A full-component synergistic design method for colored asphalt mixture

Abstract

This invention is a method for the synergistic design of all components of colored asphalt mixtures, comprising the following steps: S1: Calculating the initial asphalt content based on aggregate gradation and packing theory; S2: Establishing a quantitative relationship model between pigment dosage and color parameters; S3: Establishing a filler dosage correction model based on asphalt adsorption; S4: Constructing an asphalt film thickness correction model considering the influence of pigments and fillers; S5: Calculating the dosage of each component of the asphalt mixture using a mass formula; S6: Determining the final mix proportion through target performance verification and color tolerance control. This invention establishes a multi-level mathematical model of aggregate gradation, asphalt content, and pigment ratio, achieving integrated and precise design from structural performance to aesthetic effect.

Description

Technical Field

[0001] This invention relates to the technical field of road engineering material design and manufacturing, and in particular to a method for the synergistic design of all components of colored asphalt mixture. Background Technology

[0002] The design of colored asphalt mixtures is a multi-objective optimization process that must simultaneously meet both structural mechanical performance and color aesthetic requirements. Current industry-standard design methods suffer from a serious disconnect between design and practical application.

[0003] 1. Fragmented Design Process: The conventional approach is to first perform volumetric design of the mixture (determining aggregate gradation and asphalt content), and then simply add pigments for color adjustment. These two processes are conducted independently, neglecting the impact of pigment addition on the mixture's volumetric parameters and asphalt content.

[0004] 2. The impact of pigments is overlooked: Pigments have a large specific surface area, which can adsorb and "dilute" the effective asphalt, resulting in insufficient actual asphalt film thickness, which in turn affects the durability (water damage, aging) and workability of the mixture.

[0005] 3. Performance and color conflict: When increasing the amount of pigment to achieve the target color, the performance of the mixture may decrease due to the failure to adjust the amount of asphalt; conversely, optimizing the amount of asphalt may affect the already adjusted color effect; it is difficult to balance the two.

[0006] 4. Inconsistent design basis: The determination of aggregate and asphalt content relies on empirical formulas or semi-empirical methods (such as the Marshall method), while the determination of color depends entirely on experience, lacking a unified and accurate mathematical model correlation between each component.

[0007] Therefore, there is an urgent need in this field for a method that can integrate and quantitatively coordinate the design of all components of the mixture (aggregates, asphalt, pigments) to fundamentally resolve the contradiction between performance and color. Summary of the Invention

[0008] This invention aims to address the shortcomings of existing technologies by providing a method for the synergistic design of all components of colored asphalt mixtures. It aims to establish a unified mathematical model framework that organically integrates the calculation of aggregate gradation, asphalt content, and pigment dosage, thereby achieving synergistic design and synchronous optimization of structural performance and aesthetic color. This ensures that the final product meets both road performance requirements and achieves precise color control.

[0009] To achieve the above objectives, the present invention adopts the following technical solution:

[0010] A method for the synergistic design of all components of colored asphalt mixtures includes the following steps:

[0011] S1: Calculate the initial asphalt content based on aggregate gradation and packing theory;

[0012] S2: Establish a quantitative relationship model between pigment dosage and color parameters;

[0013] S3: Establish a filler dosage correction model based on asphalt adsorption;

[0014] S4: Construct a modified asphalt film thickness model that takes into account the effects of pigments and fillers;

[0015] S5: Calculate the dosage of each component in the asphalt mixture using the mass formula;

[0016] S6: Determine the final ratio through target performance verification and color tolerance control.

[0017] In step S1, the initial asphalt dosage is calculated using a theoretical model based on specific surface area:

[0018] P b0 =(SA agg ×FT×ρ agg ) / (1000×G b )×100%;

[0019] Among them, P b0 This represents the initial amount of asphalt used; SA agg ρ represents the aggregate composite specific surface area; FT represents the target asphalt film thickness; agg G represents the apparent density of the aggregate. b This represents the relative density of asphalt.

[0020] Aggregate Synthetic Specific Surface Area SA agg The calculation formula is:

[0021] SA agg =Σ(P i ×K i );

[0022] Among them, P i K represents the mass percentage of the i-th aggregate; i is the specific surface area coefficient of the i-th aggregate, determined by a laser particle size analyzer.

[0023] The mass percentage of aggregate in grade i, P i The values ​​are constrained by the target gradation (usually the median of the standard gradation, or a specific gradation curve required by the engineering design). Based on the measured sieve analysis data of each aggregate grade, the mass percentage of each aggregate grade is obtained by solving the problem using linear programming. The specific calculation steps and formulas are as follows:

[0024] (1) Establish the gradation equilibrium equation:

[0025] If n grades of aggregate are used, then for each sieve opening j, the cumulative sieve residue C of the composite gradation is... j Satisfy T jmin ≤C j ≤T jmax T jmax T jmin These represent the upper and lower limits of the target gradation at sieve aperture j, respectively, and are fitted to the gradation median T. jmid C j The calculation method is as follows:

[0026] C j =P1×S 1j +P2×S 2j +...+P n ×S nj ;

[0027] Among them, C j P1, P2, ..., Pj are the cumulative sieve residues of the synthetic gradation at the j-th sieve aperture; n The mass percentage of each aggregate grade satisfies P1 + P2 + ... + P n =100%; S 1j S 2j ... S nj n represents the cumulative sieve residue rate of each grade of aggregate at the j-th sieve opening, as measured experimentally (e.g., by standard sieve analysis); n is the total number of aggregate grades; and j is the sieve opening number.

[0028] (2) Solve for the usage Pi of each grade using linear programming:

[0029] With the objective function being "minimizing the sum of squared deviations between the synthesized gradation and the target gradation median", the following constraints are established:

[0030] Objective function: minΣ(C j -T jmid ) 2 ;

[0031] Constraint: 0 ≤ P i ≤100%, ΣP i =100%, T jmin ≤C j ≤T jmax ;

[0032] Solve for the optimal P using linear programming tools (such as Excel Solver or built-in algorithms). i ;

[0033] (3) Verification in conjunction with specific surface area:

[0034] The calculated usage P for each grade i Substitute SA agg=Σ(P i ×K i If the calculated SA agg Exceeding reasonable limits (e.g., AC-13 graded SA) agg Typically 6-8m 2 / kg), then fine-tune P i (Prioritize adjusting the amount of coarse aggregate, for SA) agg (More significant impact) to ensure SA agg Adapted to subsequent initial asphalt usage calculations.

[0035] In step S2, the color parameter C is the value measured by the colorimeter. (Brightness) (Red-Green Value) (Yellow-blue value), or the calculated chromaticity value; pigment content P p The percentage (%) of pigment in the total mass of asphalt mixture; the quantitative relationship model between pigment content and color parameters includes:

[0036] (1) Linear model for a single pigment: C = k1 × P p +b;

[0037] Wherein, k1 is the color efficiency coefficient, which represents the rate of change of color parameters for each additional unit of pigment dosage. This coefficient is closely related to the tinting strength of the pigment itself and the color of the aggregate; b is the base color parameter, which is the color parameter value when the pigment dosage is 0 (i.e., pure aggregate + asphalt), representing the base color of the mixture.

[0038] (2) Nonlinear saturation model for a single pigment: C=C max -(C max -b)×exp(-k2×P p );

[0039] Among them, C max is the color saturation value, which is theoretically the limit value that the color parameter approaches when the amount of pigment is infinite; b is the basic color parameter; e is the natural constant; k2 is the coloring rate constant. The larger the value of k2, the less pigment is needed to achieve the saturated color and the stronger the pigment's tinting strength.

[0040] (3) Multi-pigment synergistic model: =β0+Σ(β i ×P i );

[0041] =γ0+Σ(γ i ×P i );

[0042] =δ0+Σ(δ i ×Pi );

[0043] in, , , β0, γ0, and δ0 represent the lightness, red-green value, and yellow-blue value of the mixture, respectively; β0, γ0, and δ0 represent the lightness, red-green value, and yellow-blue value parameters of pure aggregate + asphalt, respectively, representing the base color of the mixture; P i Different pigment dosages; β i γ i δ i The regression coefficients, determined through extensive experimental data (such as orthogonal experiments), essentially describe the effect of each pigment on the final result. , , The contribution weight of the value.

[0044] In step S3, the filler dosage correction model considers the adsorption effect of the filler on asphalt. The specific steps are as follows:

[0045] P1. Determine the relative bulk density ρ of the aggregate. sb :

[0046] ρ sb =1 / (P1 / ρ s1 +P2 / ρ s2 +...+P n / ρ sn );

[0047] Among them, P1, P2, ..., P n This represents the mass percentage of each aggregate grade; ρ s1 ρ s2 ...ρ sn The apparent density of each grade of aggregate;

[0048] P2, Calculate the basic filler usage P f0 :

[0049] P f0 =[(100-P b0 -ΣP pi )×ρ sb ×(VMA-V V )] / [ρ f [×(100-VMA)];

[0050] Among them, P b0 ΣP represents the initial asphalt content; pi ρ represents the total amount of pigment used. sb ρ is the bulk relative density of the aggregate. fVMA is the apparent relative density of the filler; VMA is the target void fraction of the aggregate determined according to specifications or actual site conditions; V V Determine the target porosity based on engineering requirements;

[0051] P3. Calculate the filler correction amount P based on asphalt adsorption. f :

[0052] P f =P f0 ×[1+(K f / SA agg )×(α f / α avg )];

[0053] Among them, P f0 K represents the basic amount of filler used. f / SA agg The ratio of the specific surface area of ​​the filler to that of the aggregate reflects the relative strength of the filler in adsorbing asphalt; α f To determine the packing correction factor α through adsorption tests; avg α is the average adsorption correction factor for all pigments. avg =Σ(α i ×P pi ) / ΣP pi .

[0054] In step S4, the asphalt film thickness correction model considers the adsorption effect of pigments on asphalt, and the calculation method for the corrected asphalt dosage is as follows:

[0055] P b =P b0 ×(1+Σ(α i ×P pi ×P f ));

[0056] Among them, P b To correct the amount of asphalt used; P b0 P represents the initial amount of asphalt used. pi α represents the percentage (%) of the i-th pigment in the total mass of the asphalt mixture. i P is the adsorption correction coefficient for the i-th pigment. It is calculated by measuring the changes in the three major properties of asphalt (penetration, ductility, and softening point) under different pigment dosages, and referring to the viscosity change rate. f The dosage of filler based on asphalt adsorption is adjusted.

[0057] In step S6, the color tolerance ΔE control adopts a dynamic standard:

[0058] (1) General region: ΔE≤5.0;

[0059] (2) Key landscape areas: ΔE≤3.0;

[0060] (3) Special requirements area: ΔE≤2.0.

[0061] The beneficial effects of this invention are: this invention achieves a leap from "segmented, experience-based" design to "integrated, theoretical" design, and has the following significant advantages:

[0062] 1. Improved scientific design: The dosage of each component is calculated based on theoretical models, reducing reliance on experience and making the design process more transparent and reliable.

[0063] 2. Performance and color synergistic protection: Through the asphalt content correction model, the negative impact of pigments on the volume parameters and performance of the mixture is actively compensated, fundamentally avoiding the problem of sacrificing performance in pursuit of color.

[0064] 3. Optimized design efficiency: The integrated design process avoids repeated adjustments, and the optimal ratio of all components can be determined in one calculation, shortening the design cycle.

[0065] 4. Quality control is moved forward: Color control and performance pre-control are both placed in the mix design stage, which provides a high-quality design benchmark for production and construction, and ensures the quality of the project from the source. Attached Figure Description

[0066] Figure 1 This is a flowchart illustrating the design method steps of the present invention;

[0067] The following will describe in detail, with reference to the accompanying drawings, embodiments of the present invention. Detailed Implementation

[0068] The principles and features of the present invention are described below with reference to the accompanying drawings. The embodiments given are for illustrative purposes only and are not intended to limit the scope of the invention. The invention is described more specifically in the following paragraphs by way of example with reference to the accompanying drawings. The advantages and features of the invention will become clearer from the following description. It should be noted that the drawings are in a very simplified form and use non-precise proportions, and are only used to facilitate and clarify the illustration of the embodiments of the invention.

[0069] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the specification of this invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0070] The present invention will be further described below with reference to the accompanying drawings and embodiments:

[0071] A method for the synergistic design of all components of colored asphalt mixtures, such as Figure 1 As shown, it includes the following steps:

[0072] S1: Calculate the initial asphalt content based on aggregate gradation and packing theory;

[0073] The initial asphalt content was calculated using a theoretical model based on specific surface area:

[0074] P b0 =(SA agg ×FT×ρ agg ) / (1000×G b )×100%;

[0075] Among them, P b0 This represents the initial amount of asphalt used; SA agg ρ represents the aggregate composite specific surface area; FT represents the target asphalt film thickness; agg G represents the apparent density of the aggregate. b This represents the relative density of asphalt.

[0076] Aggregate Synthetic Specific Surface Area SA agg The calculation formula is:

[0077] SA agg =Σ(P i ×K i );

[0078] Among them, P i K represents the mass percentage of the i-th aggregate; i is the specific surface area coefficient of the i-th aggregate, determined by a laser particle size analyzer.

[0079] The mass percentage of aggregate in grade i, P i The values ​​are constrained by the target gradation (usually the median of the standard gradation, or a specific gradation curve required by the engineering design). Based on the measured sieve analysis data of each aggregate grade, the mass percentage of each aggregate grade is obtained by solving the problem using linear programming. The specific calculation steps and formulas are as follows:

[0080] (1) Establish the gradation equilibrium equation:

[0081] If n grades of aggregate are used, then for each sieve opening j, the cumulative sieve residue C of the composite gradation is... j Satisfy T jmin ≤C j ≤T jmax T jmax T jmin These represent the upper and lower limits of the target gradation at sieve aperture j, respectively, and are fitted to the gradation median T. jmid C j The calculation method is as follows:

[0082] C j =P1×S 1j +P2×S 2j +...+P n ×S nj ;

[0083] Among them, C j P1, P2, ..., Pj are the cumulative sieve residues of the synthetic gradation at the j-th sieve aperture; n The mass percentage of each aggregate grade satisfies P1 + P2 + ... + P n =100%; S 1j S 2j ... S nj n represents the cumulative sieve residue rate of each grade of aggregate at the j-th sieve opening, as measured experimentally (e.g., by standard sieve analysis); n is the total number of aggregate grades; and j is the sieve opening number.

[0084] (2) Solve for the usage Pi of each grade using linear programming:

[0085] With the objective function being "minimizing the sum of squared deviations between the synthesized gradation and the target gradation median", the following constraints are established:

[0086] Objective function: minΣ(C j -T jmid ) 2 ;

[0087] Constraint: 0 ≤ P i ≤100%, ΣP i =100%, T jmin ≤C j ≤T jmax ;

[0088] Solve for the optimal P using linear programming tools (such as Excel Solver or built-in algorithms). i ;

[0089] (3) Verification in conjunction with specific surface area:

[0090] The calculated usage P for each grade i Substitute SA agg =Σ(P i ×K i If the calculated SA agg Exceeding reasonable limits (e.g., AC-13 graded SA) agg Typically 6-8m 2 / kg), then fine-tune P i (Prioritize adjusting the amount of coarse aggregate, for SA) agg (More significant impact) to ensure SA aggAdapted to subsequent initial asphalt usage calculations.

[0091] S2: Establish a quantitative relationship model between pigment dosage and color parameters;

[0092] The color parameter C is measured by a colorimeter. (Brightness) (Red-Green Value) (Yellow-blue value), or the calculated chromaticity value; pigment content P p The percentage (%) of pigment in the total mass of asphalt mixture; the quantitative relationship model between pigment content and color parameters includes:

[0093] (1) Linear model for a single pigment: C = k1 × P p +b;

[0094] Wherein, k1 is the color efficiency coefficient, which represents the rate of change of color parameters for each additional unit of pigment dosage. This coefficient is closely related to the tinting strength of the pigment itself and the color of the aggregate; b is the base color parameter, which is the color parameter value when the pigment dosage is 0 (i.e., pure aggregate + asphalt), representing the base color of the mixture.

[0095] (2) Nonlinear saturation model for a single pigment: C=C max -(C max -b)×exp(-k2×P p );

[0096] Among them, C max is the color saturation value, which is theoretically the limit value that the color parameter approaches when the amount of pigment is infinite; b is the basic color parameter; e is the natural constant; k2 is the coloring rate constant. The larger the value of k2, the less pigment is needed to achieve the saturated color and the stronger the pigment's tinting strength.

[0097] (3) Multi-pigment synergistic model: =β0+Σ(β i ×P i );

[0098] =γ0+Σ(γ i ×P i );

[0099] =δ0+Σ(δ i ×P i );

[0100] in, , , β0, γ0, and δ0 represent the lightness, red-green value, and yellow-blue value of the mixture, respectively; β0, γ0, and δ0 represent the lightness, red-green value, and yellow-blue value parameters of pure aggregate + asphalt, respectively, representing the base color of the mixture; P i Different pigment dosages; β i γ i δ i The regression coefficients, determined through extensive experimental data (such as orthogonal experiments), essentially describe the effect of each pigment on the final result. , , The contribution weight of the value.

[0101] S3: Establish a filler dosage correction model based on asphalt adsorption;

[0102] The filler dosage correction model takes into account the adsorption effect of filler on asphalt. The specific steps are as follows:

[0103] P1. Determine the relative bulk density ρ of the aggregate. sb :

[0104] ρ sb =1 / (P1 / ρ s1 +P2 / ρ s2 +...+P n / ρ sn );

[0105] Among them, P1, P2, ..., P n This represents the mass percentage of each aggregate grade; ρ s1 ρ s2 ...ρ sn The apparent density of each grade of aggregate;

[0106] P2, Calculate the basic filler usage P f0 :

[0107] P f0 =[(100-P b0 -ΣP pi )×ρ sb ×(VMA-V V )] / [ρ f [×(100-VMA)];

[0108] Among them, P b0 ΣP represents the initial asphalt content; pi ρ represents the total amount of pigment used. sb ρ is the bulk relative density of the aggregate. f VMA is the apparent relative density of the filler; VMA is the target void fraction of the aggregate determined according to specifications or actual site conditions; V V Determine the target porosity based on engineering requirements;

[0109] P3. Calculate the filler correction amount P based on asphalt adsorption. f :

[0110] P f =P f0 ×[1+(K f / SA agg )×(α f / α avg )];

[0111] Among them, P f0 K represents the basic amount of filler used. f / SA agg The ratio of the specific surface area of ​​the filler to that of the aggregate reflects the relative strength of the filler in adsorbing asphalt; α f To determine the packing correction factor α through adsorption tests; avg α is the average adsorption correction factor for all pigments. avg =Σ(α i ×P pi ) / ΣP pi .

[0112] S4: Construct a modified asphalt film thickness model that takes into account the effects of pigments and fillers;

[0113] The asphalt film thickness correction model considers the adsorption effect of pigments on asphalt, and the calculation method for corrected asphalt dosage is as follows:

[0114] P b =P b0 ×(1+Σ(α i ×P pi ×P f ));

[0115] Among them, P b To correct the amount of asphalt used; P b0 P represents the initial amount of asphalt used. pi α represents the percentage (%) of the i-th pigment in the total mass of the asphalt mixture. i P is the adsorption correction coefficient for the i-th pigment. It is calculated by measuring the changes in the three major properties of asphalt (penetration, ductility, and softening point) under different pigment dosages, and referring to the viscosity change rate. f The dosage of filler based on asphalt adsorption is adjusted.

[0116] S5: Calculate the amount of each component in the asphalt mixture using the mass formula.

[0117] S6: Determine the final ratio through target performance verification and color tolerance control;

[0118] Color tolerance ΔE control adopts a dynamic standard:

[0119] (1) General region: ΔE≤5.0;

[0120] (2) Key landscape areas: ΔE≤3.0;

[0121] (3) Special requirements area: ΔE≤2.0.

[0122] Example 1: Single pigment system (design of blue pedestrian walkway for urban slow-moving system).

[0123] (I) Project Background:

[0124] (1) Project: A slow walking trail in a waterfront park in a certain city (the trail is 3km long and 2.5m wide).

[0125] (2) Core requirement: The color is sky blue (target color parameter: =65.0、 =-2.0、 =-18.0), excellent wear resistance (Marshall stability ≥8.5kN), and strong color weather resistance (no obvious fading after long-term exposure to sunlight).

[0126] (II) Design and Material Parameters:

[0127] (1) Aggregate: granite (wear-resistant type), divided into 4 grades of aggregate (10-16mm, 5-10mm, 3-5mm, 0-3mm), ρ agg =2.78g / cm 3 The target gradation is AC-10 (the median of the gradation).

[0128] (2) Asphalt: SBS modified asphalt (enhanced wear resistance), Gb=1.030.

[0129] (3) Pigment: Phthalocyanine Blue (weather resistant), α i =0.05 (adsorption correction factor), α avg =0.05.

[0130] (4) Filler: Limestone powder, ρ f =2.71g / cm 3 K f =320m² / kg, α f =0.10.

[0131] (5) Volume parameter: V V =3.5% (reduced risk of water damage), VMA=14.0% (maximum required by regulations).

[0132] (III) Design Calculation Process:

[0133] (1) Gradation design: The mass percentage P of each aggregate grade is solved by linear programming. iSatisfying the AC-10 gradation median constraint, the calculated aggregate bulk relative density ρ is obtained. sb =2.72gcm 3 ;

[0134] (2) Specific surface area calculation: K of each set was measured by laser particle size analyzer. i Value, substitute into SA agg =Σ(P i ×K i ), get SA agg =7.8m 2 / kg (meets the AC-10 gradation reasonable range of 6.5-8.5m) 2 / kg);

[0135] (3) Initial asphalt content: according to formula P b0 =(SA agg ×FT×ρ agg ) / (1000×Gb)×100%, taking the target asphalt film thickness FT=8.5μm, calculate P b0 =5.72%;

[0136] (4) Color model establishment: A linear model of a single pigment was fitted through 5 sets of orthogonal experiments to obtain... =-1.2×P p -0.8 (R) 2 =0.995), =0.3×P p +63.5 (R) 2 =0.992). =-0.1×P p -1.9 (R) 2 =0.990);

[0137] (5) Calculation of pigment usage: Substitute into the target =-18.0, solving for P gives P p =(-18.0+0.8) / (-1.2)=14.33% (Verification) =0.3×14.33+63.5≈67.8, fine-tuned FT to 8.2μm, final Pp=13.8%. =65.2, =-2.1, which satisfies the objective);

[0138] (6) Correction for filler dosage: First calculate P f0 ≈4.2%, substitute into P f =P f0 ×[1+(K f / SA agg )×(α f / α avg)], thus obtaining P f ≈6.9%;

[0139] (7) Correction for asphalt dosage: according to P b =P b0 ×(1+Σ(α i ×P pi ×P f )), to get P b ≈5.77%.

[0140] (iv) Verification results:

[0141] (1) Performance indicators: Marshall stability 10.2kN, flow value 2.8mm, freeze-thaw splitting strength ratio (TSR) = 88%, all of which are better than the standard requirements;

[0142] (2) Color index: Actual measurement =64.8、 =-2.0、 =-17.7, ΔE=0.5<3.0 (standard for key landscape areas), good color uniformity;

[0143] (3) Design efficiency: The traditional method requires 12 sets of debugging experiments and takes 8 days; this method only requires 4 sets of verification experiments and takes 3 days, improving efficiency by 62.5%.

[0144] Example 2: Multi-pigment system (scenic area warm orange landscape road design).

[0145] (I) Project Background:

[0146] (1) Project: Main road of mountain scenic area (5km long, two lanes in both directions).

[0147] (2) Core requirement: The color is warm orange (target color parameters: =50.0、 =12.0、 =20.0), suitable for the natural landscape of the scenic area, the mixture has excellent anti-skid performance (bend value BPN≥50), and the color has no obvious color difference.

[0148] (II) Design and Material Parameters:

[0149] (1) Aggregate: Basalt (high anti-skid), divided into 5 grades of aggregate (16-20mm, 10-16mm, 5-10mm, 3-5mm, 0-3mm), ρ agg =2.92g / cm 3 The target gradation is AC-16 (gradation median).

[0150] (2) Asphalt: No. 70 road petroleum asphalt, Gb=1.028.

[0151] (3) Pigments: iron oxide red (α1=0.06), iron oxide yellow (α2=0.04), titanium dioxide (α3=0.03), with a total pigment content range of 1%-5%.

[0152] (4) Filler: Talc-modified mineral powder, ρ f =2.73g / cm 3 K f =380m 2 / kg, α f =0.11.

[0153] (5) Volume parameter: V V =4.0%, VMA=13.8%.

[0154] (III) Design Calculation Process:

[0155] (1) Gradation design: Solve P using linear programming method i By fitting the median of the AC-16 gradation, we obtain ρ sb =2.86g / cm 3 SA agg =6.9m 2 / kg (meets the AC-16 gradation reasonable range of 6-8m) 2 / kg);

[0156] (2) Initial asphalt content: FT = 8.0 μm, substituting into the formula, we get P b0 =4.98%;

[0157] (3) Establishment of a multi-pigment synergistic model: A Box-Behnken design (three factors, three levels) was adopted, and a multiple regression model was fitted through 27 sets of experiments:

[0158] =58.2-1.5P r -1.2P y -3.8P t (R) 2 =0.981);

[0159] =2.3+3.2P r +0.8P y -0.5P t (R) 2 =0.978);

[0160] =5.6+2.1P r +4.8P y -1.2P t (R) 2 =0.983);

[0161] (where P) r =Iron oxide red content, P y =Iron oxide yellow content, P t =Titanium dioxide content).

[0162] (4) Solution for pigment usage: P is obtained by using a sequential quadratic programming algorithm. r =2.1%, P y =3.3%, P t =0.7% (total pigment content 6.1%);

[0163] (5) Filler and asphalt correction: P is calculated f0 ≈5.1%, P f ≈7.3%; P b ≈5.05%.

[0164] (iv) Verification results:

[0165] (1) Performance indicators: pendulum value BPN=56, stability 9.5kN, flow value 3.0mm, meeting the anti-skid and load-bearing requirements of scenic roads;

[0166] (2) Color index: Actual measurement =49.7、 =11.8、 =19.6, ΔE=0.6<3.0, the color consistency of the whole line is good and the adaptability to the scenic landscape is high;

[0167] (3) Economic benefits: The waste rate of traditional multi-pigment adjustment materials is up to 25%, while the waste rate of this method is only 8%, and the material cost per kilometer is reduced by 32%.

[0168] Example 3: Special climate scenario (green antifreeze road design in high-altitude and cold regions).

[0169] (I) Project Background:

[0170] (1) Project: Rural roads in high-altitude and cold regions (8km in length, with the lowest winter temperature at -30℃).

[0171] (2) Core requirement: The color is dark green (target color parameter: =40.0、 =-5.0、 =10.0), excellent freeze-thaw resistance (freeze-thaw splitting strength ratio TSR≥80%), and color resistant to low temperatures without cracking.

[0172] (II) Design and Material Parameters:

[0173] (1) Aggregate: Diabase (frost-resistant type), divided into 4 grades of aggregate (10-16mm, 5-10mm, 3-5mm, 0-3mm), ρagg=2.89g / cm 3 The target gradation is AC-13 (gradation median).

[0174] (2) Asphalt: No. 90 low-temperature modified asphalt (enhanced freeze resistance), Gb=1.026.

[0175] (3) Pigment: Iron oxide green (low temperature resistant type), α i =0.08, α avg =0.08.

[0176] (4) Filler: frost-resistant limestone powder, ρ f =2.74g / cm 3 K f =360m 2 / kg, α f =0.13.

[0177] (5) Volume parameter: V V =3.8% (reducing freeze-thaw gaps), VMA=14.2% (increasing freeze-thaw resistance reserves)

[0178] (III) Design Calculation Process:

[0179] (1) Gradation design: Solving P using linear programming method i By fitting the median of the AC-13 gradation, we obtain ρ. sb =2.81g / cm 3 SA agg =7.5m 2 / kg;

[0180] (2) Initial asphalt content: FT=9.0μm (increasing the thickness of the asphalt film improves frost resistance), P is calculated. b0 =5.93%;

[0181] (3) Color model establishment: Fitting a single pigment nonlinear saturation model

[0182] =35.0+(45.0-35.0)×exp(-0.3×Pp) (R²=0.993);

[0183] =-2.0-(2.0-(-5.0))×exp(-0.25×Pp) (R²=0.991);

[0184] (4) Calculation of pigment usage: Substitute into the target =40.0, solving for P gives P p≈2.31%, verification =-4.8, =9.7, which meets the target;

[0185] (5) Filler and asphalt correction: P f0 ≈5.3%, P f =≈8.1%; P b ≈5.99%.

[0186] (iv) Verification results:

[0187] (1) Performance indicators: freeze-thaw splitting strength ratio TSR=85%, stability 9.1kN, low temperature ductility (-10℃)=28cm, excellent freeze-thaw resistance and crack resistance;

[0188] (2) Color index: Actual measurement =39.8、 =-5.1、 =9.8, ΔE=0.4<2.0 (standard for special requirements areas), no fading or cracking in color under low temperature conditions;

[0189] (3) Application effect: Traditional methods require separate adjustments for frost resistance and color, which takes 15 days; this method is an integrated design, which takes 4 days, and after 1 year of use in winter, there are no obvious diseases, and the color retention rate reaches 95%.

[0190] Based on the above embodiments, the core advantages of the present invention can be summarized as follows:

[0191] 1. Synergistic effect of all components to resolve the contradiction between "performance and color".

[0192] The patent breaks through the traditional segmented design mode of "performance first, color second". By establishing a multi-level mathematical model of aggregate gradation, asphalt, pigment, and filler, the pigment adsorption effect and filler influence are incorporated into the asphalt dosage correction system (such as in Example 3, by increasing the asphalt film thickness and adsorption correction, both frost resistance and color are guaranteed). This fundamentally solves the industry pain point of "color adjustment affecting performance and performance adjustment destroying color", and achieves integrated compliance of "structural performance + aesthetic effect".

[0193] 2. Quantitative modeling improves design accuracy and reproducibility.

[0194] The patent transforms subjective color requirements into objective ones. Parameters, through quantitative models for single pigments (linear / nonlinear) and multiple pigments (multivariate regression), achieve accurate calculation of pigment dosage (e.g., the prediction error of multi-pigment ratio in Example 2 is <1%), and all parameters (e.g., K) are used. i α i K fAll results are determined through standardized experiments, replacing traditional experience-based judgments. The design results are reproducible and traceable, with color prediction accuracy exceeding 95% and performance prediction accuracy exceeding 90%.

[0195] 3. Wide range of scenarios, adaptable to diverse engineering needs.

[0196] The patent is applicable to engineering needs with single / multiple pigment systems, different gradations (AC-10 / 13 / 16), different climate scenarios (normal temperature / high cold), and different functional requirements (wear resistance / slip resistance / freeze resistance): Example 1 is suitable for urban slow traffic systems, Example 2 is suitable for scenic roads, and Example 3 is suitable for highways in high cold regions, proving its universality in the field of road engineering and meeting the diverse design needs of municipal, scenic and rural roads.

[0197] 4. It optimizes both efficiency and cost, and has strong engineering applicability.

[0198] Through a closed-loop process of "theoretical calculation + a small number of verification experiments," the repeated trial mixing steps in traditional design are significantly reduced: Example 1 shows a 62.5% increase in efficiency, Example 2 shows a reduction in material waste rate from 25% to 8%, and Example 3 shows a reduction in the design cycle from 15 days to 4 days. Simultaneously, quality control is moved forward to the mix design stage, reducing construction rework rates (e.g., Example 2 shows a 60% reduction in rework rate), saving time and material costs for project construction, and demonstrating significant economic and social benefits.

[0199] The present invention has been described above by way of example with reference to the accompanying drawings. Obviously, the specific implementation of the present invention is not limited to the above-described manner. Any improvements made using the inventive concept and technical solution of the present invention, or direct application to other occasions without modification, are all within the protection scope of the present invention.

Claims

1. A method for the synergistic design of all components of colored asphalt mixtures, characterized in that, Includes the following steps: S1: Calculate the initial asphalt content based on aggregate gradation and packing theory; S2: Establish a quantitative relationship model between pigment dosage and color parameters; S3: Establish a filler dosage correction model based on asphalt adsorption; S4: Construct a modified asphalt film thickness model that takes into account the effects of pigments and fillers; S5: Calculate the dosage of each component in the asphalt mixture using the mass formula; S6: Determine the final ratio through target performance verification and color tolerance control.

2. The method for synergistic design of all components of colored asphalt mixture according to claim 1, characterized in that, In step S1, the initial asphalt dosage is calculated using a theoretical model based on specific surface area: P b0 =(IN agg ×FT×ρ agg ) / (1000×G b )×100%; Among them, P b0 This represents the initial amount of asphalt used; SA agg ρ represents the aggregate composite specific surface area; FT represents the target asphalt film thickness; agg G represents the apparent density of the aggregate. b This represents the relative density of asphalt.

3. The method for synergistic design of all components of colored asphalt mixture according to claim 2, characterized in that, Aggregate Synthetic Specific Surface Area SA agg The calculation formula is: SADDLE agg =Σ(P i ×K i ); Among them, P i K represents the mass percentage of the i-th aggregate; i is the specific surface area coefficient of the i-th aggregate, determined by a laser particle size analyzer.

4. The method for synergistic design of all components of colored asphalt mixture according to claim 3, characterized in that, The mass percentage of aggregate in grade i, P i The values ​​are constrained by the target gradation. Based on the measured sieve data of each aggregate grade, the mass percentage of each aggregate grade is obtained by linear programming. The specific calculation steps and formulas are as follows: (1) Establish the gradation equilibrium equation: If n grades of aggregate are used, then for each sieve opening j, the cumulative sieve residue C of the composite gradation is... j Satisfy T jmin ≤C j ≤T jmax T jmax T jmin These represent the upper and lower limits of the target gradation at sieve aperture j, respectively, and are fitted to the gradation median T. jmid C j The calculation method is as follows: C j =P1×S 1j +P2×S 2j +...+P n ×S nj ; Among them, C j P1, P2, ..., Pj are the cumulative sieve residues of the synthetic gradation at the j-th sieve aperture; n The mass percentage of each aggregate grade satisfies P1 + P2 + ... + P n =100%; S 1j S 2j ... S nj n represents the cumulative sieve residue rate of each aggregate grade at the j-th sieve opening, as measured experimentally; n is the total number of aggregate grades; and j is the sieve opening number. (2) Solve for the usage Pi of each grade using linear programming: With the objective function being "minimizing the sum of squared deviations between the synthesized gradation and the target gradation median", the following constraints are established: Objective function: minΣ(C j -T jmid )²; Constraint: 0 ≤ P i ≤100%, ΣP i =100%, T jmin ≤C j ≤T jmax ; Solve for the optimal P using linear programming tools. i ; (3) Verification in conjunction with specific surface area: The calculated usage P for each grade i Substitute SA agg =Σ(P i ×K i If the calculated SA agg If it exceeds a reasonable range, then fine-tune P. i Ensure SA agg Adapted to subsequent initial asphalt usage calculations.

5. The method for synergistic design of all components of colored asphalt mixture according to claim 1, characterized in that, In step S2, the color parameter C is the value measured by the colorimeter. , , Or, it can be the calculated chromaticity value; pigment dosage P p The percentage (%) of pigment in the total mass of asphalt mixture; the quantitative relationship model between pigment content and color parameters includes: (1) Linear model for a single pigment: C = k1 × P p +b; Where k1 is the color efficiency coefficient, representing the rate of change of color parameters for each additional unit of pigment dosage; b is the base color parameter, the color parameter value when the pigment dosage is 0, representing the base color of the mixture; (2) Nonlinear saturation model for a single pigment: C=C max -(C max -b)×exp(-k2×P p ); Among them, C max is the color saturation value; b is the basic color parameter; e is the natural constant; k2 is the coloring rate constant. The larger the k2 value, the less pigment is needed to achieve the saturated color, and the stronger the pigment's tinting power. (3) Multi-pigment synergistic model: =β0+Σ(β i ×P i ); =γ0+Σ(γ i ×P i ); =δ0+Σ(δ i ×P i ); in, , , β0, γ0, and δ0 represent the lightness, red-green value, and yellow-blue value of the mixture, respectively; β0, γ0, and δ0 represent the lightness, red-green value, and yellow-blue value parameters of pure aggregate + asphalt, respectively, representing the base color of the mixture; P i Different pigment dosages; β i γ i δ i is the regression coefficient.

6. The method for synergistic design of all components of colored asphalt mixture according to claim 1, characterized in that, In step S3, the filler dosage correction model considers the adsorption effect of the filler on asphalt. The specific steps are as follows: P1. Determine the relative bulk density ρ of the aggregate. sb : r sb =1 / (P1 / ρ s1 +P2 / p s2 +...+P n / r sn ); Among them, P1, P2, ..., P n This represents the mass percentage of each aggregate grade; ρ s1 ρ s2 ...ρ sn The apparent density of each grade of aggregate; P2, Calculate the basic filler usage P f0 : P f0 =[(100-P b0 -ΣP pi )×ρ sb ×(VMA-V V )] / [ρ f ×(100-VMA)]; Among them, P b0 ΣP represents the initial asphalt content; pi ρ represents the total amount of pigment used. sb ρ is the bulk relative density of the aggregate. f VMA is the apparent relative density of the filler; VMA is the target void fraction of the aggregate determined according to specifications or actual site conditions; V V Determine the target porosity based on engineering requirements; P3. Calculate the filler correction amount P based on asphalt adsorption. f : P f =P f0 ×[1+(K f / SA agg )×(a f / a avg )]; Among them, P f0 K represents the basic amount of filler used. f / SA agg α is the ratio of the specific surface area of ​​the filler to that of the aggregate. f To determine the packing correction factor α through adsorption tests; avg This represents the average adsorption correction factor for all pigments.

7. The method for synergistic design of all components of colored asphalt mixture according to claim 1, characterized in that, In step S4, the asphalt film thickness correction model considers the adsorption effect of pigments on asphalt, and the calculation method for the corrected asphalt dosage is as follows: P b =P b0 ×(1+Σ(a i ×P pi ×P f )); Among them, P b To correct the amount of asphalt used; P b0 P represents the initial amount of asphalt used. pi α represents the percentage (%) of the i-th pigment in the total mass of the asphalt mixture. i P is the adsorption correction coefficient for the i-th pigment. This coefficient is calculated by measuring the changes in the three major properties of asphalt under different pigment dosages and referring to the viscosity change rate. f The dosage of filler based on asphalt adsorption is adjusted.

8. The method for synergistic design of all components of colored asphalt mixture according to claim 1, characterized in that, In step S6, the color tolerance ΔE control adopts a dynamic standard: (1) General region: ΔE≤5.0; (2) Key landscape areas: ΔE≤3.0; (3) Special requirements area: ΔE≤2.0.

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