler and asphalt according to claim 1 is characterized in that: The cylindrical competitive interactive powder material specimen described in step S1; a cylindrical staggered mold is used, and the specific structure of the mold is that the central circular area is filled with mineral powder filler, the first annular area is filled with fly ash, the second annular area is filled with mineral powder filler, and the third annular area is filled with fly ash, and each area is isolated by a spacer separation partition; The specific marking of the waste fly ash and the mineral powder filler in step S1 is characterized in that the waste fly ash and the mineral powder filler are fluorescently marked by selecting nanoparticles doped with rare earth elements; YVO4:Eu is selected as the powder of the mineral powder filler. 3+ Nanoparticles are used for labeling, which can emit red light; LaPO4:Ce is used for waste fly ash powder 3+ , Tb 3+ The nanoparticles can be labeled to emit green light; the labeled fly ash powder and mineral powder filler powder can be directly observed to emit fluorescence of different colors under a fluorescence microscope; The specific marking of garbage fly ash and mineral powder filler as described in step S1 is characterized in that the selected inorganic nanoparticle colorant is surface treated to improve its adsorption capacity, and the specific steps are: adding nanoparticles to anhydrous ethanol to prepare a nanoparticle dispersion suspension; adding trichloromethylsilane coupling agent to anhydrous ethanol to prepare a treatment liquid; slowly adding the prepared silane coupling agent treatment liquid to the nanoparticle dispersion, and stirring with a magnetic stirring bar to ensure that the two are fully mixed; reacting the mixed solution at a temperature of 50 to 60° C., the reaction time is generally set at 4 to 6 hours, and finally drying to obtain a surface-treated fluorescent inorganic nanoparticle colorant; The specific marking of the garbage fly ash and the mineral powder filler described in step S1 is characterized in that the nanoparticles are adsorbed on the garbage fly ash powder and the mineral powder filler powder by using electrophoretic deposition, and the steps of electrophoretic deposition are: dispersing the nanoparticle colorant into 95% ethanol by mass to prepare a nanoparticle dispersion, and adding an appropriate amount of PVP surfactant to improve the dispersibility; treating the mineral powder filler powder and the garbage fly ash powder with a surface conductive coating; adding the mineral powder filler powder and the garbage fly ash powder to the nanoparticle dispersion, inserting electrodes, and starting electrophoretic deposition with a DC power supply, and setting the deposition time to 10 to 20 minutes; filtering and drying after the deposition to obtain the specifically marked garbage fly ash powder and the mineral powder filler powder.

3. The method for quantitatively studying the competitive interaction behavior between garbage fly ash, filler and asphalt according to claim 1 is characterized in that: The preparation method of the competitive interaction specimen to be evaluated described in step S2 is specifically as follows: the heating barrel used in the preparation is cylindrical, with specific dimensions of 22 cm in diameter and 30 cm in height; the prefabricated specifically labeled powder specimen is placed in an immersed cylindrical groove at the bottom of the cylindrical heating barrel, and there are heating thermal resistance wires and heat transfer oil at the bottom and wall of the barrel to quantitatively supply heat to stimulate the composite interactive melting of asphalt, mineral powder filler and fly ash; the inner liner of the heating barrel used to hold asphalt is 316 type stainless steel, and the inner wall of the heating barrel is coated with an oleophobic barrier; along the cylindrical Slowly pour hot asphalt into the inner walls of both ends of the heating barrel until the asphalt surface reaches the calibration line marked on the inner barrel, then turn on the heating device, heat the asphalt together with the specifically marked powdery specimen to 170°C and keep it warm at high temperature for 20 to 30 minutes; during the insulation period, stir with a magnetic stirring bar from both sides of the heating barrel, and set the speed of the magnetic stirring bar to 500 to 700 r / min; after the specified test time is reached, put the insulation barrel into the freezer, use liquid nitrogen to flash freeze the specimen, and then keep it warm at -10 to 20°C.

4. The method for quantitatively studying the competitive interaction behavior between garbage fly ash, filler and asphalt according to claim 1, characterized in that: In step S3, the competitive interaction specimen to be evaluated is cut according to a preset scheme to obtain a thin slice specimen; an interactive quantization reference plane is set on the specimen, the reference plane is set at the bottom of the specimen in the vertical direction, and the reference plane is set at the central axis position of the specimen in the horizontal direction; The specimen was taken out from the freezer, and a blade was used to cut the competitive interactive specimen with the edge of the mold being evaluated as the starting point. The competitive interactive specimen was cut horizontally and vertically to form a competitive interactive characterization thick sheet specimen; the horizontal cutting was perpendicular to the generatrix of the cylindrical specimen to be evaluated, and the cutting interval thickness was 1 cm; the vertical cutting was perpendicular to the upper surface of the cylindrical specimen to be evaluated, and the cutting interval thickness was 1 cm; according to this setting, two specimens were cut to obtain 6 pie-shaped sections in the horizontal direction with a total of 5 characterization surfaces, and 6 rectangular columnar sections in the vertical direction with a total of 5 characterization surfaces. After cutting, the thick sheet specimen was wrapped with silicone oil paper and placed in a freezer for refrigeration.

5. The method for quantitatively studying the competitive interaction behavior between garbage fly ash, filler and asphalt according to claim 1 is characterized in that: The preparation of competitive interactive asphalt specimens described in step S3 uses a fluorescent microscope to identify and calibrate the interactive area and characteristics of fly ash and mineral powder filler; the thick sheet specimen is taken out and then a low-temperature precision cutting process is used to obtain a thin sheet specimen, the thin sheet specimen is a surface slice of each thick sheet specimen used to characterize the particle migration of the cutting surface, one thick sheet specimen is cut into one thin sheet specimen, that is, two cut specimens obtain a total of 10 thin sheet specimens of characterization surface; the thickness of the thin sheet specimen is controlled to be 30μm for easy observation; to calibrate the interactive characterization area, a coordinate system is set with the centroid of each thin sheet specimen as the coordinate origin, the coordinate system divides the thin sheet specimen into four equal parts, and on each section, a 10×10 square grid surface is constructed with the coordinate system as the center and the centroid coincides with the center of the coordinate system, the four endpoints of the square grid surface are distributed on the arc of the thin sheet specimen, and the size of each grid on the grid surface is the same; The specific calibrated powdery material in the thin slice specimen is identified and its coordinates are determined by using a fluorescence microscope. The specific method is as follows: the processed thin slice specimen is placed on a glass slide, covered with a cover glass and dripped with a sealing agent. According to the fluorescent nanoparticles doped with rare earth elements, specifically: YVO4:Eu 3+ Nanoparticles and LaPO4:Ce 3+ , Tb 3+ Excitation and emission spectra of nanoparticles, select the corresponding excitation filter and emission filter, specifically YVO4:Eu 3+ Nanoparticles select the excitation filter with wavelength of 365nm and the emission filter with wavelength of 545nm; LaPO4:Ce 3+ , Tb 3+ For the nanoparticles, select an excitation filter with a wavelength of 365nm and an emission filter with a wavelength of 615nm; fix the glass slide and use a low-power objective lens with a specific magnification of 10×. First, find the sample area and roughly adjust the focus to make the sample clearly visible; then switch to a high-power objective lens with a specific magnification of 40×, 60× or 100× for fine focusing, and adjust the light intensity of the fluorescence microscope and the exposure time of the camera to obtain the best image contrast and brightness, and determine the coordinates of the fly ash and mineral powder filler in the picture; mark the fly ash and mineral powder filler of each grid while ensuring the clarity of the image, digitize the marked image, count the particles through the coordinates of the fly ash and mineral powder filler, and calculate the distance between each particle, and record the number of mineral powder particles and garbage fly ash particles in each grid as well as the distance data between the particles, and perform corresponding operations on each section.

6. The method for quantitatively studying the competitive interaction behavior between garbage fly ash, filler and asphalt according to claim 1, characterized in that: In step S4, the quantitative index system of the competitive interaction between garbage fly ash and filler and asphalt binder is used to evaluate the dominant side and efficiency of the competitive interaction; the quantitative index coefficient of variation and the aggregation index are used to evaluate the degree of interaction between mineral powder particles and garbage fly ash particles and asphalt, and the calculation of the coefficient of variation and the aggregation index is based on the identification of the interaction area and characteristics of the fly ash and the mineral powder filler by using a fluorescent microscope as described in step S3, wherein the number of mineral powder particles and garbage fly ash particles in the grid of each section is identified; the coefficient of variation and the aggregation index of the indicators characterizing the competitive interaction between the mineral powder filler and the garbage fly ash and the asphalt binder are applicable to both transversely cut specimens and longitudinally cut specimens, and the two specimens are calculated and evaluated using the same evaluation system; Define the coefficient of variation B v , the calculation process is: based on the number of particles in a 10×10 grid, calculate the mean μ of the number of particles in all grid cells. The specific calculation formula is: The meanings of the parameters are as follows: μ is the average number of particles per unit grid cell; n i is the number of particles in each grid, i is the number of the grid; N is the total number of grids; After obtaining the mean μ, the standard deviation of the number of particles contained in each grid is calculated. The specific calculation formula is: The letters mean: δ is the standard deviation of the number of particles contained in each cell; k is the sample capacity, and the number of grid divisions for each section is 10×10, that is, k=100; n i is the number of particles in each grid, i is the number of the grid, where i = 1, 2, 3, …, k; μ is the mean number of particles in all grid cells; The calculation formula of the coefficient of variation of the particle statistics of the section grid is: Among them B v is the coefficient of variation of the particle statistics of the section grid; δ is the standard deviation of the number of particles contained in each cell; μ is the average number of particles per unit grid cell; the coefficient of variation B v That is, as a characterization indicator of the uniformity of particles when interacting with asphalt; The degree of dispersion can be known from the value range of the coefficient of variation and the particle distribution characteristics of the section specimen can be analyzed. The coefficient of variation interval is divided and evaluated as follows, where B v The coefficient of variation representing the particle statistics of the slice mesh: (1) When the coefficient of variation B v When the absolute value is in the interval [0,0.1], it means that the data fluctuates less, has a lower degree of discreteness, and the data is relatively stable, indicating that the interactive particles in the section specimen present a uniform distribution characteristic; It is specially noted that when the coefficient of variation B v When the absolute value is in the interval (0.1, 0.3], the fluctuation of the data is at a medium level and has a certain degree of discreteness, indicating that the interactive particles in the section specimen have the characteristics of cluster distribution and the interactive morphology characteristics of the interactive particle clusters appear in the specimen; (2) When the coefficient of variation B v When the absolute value is in the interval (0.3, 1), it means that the data fluctuates greatly, has a high degree of discreteness, and is relatively unstable, indicating that the interacting particles in the section specimen present a random distribution morphology.

7. The method for quantitatively studying the competitive interaction behavior between garbage fly ash, filler and asphalt according to claim 1, characterized in that: Step S4, using a quantitative index system for competitive interaction between garbage fly ash and filler and asphalt binder to evaluate the advantages and effectiveness of the competitive interaction; The aggregation index is used to measure the aggregation degree of particles and determine whether there is significant aggregation of particles. Define the convergence index C, and use the nearest neighbor distance method to calculate the convergence index C. The calculation process is as follows: based on the distance statistics of particles in a 10×10 grid, record the data between each migrating particle and its nearest neighbor, average the nearest neighbor distances of all points, and get the average nearest neighbor distance The calculation formula is: The meaning of each parameter is: represents the average nearest neighbor distance of the migrating particles under the section; d i represents the distance between each migrating particle and its nearest neighbor, i is the number of each migrating particle, i = 1, 2, 3, 4, ... n; n represents the total number of migrating particles involved in the counting under this section; Then calculate the expected nearest neighbor distance The calculation formula is: The meaning of each parameter is: represents the expected nearest neighbor distance of the migrating particles under the section; ρ represents the point density of the migrating particles under the section; n represents the total number of migrating particles involved in the counting under the section; A represents the area of ​​the section; The cumulative function A(d) is defined as the number of point pairs within the detection circle with a radius of d minus the expected number of point pairs, where d represents an adjustable spatial scale. The distance between the migrated particle data points at this scale is used to analyze and understand the spatial properties and patterns of the data. When using the circle controlled by d to calculate the cumulative function A(d) or the convergence index C, it is not necessarily required that all data points are completely included in the circle. The main purpose of selecting d is to define a distance threshold to determine whether the point pairs within the threshold are taken into account. In mathematics, 3 times the expected nearest neighbor distance is often selected as d to calculate the cumulative function, that is, Therefore, the cumulative function A(d) can be expressed as: The meanings of the parameters are as follows: A(d) represents the cumulative function; ρ represents the density of the migrating particles under the section; n represents the total number of migrating particles involved in the counting under the section; i and j both represent the number of migrating particles under the section, where d ij represents the distance from the i-th migrating particle to the j-th migrating particle; 1(d ij ≤d) is the indicator function, that is, if d is satisfied ij ≤d is 1, otherwise it is 0; Therefore, the average nearest neighbor distance and expected nearest neighbor distance The convergence index C can be obtained, and its calculation formula is: The meanings of the parameters are as follows: C represents the migration particle aggregation index at a distance scale of d; A(d) represents the cumulative function; d is the distance scale, which is also the radius of the detection circle, and the value of 3 times the expected nearest neighbor distance d is selected; The aggregation degree of particles can be known from the value range of the aggregation index C to characterize the characteristics of particles when interacting with asphalt. The aggregation index C of the particle statistics of the section can be used to evaluate the aggregation of migrating particles according to its value range: (1) When the aggregation index C satisfies C≈0, it means that the migrating particles are closer to the characteristics of random distribution, and the reference value of aggregation and dispersion uniformity is not great; (2) When the aggregation index C satisfies C>0, it means that the distribution of migrating particles shows aggregation, indicating that there will be particle clustering in some areas, and the larger the absolute value of C, the stronger the aggregation; (3) When the convergence index C satisfies C < 0, it means that the distribution of migrating particles is dispersed, indicating that the distances between migrating particles in the entire cross-sectional area are far apart and more dispersed, and the larger the absolute value of C, the stronger its dispersion.

8. The method for quantitatively studying the competitive interaction behavior between garbage fly ash, filler and asphalt according to claim 1, characterized in that: Step S4 evaluates the advantages and effectiveness of competitive interaction behavior; wherein the comprehensive coefficient of variation B v The coefficient of variation is used to evaluate the overall distribution of the migrating particles after interaction with asphalt, and the aggregation index is used to evaluate the degree of interaction between the migrating particles and asphalt. The two indicators are used to comprehensively evaluate the competitive interaction between the two particles and asphalt: (1) When the migrating particles show a coefficient of variation B v When the value is (0, 0.3] and the aggregation index C>0, the comprehensive evaluation shows that the particles show high aggregation and uniform distribution, indicating that there is a strong particle-asphalt interaction in some areas. The interaction degree between the particles and the asphalt in this interactive state is the best. (2) When the migrating particles show a coefficient of variation B v The value is (0, 0.3], and the aggregation index C is less than 0; the comprehensive evaluation is that the particles are evenly distributed but the interaction strength with asphalt is weak, indicating that the particles are evenly distributed after interacting with asphalt, but the interaction strength is limited; (3) When the migrating particles show a coefficient of variation B v When the value is (0.3, 1) and the aggregation index C>0, the comprehensive evaluation is that the particles show high aggregation but uneven distribution, indicating that there is a local concentrated interaction between the particles and the asphalt; (4) When the migrating particles show a coefficient of variation B v When the value is (0.3, 1) and the aggregation index C is less than 0, the comprehensive evaluation shows that the particles are unevenly distributed and the interaction is weak, indicating that there are randomly distributed interference factors in the interaction area, which leads to weak interaction between particles and asphalt. The degree of interaction between the interacting particles and asphalt in this interactive state is the worst.

Images