Prediction method for wear resistance of aggregate surface

Abstract

The invention relates to a method for predicting the wear resistance of an aggregate surface, and belongs to the technical field of pavement material performance testing. The method comprises the following steps: firstly, carrying out an abrasion test on various aggregates, and carrying out a morphological characteristic test to obtain an optimal morphological index changing along with the abrasion frequency; establishing a linear direct proportion function of the abrasion loss rate of each type of aggregate in different abrasion stages and the optimal morphological index change rate; preparing various types of aggregate powder, and carrying out XRD (X-Ray Diffraction) test to determine mineral phase components and mass fractions of the aggregate powder; cubic sample blocks of various aggregates are manufactured, the Young modulus and Poisson's ratio of mineral phases of the aggregates are obtained through indentation testing, and the porosity of the aggregates is obtained through mercury intrusion testing; calculating the equivalent macroscopic Young modulus of each type of aggregate based on an MT homogenization method; establishing a linear relation between the equivalent macroscopic Young modulus and a proportionality coefficient; and correcting the linear proportional function to obtain a pre-estimation model. The method comprehensively considers the morphological characteristics and mineral composition of the aggregate, and can effectively improve the prediction precision of the wear resistance of the surface of the aggregate.

Description

Technical Field

[0001] This invention belongs to the field of road material performance testing technology, specifically relating to a method for predicting the abrasion resistance of aggregate surfaces. Background Technology

[0002] Currently, the evaluation of aggregate abrasion resistance is mostly conducted through the Los Angeles abrasion test to explore its abrasion loss rate. In addition, in recent years, some scholars at home and abroad have attempted to study the surface texture characteristics of aggregates. Zhang used the Los Angeles abrasion test to simulate the force applied to coarse aggregates and compared the morphology of different coarse aggregates before and after abrasion; simultaneously, he used the AIMS method to measure their morphological characteristics; the study showed that the angular characteristics of each type of aggregate significantly decreased after abrasion, and the reduction in angular characteristics was the main factor causing abrasion loss. Kuang et al. used the angularity index to characterize the angularity and roughness of limestone and granite under different abrasion times; at the same time, they studied the relationship between the surface texture of coarse aggregates and the number of abrasion cycles. Zhang et al. studied the changes in coarse aggregate morphology during the Los Angeles test; they used four types of rock aggregates—limestone, tuff, granite, and diabase—and the Image Measurement System II (AIMS II) for research, and proposed a predictive model for abrasion resistance performance based on changes in aggregate morphological characteristics.

[0003] On the other hand, as a heterogeneous composite material, the macroscopic deformation and damage characteristics of aggregates are closely related to the microscopic mechanical properties of various minerals. Therefore, taking mineral composition as the starting point is one of the important approaches to studying the wear resistance of aggregates. Wu Jiangfeng conducted multi-scale wear tests on limestone, basalt, quartzite, gneiss, and red sandstone, and combined molecular dynamics and finite element simulation methods to observe and study the wear resistance of aggregates at different scales, proposing that the essential reason for the difference in aggregate wear resistance is the difference in aggregate mineral composition. Pikryl et al. pointed out that the mechanical properties of aggregates depend on the size and composition of mineral particles, and the anisotropy of surface strength of rock aggregates depends on the tendency of mineral particle shape. Lindqvist et al. studied the influence of the microscopic properties of rock aggregates on their physical and mechanical properties, and found that the microscopic characteristics of aggregates, such as mineral composition, porosity, and surface microcracks, determine the macroscopic mechanical properties of aggregates.

[0004] Despite numerous studies on aggregate abrasion resistance, the following limitations remain: While the attenuation of aggregate surface texture features is correlated with its abrasion resistance, the initial morphological characteristics of different aggregates vary, and the attenuation rates differ significantly under different morphological features. Therefore, evaluating abrasion resistance solely through the Los Angeles abrasion test has limitations. Furthermore, although mineral composition significantly contributes to aggregate abrasion resistance, current research primarily focuses on the influence of mineral composition on abrasion resistance, lacking a framework to map mineral composition-related characterization parameters to the aggregate as a whole, and thus explore the correlation between mineral composition and abrasion resistance.

[0005] Therefore, overcoming the shortcomings of existing technologies is an urgent problem to be solved in the field of pavement material performance testing technology. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for predicting the surface wear resistance of aggregates by comprehensively considering the morphological characteristics and mineral composition of aggregates, which can effectively improve the prediction accuracy of the surface wear resistance of aggregates.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0008] A method for predicting the wear resistance of aggregate surfaces includes the following steps:

[0009] Step (1): Los Angeles abrasion test is conducted on various aggregates, and morphological characteristics are tested on the aggregates before abrasion and after each abrasion test. The morphological index of each aggregate is calculated. The morphological index includes fractal dimension, edge angle parameter, axial coefficient and sphericity.

[0010] Step (2): Using the number of wear cycles and aggregate type as variables, a two-way ANOVA was used to analyze the correlation between various morphological indicators and different wear cycles and different aggregate types; the morphological indicator with the largest F value in the F test results was used as the best morphological indicator to characterize the wear resistance performance of aggregates.

[0011] Step (3) The aggregate is subjected to multiple abrasions, with each abrasion rotation being 300-500 revolutions. After each abrasion is completed, the abrasion loss rate and morphological index are measured. A linear direct proportional function of the abrasion loss rate of various aggregates and the change rate of the optimal morphological index is established for different abrasion stages.

[0012] Step (4): Grind to obtain various aggregate powders, and determine the aggregate mineral phases and their mass fractions by XRD.

[0013] Step (5): Prepare cubic samples of various aggregates, grind and polish them, clean them and dry them; the side length of the cubic sample is 5-15mm.

[0014] Step (6): Observe the cubic sample block with the optical microscope built into the indenter to determine the distribution range of minerals with a mass fraction of more than 5% in each phase of the aggregate; then, perform nanoindentation test on it to obtain the nanoscale Young's modulus, bulk modulus, shear modulus and Poisson's ratio of each mineral phase in the aggregate.

[0015] Step (7): Prepare various aggregate cube samples with a size of 5-10mm, and use mercury intrusion porosimetry to obtain the aggregate porosity;

[0016] Step (8): Calculate the equivalent macroscopic Young's modulus of various aggregates based on the MT homogenization method;

[0017] Step (9): Establish the equivalent macroscopic Young's modulus of various aggregates and their corresponding proportionality coefficients k. D Linear regression function:

[0018] k D =A 0* E hom +C0

[0019] In the formula: A0 and C0 are both fitting constants, E hom k is the equivalent macroscopic Young's modulus of the aggregate. D This is the proportionality coefficient between the wear loss rate and the rate of change of the optimal morphological index;

[0020] Step (10) corrects the first-order proportional function established in step (3) to obtain the prediction model based on Young's modulus and Los Angeles wear loss rate:

[0021] LA=(A0*E hom +C0)|F0-F n |

[0022] Then, the wear loss rate prediction model is used to predict the wear loss rate of various aggregates, and the prediction results are used as the wear resistance of the aggregate surface.

[0023] Furthermore, in step (1), the abrasion test is conducted in accordance with the relevant provisions of the coarse aggregate abrasion test (Los Angeles method) (T0317-2024) in the "Specifications for Aggregate Testing in Highway Engineering" (JTG3432-2024);

[0024] Each type of aggregate underwent 4-6 abrasion tests, with each test lasting 300-500 revolutions. After each abrasion test, the cumulative abrasion loss rate was calculated, as follows:

[0025]

[0026] In the formula: LA n The cumulative wear loss rate after the nth wear test is m0, where m is the aggregate mass before wear.n The residual mass of aggregate after the nth abrasion test.

[0027] Furthermore, in step (1), when testing the morphological characteristics, the number of aggregate particles selected for each type should not be less than 50.

[0028] The specific method for morphological feature testing is as follows: use a camera with more than 10 million pixels to acquire the morphological image of each aggregate, import it into ImageJ for morphological feature quantitative analysis, call the Analyze module in ImageJ to perform particle size analysis, and realize the calculation of fractal dimension, edge parameters, axial coefficient and sphericity.

[0029] The fractal dimension is calculated as follows:

[0030]

[0031] In the formula: D is the fractal dimension; N(r) is the number of boxes, and r is the scaling factor of the box size;

[0032] The calculation method for the angle parameters is as follows:

[0033] L = (P A / P E ) 2

[0034] In the formula: L is the angularity parameter, P A P represents the true perimeter of the aggregate particles. E The equivalent ellipse perimeter;

[0035] The axial coefficient is calculated as follows:

[0036] A = T / W

[0037] In the formula: A is the axial coefficient; T and W are the lengths of the major and minor axes of the equivalent ellipse of the two-dimensional projection of the aggregate, respectively;

[0038] The method for calculating sphericity is as follows:

[0039] C = (P A ) 2 / [4π(S A ) 2 ]

[0040] In the formula: C represents roundness, P A S represents the true perimeter of the aggregate particles. A This represents the actual area of ​​the aggregate.

[0041] Furthermore, in step (3), the established linear direct proportional function between the wear loss rate of various aggregates at different wear stages and the change rate of the optimal morphology index is as follows:

[0042] LA = kD *(|F0-F n |)

[0043] In the formula: k D F0 is the ratio coefficient between the wear loss rate and the rate of change of the optimal morphology index; F0 is the optimal morphology index value of the aggregate before wear. n α represents the optimal morphology index value of the aggregate after wear; LA represents the wear loss rate.

[0044] Furthermore, in step (4), the specific grinding method is to use a grinding mill with a mesh size of 800 or higher to obtain aggregate powder, with each type of aggregate powder weighing no less than 1g and grinding time no less than 5 minutes; subsequently, XRD testing is performed using an X-ray diffractometer, and the mineral phase composition and mass fraction of the aggregate are determined by comparing with a PDF card library.

[0045] Furthermore, in step (5), the specific method for polishing is to use sandpaper with grits of P800, P2000, P3000, P5000, and P7000 from low to high to polish until smooth; among them, the polishing time for P800, P2000, and P3000 should not be less than 5 minutes, and the polishing time for P5000 and P7000 should be more than 10 minutes.

[0046] Furthermore, in step (5), during the grinding and polishing process, sandpaper is first used for grinding, and then 80,000 mesh Al2O3 suspension is used for further polishing.

[0047] Furthermore, in step (6), the indentation area during the indentation test should be a square area with a side length of 250-300 μm, and areas with obvious defects should be avoided; the loading and unloading method is as follows: 10s loading, 5s holding load, 10s unloading, and the peak load is 5×10 -3 N; the distance between adjacent indentation points is 20μm or more;

[0048] There should be no fewer than 3 measurement points for each mineral phase.

[0049] Furthermore, the specific method for step (8) is as follows:

[0050] (8.1) The pore structure of the aggregate and the mechanical properties of the soft minerals are initially homogenized into the mechanical properties of the porous matrix solid phase, wherein the soft minerals are the minerals with the smallest Young's modulus test results in the aggregate:

[0051]

[0052] k s =E s / 3(1-2υ s )

[0053] μ s =E s / 2(1+υ s )

[0054]

[0055] In the formula: k low and μ low These are the bulk modulus and shear modulus of the porous matrix after initial homogenization, respectively. V represents the porosity of the homogenized matrix, and m represents the porosity obtained from mercury intrusion porosimetry of the aggregate. r k represents the mass fraction of soft minerals. s and μ s These are the bulk modulus and shear modulus of soft minerals, respectively; E s Young's modulus of soft minerals; υ s The Poisson's ratio for soft minerals;

[0056] (8.2) The mechanical properties of the hard minerals and porous matrix solid phase in the aggregate are homogenized twice to obtain the macroscopic mechanical properties of the material. The hard minerals are all minerals except the mineral with the lowest Young's modulus in the test results.

[0057]

[0058] k r =E r / 3(1-2υ r )

[0059] μ r =E r / 2(1+υ r )

[0060] In the formula: The macroscopic equivalent shear modulus of the aggregate after secondary homogenization; E represents the macroscopic equivalent bulk modulus of the aggregate after secondary homogenization. r Young's modulus for various hard mineral phases; f r k represents the mass fraction of various hard mineral phases. r μ r These are the bulk modulus and shear modulus of various hard mineral phases, respectively; υ r denoted by r, where r represents the Poisson's ratio for each type of hard mineral; n represents the total number of hard mineral phases; if r is 0, it is considered that there are no hard minerals.

[0061] (8.3) After obtaining the equivalent mechanical parameters of each phase medium, the equivalent macroscopic Young's modulus of the homogenized aggregate is calculated using the following formula:

[0062]

[0063] In the formula: E homThe equivalent macroscopic Young's modulus of the homogenized aggregate.

[0064] This invention also provides a method for predicting the wear resistance of aggregate surfaces, using a prediction model based on Young's modulus and Los Angeles wear loss rate, as shown in the following formula:

[0065] LA=(-1.002×E hom +649.000)|F0-F n |

[0066] The prediction model is used to predict the wear loss rate of various aggregates, and the prediction results are used as a method for evaluating the wear resistance of aggregate surfaces; the aggregate types include basalt, granite, limestone and bauxite.

[0067] In step (2) of this invention, SPSS software can be used to perform a two-way ANOVA to analyze the sensitivity of various morphological indicators to different wear times and different aggregate types.

[0068] When performing indentation testing, the distance between the measurement points of the same mineral phase is only about 20 μm. Therefore, it is only necessary to perform three tests in the same indentation area, and the result is the average of the three tests.

[0069] In this invention, the loss stage refers to each loss process, and one loss process is one loss stage.

[0070] Some technical points of this invention are as follows:

[0071] 1. Based on two-way ANOVA, we propose an optimal morphological index for the attenuation of aggregate morphological characteristics under cumulative abrasion.

[0072] 2. The Young's modulus of each mineral phase inside the aggregate was obtained by nanomechanical testing methods, and the cross-scale upgrading of the Young's modulus of the minerals was achieved based on the Mori-Tanaka method.

[0073] 3. Obtain a predictive model for aggregate wear loss based on morphological parameter decay and Young's modulus.

[0074] Compared with the prior art, the beneficial effects of this invention are as follows:

[0075] (1) The present invention uses a two-way ANOVA method to determine the optimal morphological index that varies with the number of aggregate wear cycles, which can more comprehensively evaluate the morphological changes of aggregate during the wear process, further reveal the wear mechanism, and improve the accuracy of prediction.

[0076] (2) This method fully considers the synergistic effect of aggregate phase composition and its nanoscale mechanical properties on wear behavior when predicting aggregate wear performance, and is scientific and reliable.

[0077] (3) In existing aggregate wear rate prediction technologies, most methods only construct prediction models based on relative hardness indicators, without fully considering the complex influence of aggregate morphology on wear behavior. This method considers both morphological characteristics and mechanical properties, establishing a quadratic composite regression model, which has significantly better fitting accuracy than the former and can reduce prediction error by more than 10%. In addition, the indicators used in this method are all absolute indicators, and compared with the aforementioned relative hardness indicators, the results are more intuitive and accurate. Attached Figure Description

[0078] Figure 1 The evolution trend of morphological characteristics of various aggregates under different wear cycles is shown; among them, a. axial coefficient; b. roundness; c. angular parameter; d. fractal dimension;

[0079] Figure 2 The regression results are for the fractal dimension change rate and the wear loss rate; where a. basalt; b. granite; c. limestone; d. bauxite;

[0080] Figure 3 The indentation areas and mineral phases of various aggregates are represented, including: a. basalt; b. granite; c. limestone; d. bauxite.

[0081] Figure 4 The results are the Young's modulus test results for each mineral phase in the aggregate; where a. basalt; b. granite; c. limestone; d. bauxite; Test1, Test2, and Test3 represent the results of three tests respectively;

[0082] Figure 5 Young's modulus and k D The correlation analysis results. Detailed Implementation

[0083] The present invention will now be described in further detail with reference to the embodiments.

[0084] Those skilled in the art will understand that the following embodiments are for illustrative purposes only and should not be construed as limiting the scope of the invention. Where specific techniques or conditions are not specified in the embodiments, they are performed in accordance with the techniques or conditions described in the literature in the field or according to the product instructions. Materials or equipment whose manufacturers are not specified are all conventional products that can be obtained by purchase.

[0085] Example 1

[0086] A method for predicting the wear resistance of aggregate surfaces includes the following steps:

[0087] Step (1): Los Angeles abrasion test is conducted on various aggregates, and morphological characteristics are tested on the aggregates before abrasion and after each abrasion test. The morphological index of each aggregate is calculated. The morphological index includes fractal dimension, edge angle parameter, axial coefficient and sphericity.

[0088] Step (2): Using the number of wear cycles and aggregate type as variables, a two-way ANOVA was used to analyze the correlation between various morphological indicators and different wear cycles and different aggregate types; the morphological indicator with the largest F value in the F test results was used as the best morphological indicator to characterize the wear resistance performance of aggregates.

[0089] Step (3) The aggregate is subjected to multiple abrasions, each abrasion is 400 revolutions, and the abrasion loss rate and morphological index are measured after each abrasion. A first-order direct proportional function of the abrasion loss rate of various aggregates and the change rate of the best morphological index is established at different abrasion stages.

[0090] Step (4): Grind to obtain various aggregate powders, and determine the aggregate mineral phases and their mass fractions by XRD.

[0091] Step (5): Prepare cubic samples of various aggregates, grind and polish them, clean them and dry them; the side length of the cubic sample is 10mm.

[0092] Step (6): Observe the cubic sample block with the optical microscope built into the indenter to determine the distribution range of minerals with a mass fraction of more than 5% in each phase of the aggregate; then, perform nanoindentation test on it to obtain the nanoscale Young's modulus, bulk modulus, shear modulus and Poisson's ratio of each mineral phase in the aggregate.

[0093] Step (7): Prepare various aggregate cube samples with a size of 8mm, and use mercury intrusion porosimetry to obtain the aggregate porosity;

[0094] Step (8): Calculate the equivalent macroscopic Young's modulus of various aggregates based on the MT homogenization method;

[0095] Step (9): Establish the equivalent macroscopic Young's modulus of various aggregates and their corresponding proportionality coefficients k. D Linear regression function:

[0096] k D =A 0* E hom +C0

[0097] In the formula: A0 and C0 are both fitting constants, E hom k is the equivalent macroscopic Young's modulus of the aggregate. D This is the ratio coefficient between the wear loss rate and the rate of change of the optimal morphological index;

[0098] Step (10) corrects the first-order proportional function established in step (3) to obtain the prediction model based on Young's modulus and Los Angeles wear loss rate:

[0099] LA = (A 0* E hom +C0)|F0-F n |

[0100] Then, the wear loss rate prediction model is used to predict the wear loss rate of various aggregates, and the prediction results are used as the wear resistance of the aggregate surface.

[0101] Example 2

[0102] A method for predicting the wear resistance of aggregate surfaces includes the following steps:

[0103] Step (1): Los Angeles abrasion test is conducted on various aggregates, and morphological characteristics are tested on the aggregates before abrasion and after each abrasion test. The morphological index of each aggregate is calculated. The morphological index includes fractal dimension, edge angle parameter, axial coefficient and sphericity.

[0104] Step (2): Using the number of wear cycles and aggregate type as variables, a two-way ANOVA was used to analyze the correlation between various morphological indicators and different wear cycles and different aggregate types; the morphological indicator with the largest F value in the F test results was used as the best morphological indicator to characterize the wear resistance performance of aggregates.

[0105] Step (3) The aggregate is subjected to multiple abrasions, each abrasion is 300 revolutions, and the abrasion loss rate and morphological index are measured after each abrasion. A linear direct proportional function of the abrasion loss rate of various aggregates and the change rate of the optimal morphological index is established at different abrasion stages.

[0106] Step (4): Grind to obtain various aggregate powders, and determine the aggregate mineral phases and their mass fractions by XRD.

[0107] Step (5): Prepare cubic samples of various aggregates, grind and polish them, clean them and dry them; the side length of the cubic sample is 5mm.

[0108] Step (6): Observe the cubic sample block with the optical microscope built into the indenter to determine the distribution range of minerals with a mass fraction of more than 5% in each phase of the aggregate; then, perform nanoindentation test on it to obtain the nanoscale Young's modulus, bulk modulus, shear modulus and Poisson's ratio of each mineral phase in the aggregate.

[0109] Step (7): Prepare various aggregate cube samples with a size of 5mm, and use mercury intrusion porosimetry to obtain the aggregate porosity;

[0110] Step (8): Calculate the equivalent macroscopic Young's modulus of various aggregates based on the MT homogenization method;

[0111] Step (9): Establish the equivalent macroscopic Young's modulus of various aggregates and their corresponding proportionality coefficients k. D Linear regression function:

[0112] k D =A 0* E hom +C0

[0113] In the formula: A0 and C0 are both fitting constants, E hom k is the equivalent macroscopic Young's modulus of the aggregate. D This is the proportionality coefficient between the wear loss rate and the rate of change of the optimal morphological index;

[0114] Step (10) corrects the first-order proportional function established in step (3) to obtain the prediction model based on Young's modulus and Los Angeles wear loss rate:

[0115] LA=(A0*E hom +C0)|F0-F n |

[0116] Then, the wear loss rate prediction model is used to predict the wear loss rate of various aggregates, and the prediction results are used as the wear resistance of the aggregate surface.

[0117] In step (1), the abrasion test is conducted in accordance with the relevant provisions of the coarse aggregate abrasion test (Los Angeles method) (T0317-2024) in the "Specifications for Aggregate Testing in Highway Engineering" (JTG3432-2024);

[0118] Each type of aggregate underwent four abrasion tests, with each test lasting 300 revolutions. The cumulative abrasion loss rate was calculated after each test, as follows:

[0119]

[0120] In the formula: LA n The cumulative wear loss rate after the nth wear test is m0, where m is the aggregate mass before wear. n The residual mass of aggregate after the nth abrasion test.

[0121] In step (1), when testing the morphological characteristics, the number of aggregate particles selected for each type should not be less than 50.

[0122] The specific method for morphological feature testing is as follows: use a camera with more than 10 million pixels to acquire the morphological image of each aggregate, import it into ImageJ for morphological feature quantitative analysis, call the Analyze module in ImageJ to perform particle size analysis, and realize the calculation of fractal dimension, edge parameters, axial coefficient and sphericity.

[0123] The fractal dimension is calculated as follows:

[0124]

[0125] In the formula: D is the fractal dimension; N(r) is the number of boxes, and r is the scaling factor of the box size;

[0126] The calculation method for the angle parameters is as follows:

[0127] L = (P A / P E ) 2

[0128] In the formula: L is the angularity parameter, P A P represents the true perimeter of the aggregate particles. E The equivalent ellipse circumference;

[0129] The axial coefficient is calculated as follows:

[0130] A = T / W

[0131] In the formula: A is the axial coefficient; T and W are the lengths of the major and minor axes of the equivalent ellipse of the two-dimensional projection of the aggregate, respectively;

[0132] The method for calculating sphericity is as follows:

[0133] C = (P A ) 2 / [4π(S A ) 2 ]

[0134] In the formula: C represents roundness, P A S represents the true perimeter of the aggregate particles. A This represents the actual area of ​​the aggregate.

[0135] In step (3), the established linear direct proportional function of the wear loss rate of various aggregates at different wear stages and the change rate of the optimal morphology index is as follows:

[0136] LA = k D *(|F0-F n |)

[0137] In the formula: k D F0 is the ratio coefficient between the wear loss rate and the rate of change of the optimal morphology index; F0 is the optimal morphology index value of the aggregate before wear.n α represents the optimal morphology index value of the aggregate after wear; LA represents the wear loss rate.

[0138] In step (4), the specific grinding method is to use a grinding mill with a mesh size of 800 or higher to obtain aggregate powder, with each type of aggregate powder weighing no less than 1g and grinding time no less than 5 minutes; then, XRD testing is performed using an X-ray diffractometer, and the mineral phase composition and mass fraction of the aggregate are determined by comparing with a PDF card library.

[0139] In step (5), the specific method for polishing is to use sandpaper with grits of P800, P2000, P3000, P5000, and P7000 from low to high to polish until smooth; among them, the polishing time for P800, P2000, and P3000 should not be less than 5 minutes, and the polishing time for P5000 and P7000 should be more than 10 minutes.

[0140] In step (5), when grinding and polishing, sandpaper is first used for grinding, and then 80,000 mesh Al2O3 suspension is used for further polishing.

[0141] In step (6), the indentation area for the indentation test should be a square area with a side length of 250 μm, and areas with obvious defects should be avoided; the loading and unloading method is as follows: 10s loading, 5s holding load, 10s unloading, and the peak load is 5 × 10 -3 N; the distance between adjacent indentation points is 20μm or more;

[0142] There should be no fewer than 3 measurement points for each mineral phase.

[0143] The specific method for step (8) is as follows:

[0144] (8.1) The pore structure of the aggregate and the mechanical properties of the soft minerals are initially homogenized into the mechanical properties of the porous matrix solid phase, wherein the soft minerals are the minerals with the smallest Young's modulus test results in the aggregate:

[0145]

[0146] k s =E s / 3(1-2υ s )

[0147] μ s =E s / 2(1+υ s )

[0148]

[0149] In the formula: k low and μ low These are the bulk modulus and shear modulus of the porous matrix after initial homogenization, respectively. V represents the porosity of the homogenized matrix, and m represents the porosity obtained from mercury intrusion porosimetry of the aggregate. r k represents the mass fraction of soft minerals. s and μ s These are the bulk modulus and shear modulus of soft minerals, respectively; E s Young's modulus of soft minerals; υ s The Poisson's ratio for soft minerals;

[0150] (8.2) The mechanical properties of the hard minerals and porous matrix solid phase in the aggregate are homogenized twice to obtain the macroscopic mechanical properties of the material. The hard minerals are all minerals except the mineral with the lowest Young's modulus in the test results.

[0151]

[0152] k r =E r / 3(1-2υ r )

[0153] μ r =E r / 2(1+υ r )

[0154] In the formula: The macroscopic equivalent shear modulus of the aggregate after secondary homogenization; E represents the macroscopic equivalent bulk modulus of the aggregate after secondary homogenization. r Young's modulus for various hard mineral phases; f r k represents the mass fraction of various hard mineral phases. r μ r These are the bulk modulus and shear modulus of various hard mineral phases, respectively; υ r denoted by r, where r represents the Poisson's ratio for each type of hard mineral; n represents the total number of hard mineral phases; if r is 0, it is considered that there are no hard minerals.

[0155] (8.3) After obtaining the equivalent mechanical parameters of each phase medium, the equivalent macroscopic Young's modulus of the homogenized aggregate is calculated using the following formula:

[0156]

[0157] In the formula: E hom The equivalent macroscopic Young's modulus of the homogenized aggregate.

[0158] Example 3

[0159] A method for predicting the wear resistance of aggregate surfaces includes the following steps:

[0160] Step (1): Los Angeles abrasion test is conducted on various aggregates, and morphological characteristics are tested on the aggregates before abrasion and after each abrasion test. The morphological index of each aggregate is calculated. The morphological index includes fractal dimension, edge angle parameter, axial coefficient and sphericity.

[0161] Step (2): Using the number of wear cycles and aggregate type as variables, a two-way ANOVA was used to analyze the correlation between various morphological indicators and different wear cycles and different aggregate types; the morphological indicator with the largest F value in the F test results was used as the best morphological indicator to characterize the wear resistance performance of aggregates.

[0162] Step (3) The aggregate is subjected to multiple abrasions, each abrasion is 500 revolutions, and the abrasion loss rate and morphological index are measured after each abrasion. A first-order direct proportional function of the abrasion loss rate of various aggregates and the change rate of the best morphological index is established at different abrasion stages.

[0163] Step (4): Grind to obtain various aggregate powders, and determine the aggregate mineral phases and their mass fractions by XRD.

[0164] Step (5): Prepare cubic samples of various aggregates, grind and polish them, clean them and dry them; the side length of the cubic sample is 15mm.

[0165] Step (6): Observe the cubic sample block with the optical microscope built into the indenter to determine the distribution range of minerals with a mass fraction of more than 5% in each phase of the aggregate; then, perform nanoindentation test on it to obtain the nanoscale Young's modulus, bulk modulus, shear modulus and Poisson's ratio of each mineral phase in the aggregate.

[0166] Step (7): Prepare various aggregate cube samples with a size of 10mm, and use mercury intrusion porosimetry to obtain the aggregate porosity;

[0167] Step (8): Calculate the equivalent macroscopic Young's modulus of various aggregates based on the MT homogenization method;

[0168] Step (9): Establish the equivalent macroscopic Young's modulus of various aggregates and their corresponding proportionality coefficients k. D Linear regression function:

[0169] k D =A 0* E hom +C0

[0170] In the formula: A0 and C0 are both fitting constants, E hom k is the equivalent macroscopic Young's modulus of the aggregate. D This is the proportionality coefficient between the wear loss rate and the rate of change of the optimal morphological index;

[0171] Step (10) corrects the first-order proportional function established in step (3) to obtain the prediction model based on Young's modulus and Los Angeles wear loss rate:

[0172] LA = (A 0* E hom +C0)|F0-F n |

[0173] Then, the wear loss rate prediction model is used to predict the wear loss rate of various aggregates, and the prediction results are used as the wear resistance of the aggregate surface.

[0174] In step (1), the abrasion test is conducted in accordance with the relevant provisions of the coarse aggregate abrasion test (Los Angeles method) (T0317-2024) in the "Specifications for Aggregate Testing in Highway Engineering" (JTG3432-2024);

[0175] Each type of aggregate underwent six abrasion tests, with each test lasting 500 revolutions. The cumulative abrasion loss rate was calculated after each test, as follows:

[0176]

[0177] In the formula: LA n The cumulative wear loss rate after the nth wear test is m0, where m is the aggregate mass before wear. n The residual mass of aggregate after the nth abrasion test.

[0178] In step (1), when testing the morphological characteristics, the number of aggregate particles selected for each type should not be less than 50.

[0179] The specific method for morphological feature testing is as follows: use a camera with more than 10 million pixels to acquire the morphological image of each aggregate, import it into ImageJ for morphological feature quantitative analysis, call the Analyze module in ImageJ to perform particle size analysis, and realize the calculation of fractal dimension, edge parameters, axial coefficient and sphericity.

[0180] The fractal dimension is calculated as follows:

[0181]

[0182] In the formula: D is the fractal dimension; N(r) is the number of boxes, and r is the scaling factor of the box size;

[0183] The calculation method for the angle parameters is as follows:

[0184] L = (P A / P E ) 2

[0185] In the formula: L is the angularity parameter, P A P represents the true perimeter of the aggregate particles. E The equivalent ellipse perimeter;

[0186] The axial coefficient is calculated as follows:

[0187] A = T / W

[0188] In the formula: A is the axial coefficient; T and W are the lengths of the major and minor axes of the equivalent ellipse of the two-dimensional projection of the aggregate, respectively;

[0189] The method for calculating sphericity is as follows:

[0190] C = (P A ) 2 / [4π(S A ) 2 ]

[0191] In the formula: C represents roundness, P A S represents the true perimeter of the aggregate particles. A This represents the actual area of ​​the aggregate.

[0192] In step (3), the established linear direct proportional function of the wear loss rate of various aggregates at different wear stages and the change rate of the optimal morphology index is as follows:

[0193] LA = k D *(|F0-F n |)

[0194] In the formula: k D F0 is the ratio coefficient between the wear loss rate and the rate of change of the optimal morphology index; F0 is the optimal morphology index value of the aggregate before wear. n α represents the optimal morphology index value of the aggregate after wear; LA represents the wear loss rate.

[0195] In step (4), the specific grinding method is to use a grinding mill with a mesh size of 800 or higher to obtain aggregate powder, with each type of aggregate powder weighing no less than 1g and grinding time no less than 5 minutes; then, XRD testing is performed using an X-ray diffractometer, and the mineral phase composition and mass fraction of the aggregate are determined by comparing with a PDF card library.

[0196] In step (5), the specific method for polishing is to use sandpaper with grits of P800, P2000, P3000, P5000, and P7000 from low to high to polish until smooth; among them, the polishing time for P800, P2000, and P3000 should not be less than 5 minutes, and the polishing time for P5000 and P7000 should be more than 10 minutes.

[0197] In step (5), when grinding and polishing, sandpaper is first used for grinding, and then 80,000 mesh Al2O3 suspension is used for further polishing.

[0198] In step (6), the indentation area for the indentation test should be a square area with a side length of 300 μm, and areas with obvious defects should be avoided; the loading and unloading method is as follows: 10s loading, 5s holding load, 10s unloading, and the peak load is 5×10 -3 N; the distance between adjacent indentation points is 20μm or more;

[0199] There should be no fewer than 3 measurement points for each mineral phase.

[0200] The specific method for step (8) is as follows:

[0201] (8.1) The pore structure of the aggregate and the mechanical properties of the soft minerals are initially homogenized into the mechanical properties of the porous matrix solid phase, wherein the soft minerals are the minerals with the smallest Young's modulus test results in the aggregate:

[0202]

[0203] k s =E s / 3(1-2υ s )

[0204] μ s =E s / 2(1+υ s )

[0205]

[0206] In the formula: k low and μ low These are the bulk modulus and shear modulus of the porous matrix after initial homogenization, respectively. V represents the porosity of the homogenized matrix, and m represents the porosity obtained from mercury intrusion porosimetry of the aggregate. r k represents the mass fraction of soft minerals. s and μ s These are the bulk modulus and shear modulus of soft minerals, respectively; E s Young's modulus of soft minerals; υ s The Poisson's ratio for soft minerals;

[0207] (8.2) The mechanical properties of the hard minerals and porous matrix solid phase in the aggregate are homogenized twice to obtain the macroscopic mechanical properties of the material. The hard minerals are all minerals except the mineral with the lowest Young's modulus in the test results.

[0208]

[0209] k r =E r / 3(1-2υ r )

[0210] μ r =E r / 2(1+υ r )

[0211] In the formula: The macroscopic equivalent shear modulus of the aggregate after secondary homogenization; E represents the macroscopic equivalent bulk modulus of the aggregate after secondary homogenization. r Young's modulus for various hard mineral phases; f r k represents the mass fraction of various hard mineral phases. r μ r These are the bulk modulus and shear modulus of various hard mineral phases, respectively; υ r denoted by r, where r represents the Poisson's ratio for each type of hard mineral; n represents the total number of hard mineral phases; if r is 0, it is considered that there are no hard minerals.

[0212] (8.3) After obtaining the equivalent mechanical parameters of each phase medium, the equivalent macroscopic Young's modulus of the homogenized aggregate is calculated using the following formula:

[0213]

[0214] In the formula: E hom The equivalent macroscopic Young's modulus of the homogenized aggregate.

[0215] Example 4

[0216] A method for predicting the wear resistance of aggregate surfaces includes the following steps:

[0217] Step (1): Los Angeles abrasion test is conducted on various aggregates, and morphological characteristics are tested on the aggregates before abrasion and after each abrasion test. The morphological index of each aggregate is calculated. The morphological index includes fractal dimension, edge angle parameter, axial coefficient and sphericity.

[0218] Step (2): Using the number of wear cycles and aggregate type as variables, a two-way ANOVA was used to analyze the correlation between various morphological indicators and different wear cycles and different aggregate types; the morphological indicator with the largest F value in the F test results was used as the best morphological indicator to characterize the wear resistance performance of aggregates.

[0219] Step (3) The aggregate is subjected to multiple abrasions, each abrasion is 400 revolutions, and the abrasion loss rate and morphological index are measured after each abrasion. A first-order direct proportional function of the abrasion loss rate of various aggregates and the change rate of the best morphological index is established at different abrasion stages.

[0220] Step (4): Grind to obtain various aggregate powders, and determine the aggregate mineral phases and their mass fractions by XRD.

[0221] Step (5): Prepare cubic samples of various aggregates, grind and polish them, clean them and dry them; the side length of the cubic sample is 10mm.

[0222] Step (6): Observe the cubic sample block with the optical microscope built into the indenter to determine the distribution range of minerals with a mass fraction of more than 5% in each phase of the aggregate; then, perform nanoindentation test on it to obtain the nanoscale Young's modulus, bulk modulus, shear modulus and Poisson's ratio of each mineral phase in the aggregate.

[0223] Step (7): Prepare various aggregate cube samples with a size of 8mm, and use mercury intrusion porosimetry to obtain the aggregate porosity;

[0224] Step (8): Calculate the equivalent macroscopic Young's modulus of various aggregates based on the MT homogenization method;

[0225] Step (9): Establish the equivalent macroscopic Young's modulus of various aggregates and their corresponding proportionality coefficients k. D Linear regression function:

[0226] k D =A0*E hom +C0

[0227] In the formula: A0 and C0 are both fitting constants, E hom k is the equivalent macroscopic Young's modulus of the aggregate. D This is the ratio coefficient between the wear loss rate and the rate of change of the optimal morphological index;

[0228] Step (10) corrects the first-order proportional function established in step (3) to obtain the prediction model based on Young's modulus and Los Angeles wear loss rate:

[0229] LA=(A0*E hom +C0)|F0-F n |

[0230] Then, the wear loss rate prediction model is used to predict the wear loss rate of various aggregates, and the prediction results are used as the wear resistance of the aggregate surface.

[0231] In step (1), the abrasion test is conducted in accordance with the relevant provisions of the coarse aggregate abrasion test (Los Angeles method) (T0317-2024) in the "Specifications for Aggregate Testing in Highway Engineering" (JTG3432-2024);

[0232] Five abrasion tests were conducted on each type of aggregate, with each test lasting 400 revolutions. The cumulative abrasion loss rate was calculated after each test, as follows:

[0233]

[0234] In the formula: LA n The cumulative wear loss rate after the nth wear test is m0, where m is the aggregate mass before wear. n The residual mass of aggregate after the nth abrasion test.

[0235] In step (1), when testing the morphological characteristics, the number of aggregate particles selected for each type should not be less than 50.

[0236] The specific method for morphological feature testing is as follows: use a camera with more than 10 million pixels to acquire the morphological image of each aggregate, import it into ImageJ for morphological feature quantitative analysis, call the Analyze module in ImageJ to perform particle size analysis, and realize the calculation of fractal dimension, edge parameters, axial coefficient and sphericity.

[0237] The fractal dimension is calculated as follows:

[0238]

[0239] In the formula: D is the fractal dimension; N(r) is the number of boxes, and r is the scaling factor of the box size;

[0240] The calculation method for the angle parameters is as follows:

[0241] L = (P A / P E ) 2

[0242] In the formula: L is the angularity parameter, P A P represents the true perimeter of the aggregate particles. E The equivalent ellipse perimeter;

[0243] The axial coefficient is calculated as follows:

[0244] A = T / W

[0245] In the formula: A is the axial coefficient; T and W are the lengths of the major and minor axes of the equivalent ellipse of the two-dimensional projection of the aggregate, respectively;

[0246] The method for calculating sphericity is as follows:

[0247] C = (P A ) 2 / [4π(S A ) 2 ]

[0248] In the formula: C represents roundness, P A S represents the true perimeter of the aggregate particles. A This represents the actual area of ​​the aggregate.

[0249] In step (3), the established linear direct proportional function of the wear loss rate of various aggregates at different wear stages and the change rate of the optimal morphology index is as follows:

[0250] LA = k D *(|F0-F n |)

[0251] In the formula: k D F0 is the ratio coefficient between the wear loss rate and the rate of change of the optimal morphology index; F0 is the optimal morphology index value of the aggregate before wear. n α represents the optimal morphology index value of the aggregate after wear; LA represents the wear loss rate.

[0252] In step (4), the specific grinding method is to use a grinding mill with a mesh size of 800 or higher to obtain aggregate powder, with each type of aggregate powder weighing no less than 1g and grinding time no less than 5 minutes; then, XRD testing is performed using an X-ray diffractometer, and the mineral phase composition and mass fraction of the aggregate are determined by comparing with a PDF card library.

[0253] In step (5), the specific method for polishing is to use sandpaper with grits of P800, P2000, P3000, P5000, and P7000 from low to high to polish until smooth; among them, the polishing time for P800, P2000, and P3000 should not be less than 5 minutes, and the polishing time for P5000 and P7000 should be more than 10 minutes.

[0254] In step (5), when grinding and polishing, sandpaper is first used for grinding, and then 80,000 mesh Al2O3 suspension is used for further polishing.

[0255] In step (6), the indentation area during the indentation test is a square area with a side length of 280 μm, and areas with obvious defects should be avoided; the loading and unloading method is as follows: 10s loading, 5s holding load, 10s unloading, and the peak load is 5 × 10 -3 N; the distance between adjacent indentation points is 20μm or more;

[0256] There should be no fewer than 3 measurement points for each mineral phase.

[0257] The specific method for step (8) is as follows:

[0258] (8.1) The pore structure of the aggregate and the mechanical properties of the soft minerals are initially homogenized into the mechanical properties of the porous matrix solid phase, wherein the soft minerals are the minerals with the smallest Young's modulus test results in the aggregate:

[0259]

[0260] k s =E s / 3(1-2υ s )

[0261] μ s =E s / 2(1+υ s )

[0262]

[0263] In the formula: k low and μ low These are the bulk modulus and shear modulus of the porous matrix after initial homogenization, respectively. V represents the porosity of the homogenized matrix, and m represents the porosity obtained from mercury intrusion porosimetry of the aggregate. r k represents the mass fraction of soft minerals. s and μ s These are the bulk modulus and shear modulus of soft minerals, respectively; E s Young's modulus of soft minerals; υ s The Poisson's ratio for soft minerals;

[0264] (8.2) The mechanical properties of the hard minerals and porous matrix solid phase in the aggregate are homogenized twice to obtain the macroscopic mechanical properties of the material. The hard minerals are all minerals except the mineral with the lowest Young's modulus in the test results.

[0265]

[0266] k r =E r / 3(1-2υ r )

[0267] μ r =E r / 2(1+υ r )

[0268] In the formula: The macroscopic equivalent shear modulus of the aggregate after secondary homogenization; E represents the macroscopic equivalent bulk modulus of the aggregate after secondary homogenization. r Young's modulus for various hard mineral phases; f r k represents the mass fraction of various hard mineral phases. r μ r These are the bulk modulus and shear modulus of various hard mineral phases, respectively; υ r denoted by r, where r represents the Poisson's ratio for each type of hard mineral; n represents the total number of hard mineral phases; if r is 0, it is considered that there are no hard minerals.

[0269] (8.3) After obtaining the equivalent mechanical parameters of each phase medium, the equivalent macroscopic Young's modulus of the homogenized aggregate is calculated using the following formula:

[0270]

[0271] In the formula: E hom The equivalent macroscopic Young's modulus of the homogenized aggregate.

[0272] Example 5

[0273] A method for predicting the surface wear resistance of aggregates employs a prediction model based on Young's modulus and Los Angeles wear loss rate, as shown in the following formula:

[0274] LA=(-1.002×E hom +649.000)|F0-F n |

[0275] The prediction model is used to predict the wear loss rate of various aggregates, and the prediction results are used as a method for evaluating the wear resistance of aggregate surfaces; the aggregate types include basalt, granite, limestone and bauxite.

[0276] Application Examples

[0277] A method for predicting the wear resistance of aggregate surfaces includes the following steps:

[0278] Step (1) involves conducting abrasion tests on various aggregates, and performing morphological characteristic tests on the aggregates before and after each abrasion test. The morphological indices for each aggregate are then calculated, including fractal dimension, angular parameters, axial coefficient, and sphericity. The final calculation results are shown below. Figure 1 As shown;

[0279] Specifically, abrasion tests were conducted according to the relevant provisions of the "Specifications for Aggregate Testing in Highway Engineering" (JTG 3432-2024) regarding the coarse aggregate abrasion test (Los Angeles method) (T0317-2024). Five abrasion tests were performed on each type of aggregate, with each test consisting of 500 revolutions. The cumulative abrasion loss rate was calculated after each test, as follows:

[0280]

[0281] In the formula: LA n denoted as the cumulative wear loss rate after the nth wear, m0 is the aggregate mass before wear, and mn is the residual aggregate mass after the nth wear.

[0282] Before and after each abrasion test, a certain number of aggregates were selected for morphological characteristic testing, and the number of particles should not be less than 50.

[0283] The specific method for morphological feature testing is as follows: A high-definition camera with over 10 megapixels is used to acquire aggregate morphological images one by one. These images are then imported into ImageJ for morphological feature quantification analysis. The Analyze module in ImageJ is used to perform particle size analysis, calculating fractal dimension, edge parameters, axial coefficient, and sphericity. The method for calculating fractal dimension is as follows:

[0284]

[0285] In the formula: D is the fractal dimension; N(r) is the number of boxes, and r is the scaling factor of the box size;

[0286] The calculation method for the angle parameters is as follows:

[0287] L = (P A / P E ) 2

[0288] In the formula: L is the angularity parameter, P A P represents the true perimeter of the aggregate particles. E The equivalent ellipse circumference;

[0289] The axial coefficient is calculated as follows:

[0290] A = T / W

[0291] In the formula: A is the axial coefficient; T and W are the lengths of the major and minor axes of the equivalent ellipse of the two-dimensional projection of the aggregate, respectively;

[0292] The method for calculating sphericity is as follows:

[0293] C = (P A ) 2 / [4π(S A ) 2 ]

[0294] In the formula: C represents roundness, P A S represents the true perimeter of the aggregate particles. A This represents the actual area of ​​the aggregate.

[0295] Step (2): Using the number of wears and aggregate type as variables, the two-way ANOVA method based on SPSS is used to conduct correlation analysis between various morphological indicators and different wears and aggregate types. The morphological indicator with the largest F value in the F test results is used as the best morphological indicator to characterize the wear resistance performance of aggregate.

[0296] The calculation process for the F-value is as follows.

[0297] F=[SSR / (m-1)] / [SSE / (nm)]=MSR / MSE~F(m-1,nm)

[0298] In the formula: SSR represents the regression sum of squares, SSE represents the residual sum of squares, m represents the number of factor levels, n represents the total number of observations, MSR represents the regression mean square, and MSE represents the residual mean square.

[0299] In this example, the fractal dimension was calculated to be the best morphological index, as shown in Table 1.

[0300] Table 1. Results of analysis of variance for morphological parameters considering aggregate type.

[0301]

[0302] Wherein: F crit As a criterion for significance, F a＝0.05 That is, the 95% confidence interval, F a＝0.05 >F crit This indicates that the two are significantly related, and F a＝0.05 The larger the value, the more significant the correlation.

[0303] Step (3): Taking 300 cycles as one wear stage, after each wear stage, the wear loss rate and morphological index are measured, and a linear direct proportional function is established between the wear loss rate of various aggregates and the change rate of the optimal morphological index at different wear stages:

[0304] LA = k D* (|F0-F n |)

[0305] In the formula: k D F0 is the proportionality coefficient between the wear loss rate and the rate of change of the fractal dimension; F0 is the fractal dimension value of the aggregate before wear. n LA represents the fractal dimension of the aggregate after wear; LA represents the wear loss rate; the regression results of the fractal dimension change rate and the wear loss rate are as follows: Figure 2 As shown in the figure, △F is |F0-F n |

[0306] Step (4): Grind to obtain various aggregate powders, and determine the aggregate mineral phases and their mass fractions by XRD.

[0307] The specific grinding method is to use a grinding mill of 800 mesh or higher to obtain aggregate powder, with each type of aggregate powder weighing no less than 1g and grinding time no less than 5 minutes; then, XRD test is performed using an X-ray diffractometer, and the mineral phase composition and mass fraction of the aggregate are determined by comparing with a PDF card library.

[0308] Step (5): Make cubic samples of various aggregates with a side length of 10mm, grind and polish them, clean them and dry them.

[0309] Specifically, select relatively regular aggregate particles and grind them into cubic samples with a side length of 10mm. Then, polish them using sandpaper with grits ranging from low to high: P800, P2000, P3000, P5000, and P7000, until the sample surface is sufficiently smooth. The polishing time for P800, P2000, and P3000 sandpaper should be no less than 5 minutes, while the polishing time for P5000 and P7000 sandpaper should be more than 10 minutes. If the sample is difficult to polish smoothly, an 80,000-mesh Al2O3 suspension can be used for further polishing. After polishing, clean and dry the sample for later use.

[0310] Step (6): Observe the cubic sample block using the optical microscope attached to the indenter to determine the distribution range of minerals with a mass fraction of more than 5% in various aggregate mineral phases. Subsequently, perform nanoindentation tests on the sample to obtain the nanoscale Young's modulus, bulk modulus, shear modulus, and Poisson's ratio of each aggregate mineral phase, providing basic parameters for the calculation of the equivalent macroscopic Young's modulus.

[0311] Specifically, the indentation area for the indentation test should be a square area with a side length of 300 μm, avoiding areas with obvious defects or poor surface uniformity; the loading and unloading method is: 10s loading, 5s holding load, and 10s unloading, with a peak load of 5 × 10⁻⁶. -3 N; the spacing between adjacent indentation points should be at least 20 μm. Obtain the bulk modulus, shear modulus, and Young's modulus of each mineral phase in the aggregate; no fewer than 3 measurement points should be used for each mineral phase; the indentation areas and mineral phases of various aggregates should be as follows: Figure 3 As shown;

[0312] This example, based on actual measurements, yielded the Young's moduli of the following four types of aggregate mineral phases, as shown in Table 2; the test results of the Young's moduli of each mineral phase in the aggregate are as follows: Figure 4 As shown;

[0313] Table 2 Young's modulus of each mineral phase in aggregates

[0314]

[0315] Step (7): Prepare aggregate cube samples with dimensions of 10mm×10mm×10mm, and obtain the porosity of various aggregates based on the mercury intrusion porosimetry method.

[0316] Specifically, before testing, the soil and rock samples were treated with freeze-drying to avoid pore shrinkage. Then, the samples were placed in mercury, ensuring complete immersion. After immersion, the pressure was gradually increased to allow the mercury to penetrate the sample pores. Once a certain pressure was reached, the sample pores were completely filled with mercury. At this point, the pressure was gradually reduced, and the mercury was released from the sample. During the adsorption and release process, the adsorption and release volumes of mercury were measured using a volumetric meter to obtain the aggregate porosity. The porosity calculation formula is as follows;

[0317]

[0318] In the formula: φ is the aggregate porosity, ΔV(P) is the volume increment of mercury entering the pores under different pressures, and V total This represents the total volume of aggregate.

[0319] Step (8): Calculate the equivalent macroscopic Young's modulus of various aggregates based on the MT homogenization method;

[0320] The specific method is as follows:

[0321] (8.1) Homogenize the pore structure of aggregates and the mechanical properties of soft minerals into the mechanical properties of a porous matrix solid phase:

[0322]

[0323] k s =E s / 3(1-2υ s )

[0324] μ s =E s / 2(1+υ s )

[0325] In the formula: k low and μ low These are the bulk modulus and shear modulus of the porous matrix after initial homogenization, respectively. k is the porosity of the matrix. s and μ s These are the bulk modulus and shear modulus of soft minerals, respectively; E s The Young's modulus of the soft mineral is obtained from the indentation test results; υ s The Poisson's ratio for soft minerals is obtained from indentation test results;

[0326] (8.2) Homogenize the mechanical properties of the hard minerals and porous matrix solid phase of the aggregate into the macroscopic mechanical properties of the material:

[0327]

[0328] k r =E r / 3(1-2υ r )

[0329] μ r =E r / 2(1+υ r )

[0330] In the formula: The macroscopic equivalent shear modulus of the aggregate after secondary homogenization; E represents the macroscopic equivalent bulk modulus of the aggregate after secondary homogenization. r represents the Young's modulus of various hard mineral phases, obtained from indentation test results; fr represents the mass fraction of various hard mineral phases, obtained from XRD test results; k r μ r These are the bulk modulus and shear modulus of various hard mineral phases, respectively; υ r The Poisson's ratio for various hard minerals can be obtained from indentation test results; n represents the total number of hard mineral phases; if r is 0, it is considered that there are no hard minerals.

[0331] (8.3) After obtaining the equivalent mechanical parameters of each phase medium, the equivalent macroscopic Young's modulus of the homogenized aggregate is calculated using the following formula:

[0332]

[0333] In the formula: E hom The equivalent macroscopic Young's modulus of the homogenized aggregate.

[0334] In this example, the equivalent macroscopic Young's modulus of four types of aggregates was calculated, as shown in Table 3;

[0335] Table 3. Calculation results of equivalent macroscopic Young's modulus

[0336] Aggregate type MT method(Gpa) Basalt 107.0502 granite 71.2265 limestone 67.4245 bauxite 290.9283

[0337] Step (9), with Figure 5 As shown, the equivalent macroscopic Young's modulus and the proportionality coefficient k are established. D Linear regression function:

[0338] k D =A0*E hom +C0

[0339] In the formula: A0 and C0 are both fitting constants, E hom k is the equivalent macroscopic Young's modulus of the aggregate. D This is the ratio coefficient between the wear loss rate and the rate of change of the optimal morphological index;

[0340] Step (10): Correct the first-order proportional function established in step (3) to obtain the prediction model based on Young's modulus and wear loss rate:

[0341] LA=(A0*E hom +C0)|F0-F n |

[0342] Then, the abrasion loss rate of various aggregates is predicted using the prediction model, and the prediction results are used as a method for evaluating the abrasion resistance of aggregate surfaces.

[0343] This example establishes a method for predicting the abrasion resistance of aggregates based on basalt, granite, limestone, and bauxite, and the results have high accuracy (Table 4).

[0344] Table 4. Prediction Model Based on Young's Modulus and Los Angeles Wear Loss Rate

[0345] Abrasion resistance index Fitting parameters Fitting results <![CDATA[R 2 ]]> LA <![CDATA[F n ,AND hom ]]> <![CDATA[LA=(-1.002×E hom +649.000)F0-F n ]]> 0.9558

[0346] Based on the obtained prediction model, basalt aggregate was selected for abrasion testing to verify the reliability of the invention. The measured results and prediction results are shown in Table 5.

[0347] Table 5 Error Analysis of Measured and Predicted Results of Abrasion Resistance Index of Basalt Aggregate

[0348]

[0349] Based on the data in Table 5, the prediction error of this invention is controlled within 10%, indicating high reliability. Furthermore, the prediction accuracy gradually improves with increasing wear cycles.

[0350] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A method for predicting the wear resistance of aggregate surfaces, characterized in that, Includes the following steps: Step (1): Los Angeles abrasion test is conducted on various aggregates, and morphological characteristics are tested on the aggregates before abrasion and after each abrasion test. The morphological index of each aggregate is calculated. The morphological index includes fractal dimension, edge angle parameter, axial coefficient and sphericity. Step (2): Using the number of wear cycles and aggregate type as variables, a two-way ANOVA was used to analyze the correlation between various morphological indicators and different wear cycles and different aggregate types; the morphological indicator with the largest F value in the F test results was used as the best morphological indicator to characterize the wear resistance performance of aggregates. Step (3) The aggregate is subjected to multiple abrasions, with each abrasion rotation being 300-500 revolutions. After each abrasion is completed, the abrasion loss rate and morphological index are measured. A linear direct proportional function of the abrasion loss rate of various aggregates and the change rate of the optimal morphological index is established for different abrasion stages. Step (4): Grind to obtain various aggregate powders, and determine the aggregate mineral phases and their mass fractions by XRD. Step (5): Prepare cubic samples of various aggregates, grind and polish them, clean them and dry them; the side length of the cubic sample is 5-15mm. Step (6): Observe the cubic sample block with the optical microscope built into the indenter to determine the distribution range of minerals with a mass fraction of more than 5% in each phase of the aggregate; then, perform nanoindentation test on it to obtain the nanoscale Young's modulus, bulk modulus, shear modulus and Poisson's ratio of each mineral phase in the aggregate. Step (7): Prepare various aggregate cube samples with a size of 5-10mm, and use mercury intrusion porosimetry to obtain the aggregate porosity; Step (8): Calculate the equivalent macroscopic Young's modulus of various aggregates based on the MT homogenization method; Step (9): Establish the equivalent macroscopic Young's modulus of various aggregates and their corresponding proportionality coefficients k. D Linear regression function: k D =A 0* E hom +C0 In the formula: A0 and C0 are both fitting constants, E hom k is the equivalent macroscopic Young's modulus of the aggregate. D This is the proportionality coefficient between the wear loss rate and the rate of change of the optimal morphological index; Step (10) corrects the first-order proportional function established in step (3) to obtain the prediction model based on Young's modulus and Los Angeles wear loss rate: LA=(A 0* Yes hom +C0)|F0-F n | Then, the wear loss rate prediction model is used to predict the wear loss rate of various aggregates, and the prediction results are used as the wear resistance of the aggregate surface.

2. The method for predicting the wear resistance of aggregate surface according to claim 1, characterized in that, In step (1), the abrasion test is conducted in accordance with the relevant provisions of the coarse aggregate abrasion test (Los Angeles method) (T0317-2024) in the "Specifications for Aggregate Testing in Highway Engineering" (JTG3432-2024); Each type of aggregate underwent 4-6 abrasion tests, with each test lasting 300-500 revolutions. After each abrasion test, the cumulative abrasion loss rate was calculated, as follows: In the formula: LA n The cumulative wear loss rate after the nth wear test is m0, where m is the aggregate mass before wear. n The residual mass of aggregate after the nth abrasion test.

3. The method for predicting the wear resistance of aggregate surface according to claim 1, characterized in that, In step (1), when testing the morphological characteristics, the number of aggregate particles selected for each type should not be less than 50. The specific method for morphological feature testing is as follows: use a camera with more than 10 million pixels to acquire the morphological image of each aggregate, import it into ImageJ for morphological feature quantitative analysis, call the Analyze module in ImageJ to perform particle size analysis, and realize the calculation of fractal dimension, edge parameters, axial coefficient and sphericity. The fractal dimension is calculated as follows: In the formula: D is the fractal dimension; N(r) is the number of boxes, and r is the scaling factor of the box size; The calculation method for the angle parameters is as follows: L=(P A / P E ) 2 In the formula: L is the angularity parameter, P A P represents the true perimeter of the aggregate particles. E The equivalent ellipse circumference; The axial coefficient is calculated as follows: A = T / W In the formula: A is the axial coefficient; T and W are the lengths of the major and minor axes of the equivalent ellipse of the two-dimensional projection of the aggregate, respectively; The method for calculating sphericity is as follows: C=(P A ) 2 / [4π(S A ) 2 ] In the formula: C represents roundness, P A S represents the true perimeter of the aggregate particles. A This represents the actual area of ​​the aggregate.

4. The method for predicting the surface wear resistance of aggregates according to claim 1, characterized in that, In step (3), the established linear direct proportional function of the wear loss rate of various aggregates at different wear stages and the change rate of the optimal morphology index is as follows: LA=k D *(|F0-F n |) In the formula: k D F0 is the ratio coefficient between the wear loss rate and the rate of change of the optimal morphology index; F0 is the optimal morphology index value of the aggregate before wear. n α represents the optimal morphology index value of the aggregate after wear; LA represents the wear loss rate.

5. The method for predicting the surface wear resistance of aggregates according to claim 1, characterized in that, In step (4), the specific grinding method is to use a grinding mill with a mesh size of 800 or higher to obtain aggregate powder, with each type of aggregate powder weighing no less than 1g and grinding time no less than 5 minutes; then, XRD testing is performed using an X-ray diffractometer, and the mineral phase composition and mass fraction of the aggregate are determined by comparing with a PDF card library.

6. The method for predicting the surface wear resistance of aggregates according to claim 1, characterized in that, In step (5), the specific method for polishing is to use sandpaper with grits of P800, P2000, P3000, P5000 and P7000 from low to high to polish until smooth; among them, the polishing time for P800, P2000 and P3000 should not be less than 5 minutes, and the polishing time for P5000 and P7000 should be more than 10 minutes.

7. The method for predicting the wear resistance of aggregate surface according to claim 6, characterized in that, In step (5), when grinding and polishing, sandpaper is first used for grinding, and then 80,000 mesh Al2O3 suspension is used for further polishing.

8. The method for predicting the wear resistance of aggregate surface according to claim 1, characterized in that, In step (6), the indentation area for the indentation test should be a square area with a side length of 250-300 μm, and areas with obvious defects should be avoided; the loading and unloading method is as follows: 10s loading, 5s holding load, 10s unloading, and the peak load is 5×10 -3 N; the distance between adjacent indentation points is 20μm or more; There should be no fewer than 3 measurement points for each mineral phase.

9. The method for predicting the wear resistance of aggregate surface according to claim 1, characterized in that, The specific method for step (8) is as follows: (8.1) The pore structure of the aggregate and the mechanical properties of the soft minerals are initially homogenized into the mechanical properties of the porous matrix solid phase, wherein the soft minerals are the minerals with the smallest Young's modulus test results in the aggregate: k s =E s / 3(1-2υ s ) m s =E s / 2(1+u s ) In the formula: k low and μ low These are the bulk modulus and shear modulus of the porous matrix after initial homogenization, respectively. V represents the porosity of the homogenized matrix, and m represents the porosity obtained from mercury intrusion porosimetry of the aggregate. r k represents the mass fraction of soft minerals. s and μ s These are the bulk modulus and shear modulus of soft minerals, respectively; E s Young's modulus of soft minerals; υ s The Poisson's ratio for soft minerals; (8.2) The mechanical properties of the hard minerals and porous matrix solid phase in the aggregate are homogenized twice to obtain the macroscopic mechanical properties of the material. The hard minerals are all minerals except the mineral with the lowest Young's modulus in the test results. k r =E r / 3(1-2υ r ) m r =E r / 2(1+u r ) In the formula: The macroscopic equivalent shear modulus of the aggregate after secondary homogenization; E represents the macroscopic equivalent bulk modulus of the aggregate after secondary homogenization. r Young's modulus for various hard mineral phases; f r k represents the mass fraction of various hard mineral phases. r μ r These are the bulk modulus and shear modulus of various hard mineral phases, respectively; υ r is the Poisson's ratio for various hard minerals; n represents the total number of hard mineral phase categories; (8.3) After obtaining the equivalent mechanical parameters of each phase medium, the equivalent macroscopic Young's modulus of the homogenized aggregate is calculated using the following formula: In the formula: E hom The equivalent macroscopic Young's modulus of the homogenized aggregate.

10. A method for predicting the wear resistance of aggregate surfaces, characterized in that: The following formula is used to predict the wear loss rate based on Young's modulus and Los Angeles wear rate: LA=(-1.002×E hom +649.000)|F0-F n | The prediction model is used to predict the wear loss rate of various aggregates, and the prediction results are used as a method for evaluating the wear resistance of aggregate surfaces; the aggregate types include basalt, granite, limestone and bauxite.

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