A method for predicting the optimum asphalt content in Marshall mix design

Abstract

The present invention relates to the technical field of road engineering, and particularly relates to a method for predicting the optimum asphalt content in Marshall mix design. According to the type of asphalt mixture, nominal maximum particle size and gradation, determine the design technical requirements of volume index values and calculate the basic parameters of the asphalt mixture, preliminarily determine the asphalt content range, group the asphalt content and void ratio within the range at certain intervals respectively, calculate the volume index values of different asphalt contents at different void ratios, determine the intersection of the asphalt content ranges that meet the design requirements for each volume index value under each void ratio condition according to the graphical method, then calculate the range of the optimum asphalt content according to the end values of the intersection, and then calculate the optimum asphalt content in combination with the key sieve hole and maximum particle size parameters. This method fills the blank of the existing specification that there is no method for predicting the optimum asphalt content in Marshall mix design, and solves the problem that the prediction is inaccurate due to only being able to estimate through engineering experience before the previous mix design.

Description

Technical Field

[0001] The present invention relates to the technical field of road engineering, and particularly relates to a method for predicting the optimum asphalt content in Marshall mix design. Background Art

[0002] The surface layer of highway pavement is mainly composed of asphalt mixture. The amount of asphalt in the asphalt mixture has a great influence on the pavement performance of the asphalt pavement. When the selected amount of asphalt is small, the thickness of the asphalt film on the aggregate surface is too thin, and the mixture lacks cohesion, resulting in poor durability of the mixture, easy occurrence of water damage, asphalt aging and other diseases. However, as the amount of asphalt increases, the cohesion of the mixture gradually increases, the thickness of the asphalt film on the aggregate surface thickens, and the free asphalt increases. When it reaches a certain level, the free asphalt is like a lubricant between the aggregates, causing the particles to slide and displace under the action of load, resulting in bleeding, rutting, etc. of the mixture, affecting driving safety. Therefore, an appropriate amount of asphalt is particularly important for the pavement performance of the asphalt pavement.

[0003] In China, the mix design of asphalt mixture mainly adopts the Marshall method. When determining the optimum asphalt content in the mix design, multiple groups of asphalt contents are used for Marshall tests, and the measured volume index values are analyzed and calculated to determine the optimum asphalt content. Usually, it takes 2 - 3 weeks to carry out the mix design, with a complex method and a long test cycle. At the same time, the selection of the initial asphalt content is estimated based on local practical experience, without relevant test and prediction methods. In the SHRP program in the United States, the prediction of the initial asphalt content in the superpave mix design method is only applicable to ordinary dense-graded asphalt mixtures, and the determined asphalt content often differs greatly from the target mix asphalt content, and is not applicable to the determination of the asphalt content in the Marshall mix design method. Therefore, it is particularly crucial to seek a reasonable method for predicting the optimum asphalt content in Marshall mix design. Summary of the Invention

[0004] The purpose of the present invention is to overcome the above-mentioned deficiencies of the prior art, and provide a method for predicting the optimum asphalt content in Marshall mix design, which provides asphalt content prediction for the Marshall mix design method of asphalt mixture, with an accurate prediction method and can effectively shorten the design cycle.

[0005] To achieve the above purpose, the present invention uses the following technical solutions:

[0006] A method for predicting the optimum asphalt content in the Marshall design method. According to the type of asphalt mixture, nominal maximum particle size and gradation, determine the design technical requirements for volume index values and calculate the basic parameters of the asphalt mixture, preliminarily determine the asphalt content range, group the asphalt content and void ratio within the range at certain intervals respectively, calculate the volume index values of different asphalt contents at different void ratios, determine the intersection of the asphalt content ranges that meet the design requirements for each volume index value under each void ratio condition according to the graphical method, then calculate the range of the optimum asphalt content according to the end values of the intersection, and then calculate the optimum asphalt content in combination with the key sieve hole and maximum particle size parameters.

[0007] The prediction method provided by the present invention does not require Marshall tests. By grouping the asphalt content and void ratio for volume index prediction and using the graphical method to determine the range of the optimum asphalt content, the optimum asphalt content can be calculated in combination with the key sieve hole parameters. This method fills the gap in the current specification that there is no method for predicting the optimum asphalt content in the Marshall mix design, and solves the problem of inaccurate prediction caused by only estimating through engineering experience before the previous mix design. At the same time, the optimum asphalt content predicted by this method omits the cumbersome process of determining the actual optimum asphalt content through at least 5 groups of Marshall tests in the past, greatly shortening the design time and improving the design efficiency. Compared with the asphalt content prediction method of the Superpave mix design, this method is predicted based on the idea of the Marshall mix design method, and the predicted asphalt content better meets the requirements of the Marshall mix design, is closer to the target mix, and ensures the accuracy of the design while improving the design efficiency.

[0008] The above prediction method includes the following steps:

[0009] S1. Determine the technical requirements and basic parameters of the Marshall mix design:

[0010] According to the type of asphalt mixture, nominal maximum particle size and gradation, determine the design technical requirements for volume index values and calculate the basic parameters of the asphalt mixture;

[0011] S2. Calculate and enumerate all volume index values according to the assumed asphalt content and void ratio values:

[0012] Preliminarily determine the asphalt content range according to engineering experience, and record the asphalt content within the range at certain intervals as P1, P2 ··· P n , according to the void ratio VV range determined in step S1, record the void ratio VV within the range at certain intervals as VV1, VV2 ··· VV m , according to the basic parameters determined in step S1, calculate the volume index values of different asphalt contents P n at different void ratios VV m , including: voids in mineral aggregate (VMA)m(n) , asphalt saturation VFA m(n) , filler-bitumen ratio FB m(n) and asphalt film thickness DA m(n) ; enumerate the asphalt content and the corresponding volume index values under each void ratio condition:

[0013] Volume index values under the void ratio VV1 condition:

[0014] Volume index values under the void ratio VV2 condition:

[0015] ……

[0016] Void ratio VV m condition volume index values:

[0017] S3. Determine the asphalt content range OAC where each volume index meets the design requirements of step S1 under each void ratio condition by graphical method min(m) ~OAC max(m) ;

[0018] S4. Determine the optimal asphalt content range:

[0019] According to the asphalt content range OAC min(m) ~OAC max(m) under each void ratio condition, calculate its union range OAC min ~OAC max ,

[0020] OAC min ~OAC max ={OAC min(1) ~OAC max(1)}∪{…}U{OAC min(m) ~OAC max(m)};

[0021] S5. Determine the optimal asphalt content:

[0022] Utilize the optimal asphalt content range OAC min ~OAC max , and combine with the relevant parameters of the key sieve holes and the maximum particle size to calculate the optimal asphalt content OAC. The formula is as follows:

[0023]

[0024] In the formula: P PCS is the passing percentage of the key sieve hole in the synthetic gradation, %; D pcsis the key sieve size in the synthetic gradation, mm; P NAS is the percentage of the maximum particle size passing rate in the synthetic gradation, which is 100%; D NAS is the maximum particle size in the synthetic gradation, mm. The voids in the asphalt mixture are mainly filled with fine aggregates. The content of fine aggregates is the main factor affecting the optimum asphalt content. The amount of fine aggregates is mainly controlled by the key sieve size. By establishing the degree of deviation of the key sieve size passing rate from the maximum density line, it can ensure that the error between the calculated optimum asphalt content and the asphalt content of the target mix design is small.

[0025] Preferably, in the step S1, the design technical requirements include: void ratio VV, voids in mineral aggregate VMA, asphalt saturation VFA, filler-bitumen ratio FB, asphalt film thickness DA; the basic parameters include: relative density of asphalt γ b , bulk relative density of synthetic mineral aggregate γ sb , effective relative density of synthetic mineral aggregate γ se , mass percentage of asphalt absorbed by mineral aggregate P ba , passing rate of 0.075mm P 0.075 , specific surface area of aggregate SA, maximum particle size D NSA , key sieve size D PCS , passing rate of key sieve size of synthetic gradation P PCS and percentage of maximum particle size passing in the synthetic gradation P NAS ; Further preferably, the basic parameters are calculated according to the "Technical Specifications for Construction of Highway Asphalt and Asphalt Mixtures" (JTG E20-2011).

[0026] Preferably, in the step S1, when the asphalt mixture type is dense-graded asphalt mixture, the design requirement range of void ratio VV is 3% - 6%; the design requirement of filler-bitumen ratio FB is 0.8 - 1.6; the design requirement of asphalt film thickness DA is not less than 6μm; the asphalt saturation VFA is selected according to the nominal maximum particle size: when D NMAS is 4.75mm, 9.5mm, VFA is 70% - 85%, when D NMAS is 13.2mm, 16mm, 19mm, VFA is 65% - 75%, when D NMAS is 26.5mm, 31.5mm, 37.5mm, VFA is 55% - 70%; the voids in mineral aggregate VMA are calculated according to the void ratio VV range by the following formula:

[0027] VMA = VV - 2.925ln(D NMAS ) + 17.531

[0028] In the formula, VMA is the voids in mineral aggregate, %, taking 1 decimal place; VV is the void ratio, %; D NMASis the nominal maximum aggregate size, in mm.

[0029] Specifically, in the step S1, when the asphalt mixture type is dense-graded asphalt mixture, the values of each volume index are as shown in the following table:

[0030] Table 1 Volume Index Values of Dense-Graded Asphalt Mixture

[0031]

[0032]

[0033] Preferably, in the step S1, when the asphalt mixture type is SMA asphalt mixture, the design requirement range of the void ratio VV is 3% - 4.5%, the design requirement range of the voids in mineral aggregate VMA is 17% - 18.5%, the design requirement range of the asphalt saturation VFA is 75% - 85%, and the powder-bitumen ratio FB and the asphalt film thickness DA do not have a set design requirement range.

[0034] Preferably, in the step S2, to ensure the accuracy of the asphalt dosage prediction, the interval of the asphalt dosage is 0.1%; the interval of the void ratio is 0.1% - 0.5%; further preferably, when the difference between the predicted asphalt dosage and the asphalt dosage of the target mix ratio is within the range of ±0.25% and can be accepted, the interval of the void ratio can be selected as 0.5% to reduce the overall calculation amount and further improve the prediction efficiency of the prediction method.

[0035] Preferably, in the step S2, under the conditions of the asphalt dosage P n and the void ratio VV m the calculation methods of each volume index are as follows:

[0036]

[0037]

[0038]

[0039]

[0040] In the above formulas, VMA m(n) , voids in mineral aggregate; γ n , theoretical maximum relative density, dimensionless; VV m , void ratio; γ sb , bulk relative density of the combined aggregates, dimensionless; P m , asphalt dosage; VFA m(n) , asphalt saturation; FB m(n) , powder-bitumen ratio; P 0.075 , passing rate of 0.075mm; Pba , the mass percentage of asphalt absorbed by the mineral aggregate; DA m(n) , the thickness of the asphalt film, μm; ρ b , the relative density of asphalt, dimensionless; SV, the specific surface area of the aggregate, m 2 / Kg.

[0041] Preferably, in the step S3, the specific steps are as follows:

[0042] a. First, calculate the asphalt dosage and the volume index range that meet the design technical requirements of step S1 under each void ratio condition:

[0043] The values of each volume index under the void ratio VV1 condition:

[0044] The values of each volume index under the void ratio VV2 condition:

[0045] ……

[0046] The void ratio VV m The values of each volume index under the condition:

[0047] b. Calculate the union range of the asphalt dosage under each void ratio condition. Under a certain void ratio condition, to meet the design index, the asphalt dosage must be within this range.

[0048] The intersection range of each asphalt dosage under the void ratio VV1 condition:

[0049] OAC min(1) ~OAC max(1) ={P 1a ~P 1b}}∩{P 1c ~P 1d}}∩{P 1e ~P 1f}}∩{P 1g ~P 1h}}

[0050] The intersection range of each asphalt dosage under the void ratio VV2 condition:

[0051] OAC min(2) ~OAC max(2) ={P 2a ~P 2b}}∩{P 2c ~P 2d}}∩{P 2e ~P 2f}}∩{P 2g ~P 2h}}

[0052] ……

[0053] Void ratio VV m Intersection range of asphalt dosages under various conditions:

[0054] OAC min(m) ~OAC max (m) = {P ma ~P mb} ∩ {P mc ~P md} ∩ {P me ~P mf} ∩ {P mg ~P mh}.

[0055] Preferably, in step S3, each value in OAC min(m) should be greater than the lower limit value P1 of the selected asphalt dosage, and each value in OAC max(m) should be less than the upper limit value P n of the selected asphalt dosage. Otherwise, the asphalt dosage range should be reselected and the calculation in step S2 should be redone until the requirements are met. Further preferably, when reselecting the asphalt dosage range, if there is a value in OAC min(m) equal to P1, the lower limit of the asphalt dosage range should be expanded according to the interval value in step S1. If there is a value in OAC max(m) equal to P n , the upper limit of the asphalt dosage range should be expanded according to the interval value in step S1 until all values in OAC min(m) are greater than the lower limit value P1 of the selected asphalt dosage and all values in OAC max(m) are less than the upper limit value P n .

[0056] Preferably, in step S5, the maximum particle size and key sieve holes corresponding to each nominal maximum particle size are selected according to the "Technical Specifications for Construction of Highway Asphalt Pavements" (JTG F40 - 2004). Specifically, the values are as shown in the following table:

[0057] Table 2 Maximum particle size and key sieve holes corresponding to each nominal maximum particle size

[0058]

[0059] The beneficial effects of the present invention are:

[0060] 1. The prediction method provided by the present invention does not require Marshall tests. By calculating the volume index values in multiple groups for asphalt content and air voids, and using the graphical method to determine the range of the optimal asphalt content, the predicted optimal asphalt content can be calculated in combination with the key sieve hole parameters. This method fills the gap in the current specification for the Marshall mix design without a prediction method for the optimal asphalt content, and solves the problem of inaccurate prediction caused by only estimating through engineering experience before the previous mix design. At the same time, the optimal asphalt content predicted by this method eliminates the cumbersome process of determining the actual optimal asphalt content through at least 5 groups of Marshall tests in the past, greatly shortening the design time and improving the design efficiency. Compared with the asphalt content prediction method of the Superpave mix design, this method is predicted based on the idea of the Marshall mix design method, and the predicted asphalt content better meets the requirements of the Marshall mix design, is closer to the target mix ratio, and ensures the accuracy of the design while improving the design efficiency.

[0061] 2. The present invention calculates and enumerates the asphalt content and the corresponding volume index values at each air void rate at a certain interval according to the asphalt content and the air void rate, and calculates the asphalt content range that meets the design requirements under each air void rate condition through the graphical method, and then calculates all asphalt content ranges. The optimal asphalt content must be within this range. When the asphalt content exceeds this range, it must not meet the design requirements, greatly shortening the selection range of the optimal asphalt content and improving the accuracy of the prediction.

[0062] 3. After determining the range of the optimal asphalt content, by establishing the degree of deviation of the passing rate of the key sieve holes from the maximum density line, the optimal asphalt content OAC can be calculated within the optimal asphalt content range OAC min ~OAC max , effectively improving the accuracy of predicting the optimal asphalt content. Description of the Drawings

[0063] Figure 1 is the enumeration result of each volume index value in Example 1;

[0064] Figure 2 is the analysis diagram of the asphalt content range at 3.5% air void rate in Example 1;

[0065] Figure 3 is the analysis diagram of the asphalt content range at 4.0% air void rate in Example 1;

[0066] Figure 4 is the analysis diagram of the asphalt content range at 4.5% air void rate in Example 1;

[0067] Figure 5 is the analysis diagram of the asphalt content range at 5.0% air void rate in Example 1;

[0068] Figure 6This is the flow chart of the steps of the present invention. Detailed implementation mode

[0069] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0070] Embodiment 1:

[0071] Estimate the optimal asphalt content value of AC-20 asphalt mixture. According to the type of asphalt mixture, nominal maximum particle size and gradation, determine the design technical requirements of volume index values and calculate the basic parameters of the asphalt mixture. Initially determine the asphalt content range. Group the asphalt content and void ratio within the range at certain intervals respectively. Calculate the volume index values of different asphalt contents at different void ratios. Determine the intersection of the asphalt content ranges that meet the design requirements for each volume index value under each void ratio condition according to the graphical method. Then calculate the range of the optimal asphalt content based on the end values of the intersection. Finally, calculate the optimal asphalt content in combination with the key sieve hole and maximum particle size parameters.

[0072] As Figure 6 shown, the specific estimation steps are as follows:

[0073] S1. Determine the Marshall mix design technical requirements and basic parameters of AC-20 asphalt mixture

[0074] In this embodiment, what needs to be calculated is the AC-20 asphalt mixture. The following are the basic parameters and design technical requirements:

[0075] Table 3 Design technical requirements of AC-20 asphalt mixture

[0076] VV(%) VMA(%) VFA(%) FB DA (μm) 3～6 12～15 65～75 0.8～1.6 ≥6

[0077] Relative density of asphalt γ b 、Bulk relative density of synthetic aggregate γ sb 、Effective relative density of synthetic aggregate γ se 、Percentage of asphalt mass absorbed by aggregate P ba 、Percentage passing of 0.075mm P 0.075 、Specific surface area of aggregate SA, maximum particle size D NSA 、Key sieve hole D PCS 、Percentage passing of key sieve hole of synthetic gradation P PCS ;

[0078] Table 4 Basic parameters of AC-20 asphalt mixture

[0079]

[0080] S2. According to the assumed asphalt content and void ratio values, calculate and enumerate all volume index values:

[0081] According to past engineering experience, the asphalt content range Pn In this preliminary selection, the asphalt content is 3.0% - 6.0%, and the asphalt content within the range is spaced at 0.1%, namely: 3.0%, 3.1%, 3.2%,... 6.0%; void ratio VV m According to the design requirements, the range is selected as 3.0% - 6.0%. The acceptable error range of the predicted results this time is ±0.25%. Therefore, in order to reduce the calculation amount, it is spaced at 0.5%, namely: 3.0%, 3.5%, 4.0%, 4.5%, 5.0%, 5.5%, 6.0%. Calculate and enumerate the volume index values corresponding to each asphalt content under each void ratio condition. The calculation formula is as follows:

[0082]

[0083]

[0084]

[0085]

[0086] In the above formula, VMA m(n) , mineral aggregate void ratio; theoretical maximum relative density γ n , dimensionless; VV m , void ratio; γ sb , bulk specific gravity of synthetic mineral aggregate, dimensionless; P m , asphalt content; VFA m(n) , asphalt saturation; FB m(n) , powder - bitumen ratio; P 0.075 , passing rate of 0.075mm; P ba , mass percentage of mineral aggregate absorbing asphalt; DA m(n) , asphalt film thickness, μm; ρ b , asphalt relative density, dimensionless; SA, specific surface area of aggregate, m 2 / Kg;

[0087] Enumerate the asphalt content and the corresponding volume index values under each void ratio condition, as Figure 1 shown:

[0088] Volume index values under the condition of void ratio 3.0%:

[0089] Volume index values under the condition of void ratio 3.5%:

[0090] ······

[0091] Volume index values under the condition of void ratio 6.0%:

[0092] S3. Determine the asphalt content range OAC where all volume indicators meet the design requirements of Step S1 by graphical method under each void ratio condition min(m) ~OAC max(m) ,

[0093] a. First, calculate the asphalt content and volume indicator intervals where the volume indicators meet the design technical requirements of Step S1 under each void ratio condition, such as Figure 1 the numerical values indicated by the shaded area shown:

[0094] Volume indicator values under the void ratio VV1 condition:

[0095] Volume indicator values under the void ratio VV2 condition:

[0096] ……

[0097] Volume indicator values under the void ratio VV m condition:

[0098] b Calculate the union range of asphalt content under each void ratio condition. Under a certain void ratio condition, to meet the design indicators, the asphalt content must be within this range. The graphical method is shown in Figures 2 to 5 . In each figure, the abscissa is the asphalt content (%), and the horizontal lines from top to bottom are VMA, DA, FB, and VFA in turn. Calculate the asphalt content range that meets the design requirements under each void ratio condition (that is, Figures 2 - 5 in, the overlapping part of the four horizontal lines parallel to the abscissa) as follows:

[0099] Table 5 Asphalt content range that meets the design requirements under each void ratio condition

[0100] <![CDATA[VV m (%)]]> <![CDATA[OAC min(m) (%)]]> <![CDATA[OAC max(m) (%)]]> 3.0 — — 3.5 4.1 4.9 4.0 3.9 5.1 4.5 4.1 4.9 5.0 4.5 4.7 5.5 — — 6.0 — — ;

[0101] S4. Determine the optimal asphalt content interval:

[0102] According to the asphalt content range OAC min(m) ~OAC max(m) under each void ratio condition, calculate its union range OAC min ~OAC max , that is, the optimal asphalt content interval. This interval range must be all asphalt content intervals that meet the design requirements:

[0103] OAC min ~OAC max={4.1 - 4.9} ∪ {3.9 - 5.1} ∪ {4.1 - 4.9} ∪ {4.5 - 4.7} = 3.9% - 5.1%;

[0104] S5. Determine the optimum asphalt content:

[0105] The voids in the asphalt mixture are mainly filled by fine aggregates. Generally, the amount of fine aggregates is the main factor affecting the optimum asphalt content. The amount of fine aggregates is mainly controlled by the key sieve holes. By establishing the degree of deviation of the passing rate of the key sieve holes from the maximum density line, the optimum asphalt content range OAC min ~OAC max The optimum asphalt content OAC is preferentially obtained. The formula is as follows:

[0106]

[0107]

[0108] In the formula: P PCS is the passing rate percentage of the key sieve hole in the synthetic gradation, %; D pcs is the key sieve hole in the synthetic gradation, mm; P NAS is the passing rate percentage of the maximum particle size in the synthetic gradation is 100%; D NAS is the maximum particle size in the synthetic gradation, mm.

[0109] Therefore, in this embodiment, the estimated optimum asphalt content of the AC-20 asphalt mixture is 4.4%, and the asphalt content of the target mix ratio is 4.4%. The estimated value is consistent with the asphalt content of the target mix ratio.

[0110] Verification Example 1:

[0111] To verify the accuracy of the method of the present invention in AC type dense-graded asphalt mixtures, the asphalt content estimation method is the same as in Example 1, and the superpave estimation method is carried out according to the method of Appendix X1 of AASHTO R35 in the American standard. The statistical results are as follows:

[0112]

[0113] By comparing with the asphalt content determined by the target mix ratio design, the asphalt content estimated by the method of the present invention is equivalent to the asphalt content determined by the target mix ratio. The maximum difference is only 0.12%, while the difference between the asphalt content estimated by superpave and the asphalt content determined by the target mix ratio is up to -0.58% at most, which is much larger than the difference of the estimated value of the present invention. It is proved that the present invention is accurate in estimation in AC type dense-graded asphalt mixtures compared with the existing superpave method.

[0114] Verification Example 2:

[0115] To verify the accuracy of the method of the present invention in ATB asphalt stabilized macadam, the asphalt dosage prediction method is the same as that in Example 1, and the superpave prediction method is carried out according to the method in Appendix X1 of AASHTO R35 in the American standard. The statistical results are as follows:

[0116]

[0117] By comparing with the asphalt dosage determined by the target mix design, the asphalt dosage predicted by the method of the present invention is equivalent to the asphalt dosage determined by the target mix design, and the maximum difference is only 0.08%. While the maximum difference between the asphalt dosage predicted by superpave and the asphalt dosage determined by the target mix design is 0.18%. The prediction of the present invention is accurate in dense-graded asphalt mixtures of the ATB type compared with the existing superpave method.

[0118] Verification Example 3:

[0119] To verify the accuracy of the method of the present invention in SMA asphalt mixture, the asphalt dosage prediction method is the same as that in Example 1, and the superpave prediction method is carried out according to the method in Appendix X1 of AASHTO R35 in the American standard. The statistical results are as follows:

[0120]

[0121] By comparing with the asphalt dosage determined by the target mix design, the asphalt dosage predicted by the method of the present invention is equivalent to the asphalt dosage determined by the target mix design, and the maximum difference is only 0.23%. While the maximum difference between the asphalt dosage predicted by superpave and the asphalt dosage determined by the target mix design is -1.34%, with a large deviation, which is not suitable for the prediction of the asphalt dosage of SMA asphalt mixture. The asphalt dosage prediction method of the present invention is accurate.

Claims

1. A method for predicting the optimum asphalt content in the Marshall design method, characterized in that, According to the type of asphalt mixture, nominal maximum particle size and gradation, determine the design technical requirements for volume index values, calculate the basic parameters of the asphalt mixture, preliminarily determine the asphalt content range, group the asphalt content and void ratio within the range at certain intervals respectively, calculate the volume index values at different asphalt contents under different void ratios, determine the intersection of the asphalt content ranges that meet the design requirements for each volume index value under each void ratio condition according to the graphical method, then calculate the best asphalt content range based on the end values of the intersection, and then calculate the best asphalt content in combination with the key sieve hole and maximum particle size parameters; Specifically, it includes the following steps: S1. Determine the Marshall mix design technical requirements and basic parameters: According to the asphalt mixture type, nominal maximum size D NMAS and gradation, determine the design technical requirements for the volume index value and calculate the basic parameters of the asphalt mixture; S2. Calculate and enumerate all volume index values according to the assumed asphalt content and void ratio values: Based on engineering experience, initially determine the asphalt dosage range, and record the asphalt dosages within the range at certain intervals, respectively, as , according to the air void ratio range determined in step S1, record the air void ratios within the range at certain intervals, respectively, as , according to the basic parameters determined in step S1, calculate the volume index values at different asphalt dosages under different air void ratios , including: voids in mineral aggregate , asphalt saturation , filler-bitumen ratio and asphalt film thickness ; enumerate the asphalt dosages and the corresponding volume index values under each air void ratio condition: Void fraction Volume index values under the following conditions: Void fraction Volume index values under the following conditions: …… Void fraction Volume index values under the following conditions: ; S3. Determine the asphalt content range that meets the design requirements of each volume index under each void ratio condition by graphical method ; S4. Determine the best asphalt content range: According to the asphalt content ranges under various void ratio conditions , calculate their union range , ； S5. Determine the best asphalt content: Using the optimal asphalt content range , and combining the relevant parameters of the key sieve holes and the maximum particle size, calculate the optimal asphalt content OAC, and the formula is as follows: Where: P PCS is the passing percentage of the key sieve opening in the synthetic gradation, %; D pcs is the key sieve opening in the synthetic gradation, mm; P NAS is the passing percentage of the maximum particle size in the synthetic gradation, which is 100%; D NAS is the maximum particle size in the synthetic gradation, mm.

2. The prediction method according to claim 1, characterized in that, In the step S1, the design technical requirements include: void ratio , void content in mineral aggregate , asphalt saturation , filler-bitumen ratio , asphalt film thickness ; the basic parameters include: relative density of asphalt , bulk relative density of synthetic mineral aggregate , effective relative density of synthetic mineral aggregate , mass percentage of asphalt absorbed by mineral aggregate , passing rate of 0.075mm , specific surface area of aggregate , maximum particle size D NSA , key sieve hole D PCS , passing rate P of key sieve hole in synthetic gradation PCS and passing percentage P of maximum particle size in synthetic gradation NAS ; the basic parameters are calculated according to the "Technical Specification for Construction of Highway Asphalt and Asphalt Mixtures" JTG E20 - 2011.

3. The prediction method according to claim 1, characterized in that, In the step S1, when the asphalt mixture type is a dense-graded asphalt mixture, the design requirement range of the void ratio is 3% - 6%; the design requirement of the powder-bitumen ratio FB is 0.8 - 1.6; the design requirement of the asphalt film thickness DA is not less than 6μm; the asphalt saturation VFA is selected according to the nominal maximum size: when D NMAS is 4.75mm or 9.5mm, VFA is 70% - 85%, when D NMAS is 13.2mm, 16mm or 19mm, VFA is 65% - 75%, when D NMAS is 26.5mm, 31.5mm or 37.5mm, VFA is 55% - 70%; the voids in mineral aggregate VMA is calculated according to the void ratio VV range by the following formula: where VMA is the voids in mineral aggregate, %, rounded to 1 decimal place; VV is the air voids, %; D NMAS is the nominal maximum size, mm.

4. The prediction method according to claim 1, characterized in that, In the step S1, when the asphalt mixture type is SMA asphalt mixture, the void ratio shall be within the designed requirement range of 3% - 4.5%, the voids in mineral aggregate shall be within the designed requirement range of 17% - 18.5%, the asphalt saturation shall be within the designed requirement range of 75% - 85%, and the filler-bitumen ratio and the asphalt film thickness shall not be set with a designed requirement range.

5. The prediction method according to claim 1, characterized in that, In step S2, to ensure the accuracy of asphalt content prediction, the interval of asphalt content is 0.1%; the interval of void ratio is 0.1% - 0.5%; when the difference between the predicted asphalt content and the asphalt content of the target mix is within the range of ±0.25% and can be accepted, the interval of void ratio is selected as 0.5%.

6. The prediction method according to claim 1, characterized in that, In the step S2, under the conditions of asphalt content and void ratio the calculation methods of each volume index value are as follows: In the above formula, , void ratio of aggregates; , theoretical maximum relative density, dimensionless; , porosity; , bulk relative density of synthetic aggregates, dimensionless; , asphalt content; , asphalt saturation; , filler-bitumen ratio; , passing rate of 0.075mm; , mass percentage of asphalt absorbed by aggregates; , asphalt film thickness, μm; , relative density of asphalt, dimensionless; , specific surface area of aggregates, m 2 / Kg.

7. The prediction method according to claim 1, characterized in that, In step S3, the specific steps are as follows: a. First, calculate the asphalt content and volume index ranges where the volume index meets the design technical requirements in step S1 under each void ratio condition: Void fraction Volume index values under the following conditions: Void fraction Volume index values under the following conditions: …… Void fraction Volume index values under the following conditions: ; b. Calculate the union range of asphalt content under each void ratio condition, Void ratio Intersection range of asphalt dosages under the condition: Void ratio Intersection range of asphalt dosages under the condition: …… Void ratio Intersection range of asphalt contents under the following conditions: 。 8. The prediction method according to claim 1, characterized in that, In the said step S3, each value therein should be greater than the lower limit value P1 of the selected asphalt dosage, and each value therein should be less than the upper limit value P n ; otherwise, the asphalt dosage range should be reselected and the calculation in step S2 should be carried out again until the requirements are met. When reselecting the asphalt dosage range, if there is a value equal to P1, the lower limit of the asphalt dosage range should be expanded according to the interval value in step S1. If there is a value equal to P n , the upper limit of the asphalt dosage range should be expanded according to the interval value in step S1 until all values in are greater than the lower limit value P1 of the selected asphalt dosage, and all values in are less than the upper limit value P n .

9. The prediction method according to claim 1, characterized in that, In step S5, the maximum particle size and key sieve holes corresponding to each nominal maximum particle size are selected according to the "Technical Specification for Construction of Highway Asphalt Pavements" JTG F40 - 2004.

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