A method for designing and selecting asphalt mixture gradation based on performance

Abstract

The application relates to a performance-based asphalt mixture gradation design and selection method and relates to the field of asphalt mixture gradation design. The application aims to solve the problems of excessive subjectivity and high requirements for test conditions of the existing asphalt mixture gradation design method. The application comprises the following steps: constructing a gradation curve library; obtaining a high-low temperature performance evaluation index CA ratio, a water stability performance evaluation index FA C , and a construction workability evaluation index EPSR of corresponding asphalt mixture based on gradation curve parameters f ; obtaining CA ratio score and weight, FA C and FA f average score, precipitation weight, freeze-thaw cycle index weight, and EPSR score and weight; normalizing the CA ratio weight, the precipitation weight, and the freeze-thaw cycle index weight; obtaining a total score S by using the normalized CA ratio weight, the precipitation weight, the freeze-thaw cycle index weight, the EPSR weight, and the CA ratio score, the FA C and the FA f average score, and the EPSR score; and obtaining a gradation with the maximum S in the gradation curve library. The application is used for obtaining an optimal gradation considering environmental parameters.

Description

Technical Field

[0001] This invention relates to the field of asphalt mixture gradation design, and in particular to a method for designing and selecting asphalt mixture gradation based on performance characteristics. Background Technology

[0002] Asphalt mixtures are composite materials widely used in road construction and maintenance, mainly composed of asphalt and aggregates. Aggregates typically account for over 95% of the mass of asphalt mixtures and play a crucial role in their overall performance, including road performance, workability, and other characteristics. Therefore, a reasonable aggregate gradation design is an important aspect of ensuring the performance of asphalt mixtures.

[0003] In the early 19th century, asphalt mixtures began to be used in engineering practice, but the initial aggregate gradation design methods relied mainly on engineers' experience, lacking a unified approach. With the increasing prevalence of motor vehicles, the demand for road construction continued to grow. Starting in the 1940s, American scholar Taylor proposed the famous Taylor gradation curve based on a power function model, initiating a systematic study of asphalt mixture gradation design methods. Subsequently, countries around the world developed a series of distinctive aggregate gradation design methods based on their actual asphalt pavement usage requirements, such as Germany's SMA gradation, the Soviet Union's K-method based on the maximum density curve, the United States' Bailey method and Superpave method, and China's SAC method and CAVF method, all making significant contributions to the development of asphalt mixture gradation design methods. However, these asphalt mixture gradation design methods still suffer from problems such as excessive subjectivity, poor matching with actual performance requirements, or high demands on experimental conditions. Summary of the Invention

[0004] The purpose of this invention is to address the problems of excessive subjectivity, poor matching with actual performance requirements, and high requirements for test conditions in existing asphalt mixture gradation design methods. This invention proposes a performance-based method for asphalt mixture gradation design and selection.

[0005] The specific process of a method for designing and selecting asphalt mixture gradation based on performance is as follows:

[0006] Step 1: Construct a gradation curve library;

[0007] The gradation curves are constructed based on the method for determining the gradation of mineral materials using a three-control-point hyperbola; all the gradation curves constitute a gradation curve library.

[0008] Among them, the discontinuity of the three control points is 0.22 times the nominal maximum particle size, and the discontinuity passing rate is the gradation range of the corresponding discontinuity sieve size in the "Technical Specification for Construction of Highway Asphalt Pavement".

[0009] Step 2: Obtain the high and low temperature performance evaluation index CA ratio and the water stability performance evaluation index FA of the corresponding asphalt mixture based on the gradation curve parameters. C FA f ;

[0010] The CA ratio, a high and low temperature performance evaluation index, is given by the following formula:

[0011]

[0012] Among them, P D / 2 P is the throughput when the particle size is 0.5 times the nominal maximum particle size. PCS It is the throughput of the first control sieve aperture;

[0013] The first control sieve aperture is 0.22 times the nominal maximum particle size;

[0014] The water stability performance evaluation index FA C FA f As shown in the following formula:

[0015]

[0016]

[0017] Among them, P SCS It is the throughput of the second control sieve aperture, P TCS It is the throughput of the third control sieve aperture;

[0018] The second control sieve aperture is 0.22 times that of the first control sieve aperture;

[0019] The third control sieve aperture is 0.22 times that of the second control sieve aperture;

[0020] Step 3: Obtain the workability evaluation index EPSR of the corresponding asphalt mixture based on the gradation curve parameters;

[0021] Step 4: Using the high and low temperature performance evaluation index CA ratio and the water stability evaluation index FA obtained in Steps 2 and 3. C FA f The workability evaluation index EPSR was used to obtain the CA ratio score and CA ratio weight, and FA. C with FA f The average score, precipitation weight, freeze-thaw cycle index weight, EPSR score and weight;

[0022] Step 5: Normalize the CA ratio weight, precipitation weight, and freeze-thaw cycle index weight respectively. Utilize the normalized CA ratio weight, normalized precipitation weight, normalized freeze-thaw cycle index weight, EPSR weight, and CA ratio score, FA... Cwith FA f The average score and EPSR score are used to obtain the total score S. The gradation with the largest S value in the gradation curve library is the optimal gradation.

[0023] Furthermore, the workability evaluation index (EPSR) of the asphalt mixture corresponding to the gradation curve parameters is obtained through the following formula:

[0024]

[0025]

[0026] Where D is the equivalent particle size of the mineral, D 粗 It is the equivalent particle size of coarse aggregate, D 细 It is the equivalent particle size of fine aggregate. This is the standard sieve aperture size for the k-th grade of ore. yes The standard screen aperture size for the next grade of ore is... c k yes The percentage of residue on the sieve is calculated based on the sieve aperture.

[0027] Furthermore, the CA ratio score is obtained using the following formula:

[0028]

[0029] Among them, CA min It is the minimum CA ratio among all gradations in the gradation curve library, CA max It is the maximum value among all gradation CA ratios in the gradation curve library.

[0030] Furthermore, the CA ratio weight is obtained using the following formula:

[0031]

[0032] Among them, ATE i It is the annual extreme temperature range of region i, ATE av It is the average annual extreme temperature difference for all regions in the country.

[0033] Furthermore, the FA C with FA f The average score is obtained using the following formula:

[0034]

[0035] Among them, FA av Is FA C and FA f Average value, FA avmin It is the FA of all gradations in the gradation curve library.C and FA f The minimum value among the averages, FA avmax It is the FA of all gradations in the gradation curve library. C and FA f The maximum value among the averages.

[0036] Furthermore, the precipitation weight is obtained using the following formula:

[0037]

[0038] Among them, AR i It is the annual precipitation of region i, AR av It is the average precipitation in all regions of the country.

[0039] Furthermore, the weight of the freeze-thaw cycle index is obtained through the following formula:

[0040]

[0041] Among them, FCI i It is the freeze-thaw cycle index (FCI) for region i. av It is the average value of the freeze-thaw cycle index for all regions in the country.

[0042] Furthermore, the EPSR score and weight are obtained using the following formula:

[0043]

[0044]

[0045] Where, ω EPSR It is the EPSR weight, EPSR max It is the maximum value of the equivalent particle size ratio (EPSR) for all gradations in the gradation curve library. av It is the average equivalent particle size ratio (EPSR) of all gradations in the gradation curve library. min It is the minimum equivalent particle size ratio (EPSR) of all gradations in the gradation curve library.

[0046] Furthermore, the normalized CA ratio weight, the normalized precipitation weight, and the normalized freeze-thaw cycle index weight are obtained through the following formulas:

[0047]

[0048] Where j = 1, 2, or 3, ω1 = ω CA , ω2=ω AR ,ω3=ω FCI ,ω' j These are the normalized weights.

[0049] Furthermore, the normalized CA ratio weight, normalized precipitation weight, normalized freeze-thaw cycle index weight, EPSR weight, and CA ratio score, FA are used. C with FA f The total score S is obtained by taking the average score and the EPSR score, and is calculated using the following formula:

[0050] S=ω1'U(CA)+(ω'2+ω'3)U(FA av )+ω EPSR U(EPSR)

[0051] Where ω1' is the normalized CA ratio weight, ω'2 is the normalized precipitation weight, and ω3' is the normalized freeze-thaw cycle index weight.

[0052] The beneficial effects of this invention are as follows:

[0053] This invention proposes the application of high and low temperature performance evaluation index (CA ratio) and water stability performance evaluation index (FA). C and FA f This invention uses the workability index (EPSR) and other parameters to comprehensively evaluate the performance of corresponding asphalt mixtures based on gradation. It calculates the score and weight of each indicator, multiplies the score of each indicator by its weight to obtain the total score, and the highest total score is the optimal gradation. This allows for obtaining the optimal gradation without testing. The optimal gradation obtained by this invention takes into account local environmental characteristics (temperature, precipitation, and freeze-thaw cycles), ensuring strong objectivity and improving its matching with actual usage needs, thus better meeting practical application requirements. Attached Figure Description

[0054] Figure 1 The CA ratio is the membership function.

[0055] Figure 2 The CA ratio is the weighted membership function;

[0056] Figure 3 For FA av Score membership function;

[0057] Figure 4 The membership function for annual precipitation;

[0058] Figure 5 The membership function of the freeze-thaw cycle index;

[0059] Figure 6 The membership function is the equivalent particle size ratio score.

[0060] Figure 7 This is the equivalent particle size ratio weighted membership function. Detailed Implementation

[0061] Specific Implementation Method 1: The specific process of this implementation method for designing and selecting asphalt mixture gradation based on performance is as follows:

[0062] Step 1: Construct a gradation curve library;

[0063] The gradation curves are constructed based on the method for determining the gradation of mineral materials using a three-control-point hyperbola; all the gradation curves constitute a gradation curve library.

[0064] First, set three control points and their corresponding sieve apertures for the material throughput:

[0065] Among them, the nominal maximum particle size and 0.075mm are two fixed control points. The gradation range of the sieve holes corresponding to these two control points is set according to the "Technical Specification for Construction of Highway Asphalt Pavement" (JTG F40-2004); the discontinuity of the third control point is 0.22 times the nominal maximum particle size; the passing rate of the discontinuity point is the gradation range of the corresponding sieve holes in the "Technical Specification for Construction of Highway Asphalt Pavement" (JTG F40-2004). Within this range, the passing rate of the three control points is dynamically adjusted in a minimum unit of 1%.

[0066] Then, the gradation curves of fine aggregates are uniformly constructed using power functions, while the gradation curves of coarse aggregates are constructed using exponential, power, and logarithmic functions respectively. All gradation curves constitute a gradation curve library.

[0067] Comparative analysis shows that the gradation constructed using this step basically conforms to the gradation characteristics of AC type continuous dense gradation in the "Technical Specification for Construction of Highway Asphalt Pavement" (JTGF40-2004) (hereinafter referred to as the "Specification"). To construct a gradation curve library covering the entire range of AC type gradations in the Specification, this invention improves the method for determining the discontinuity point (fixed at 4.75mm) and its pass rate requirement (fixed at 28%–40%). Because the role of 4.75mm aggregate is significantly inconsistent in asphalt mixtures with different nominal maximum particle sizes, this invention uses a dynamic adjustment method to determine the discontinuity point between coarse and fine aggregates. The discontinuity point is changed from the original fixed 4.75mm to 0.22 times the nominal maximum particle size. This is based on the fact that when all aggregate particles are round, the ratio of the first control sieve aperture size to the nominal maximum particle size to achieve the interlocking state is 0.155; when all aggregate particles are square, this ratio is 0.289. Since aggregate particles are not all round or square, both are used. The mean value of 0.22 is used as a scaling factor. The passing rate at the discontinuity is adjusted to the gradation range corresponding to the sieve size of the intermediate discontinuity in the standard. Thus, the aggregate passing rates at the three control points are all within the gradation range of AC type gradation in the standard. Within this range, the passing rates of the three control points are dynamically adjusted in 1% increments. Taking AC-13 type asphalt concrete as an example, in the gradation curve library constructed in this invention, the passing rates of 0.075mm are 4%, 5%, 6%, 7%, and 8%, respectively, and the passing rate at the discontinuity of 2.36mm is... The passing rates were 24%, 25%, 26%, ..., 48%, 49%, and 50%, respectively, and the passing rates for the nominal maximum particle size of 13.2 mm were 90%, 91%, 92%, ..., 98%, 99%, and 100%, respectively. Then, the gradation curves for fine aggregates were uniformly constructed using power functions, while the gradation curves for coarse aggregates were constructed using exponential, power, and logarithmic functions, respectively. Thus, the gradation curve library for the nominal maximum particle size of 13.2 mm contains 5 × 27 × 11 × 3 = 4455 gradations.

[0068] Step 2: Obtain the high and low temperature performance evaluation index CA ratio and the water stability performance evaluation index FA of the corresponding asphalt mixture based on the gradation curve parameters. C FA f This includes the following steps:

[0069] Step 2.1. Obtain the CA ratio (high and low temperature performance evaluation index) of the corresponding asphalt mixture based on the gradation curve parameters:

[0070] The CA ratio reflects the composition of coarse aggregates by different particle sizes. It is mainly used to characterize the coarse aggregate content in mineral materials and to analyze their porosity characteristics. The calculation formula is as follows:

[0071]

[0072] In the formula: P D / 2—Passing rate (%) for particles with a diameter of 0.5 times the nominal maximum particle size;

[0073] P PCS —Passing rate (%) of the first control sieve aperture (0.22 times the nominal maximum particle size).

[0074] This invention uses this parameter to characterize the high and low temperature performance of gradation-matched asphalt mixtures. When the CA ratio is 0.4 to 0.8, as the CA ratio increases, the high and low temperature performance of the mixture deteriorates, and the porosity and aggregate void ratio also show a significant increasing trend. Therefore, for mixtures of the same gradation type, it can be considered that when CA approaches 0.4 from the right, the high and low temperature performance of the mixture is optimal at the same time, and the mixture is also the densest at this time.

[0075] Step 22: Obtain the water stability performance evaluation index FA of the corresponding asphalt mixture based on the gradation curve parameters. C :

[0076] First, based on the discontinuity determination method in step one, 0.22 times the discontinuity of coarse and fine aggregates (i.e., the first control sieve hole) is used as the second discontinuity (i.e., the second control sieve hole) to divide the fine aggregates. The fine aggregates are divided into a coarser part and a finer part, which are called the first fine aggregate and the second fine aggregate.

[0077] Then, the water stability performance evaluation index FA is calculated. C FA C This is an indicator used to reflect the filling and interlocking situation between the two, and the formula is as follows:

[0078]

[0079] In the formula: P SCS —Pass rate (%) of the second control sieve aperture (0.22 times that of the first control sieve aperture).

[0080] Steps 2 and 3: Obtain the water stability performance index FA of the corresponding asphalt mixture based on the gradation curve parameters. f :

[0081] First, 0.22 times the second discontinuity is taken as the third discontinuity (i.e. the third control screen hole), and the second fine aggregate is divided into a coarser part and a finer part. The finer part of the second fine aggregate is the fine sand part.

[0082] Then, using FA f The formula for calculating the proportion of fine sand in the second fine aggregate, which reflects the interlocking of the finest grade, is as follows:

[0083]

[0084] In the formula: P TCS—Pass rate (%) of the third control sieve aperture (0.22 times that of the second control sieve aperture).

[0085] In this step, FA f with FA C Similarly, this invention uses this parameter to characterize the water stability of graded asphalt mixtures. FA C Within the range of 0.35 to 0.5, the higher the value, the lower the porosity and aggregate interstitial ratio of the mixture, the greater the Marshall stability, and the continuously improved water stability. FA f Within the range of 0.35 to 0.5, both water stability and Marshall stability exhibit maximum values. Therefore, FA can be considered... f with FA C The water stability, strength and density are best in the range of 0.35 to 0.5, and the closer to 0.5, the better the overall performance.

[0086] Step 3: Obtain the workability evaluation index (Equivalent Coarse-Fine Aggregate Ratio, EPSR) of the corresponding asphalt mixture based on the gradation curve parameters:

[0087] The Equivalent Particle Size Ratio (EPSR) uses the first control sieve aperture size (0.22 times the nominal maximum particle size) as the dividing point between coarse and fine aggregates. The equivalent particle sizes of the coarse and fine aggregates are calculated separately, and their ratio is used as an indicator to evaluate the discontinuity of the gradation, indirectly assessing the workability of the gradation. The calculation formula is shown below:

[0088]

[0089]

[0090] Where: EPSR—equivalent particle size ratio of coarse and fine aggregates;

[0091] D—Equivalent particle size of the mineral, D 粗 It is the equivalent particle size of coarse aggregate, D 细 It is the equivalent particle size of the fine aggregate, in mm;

[0092] —Standard sieve aperture size for a certain grade of ore, in mm;

[0093] —— The standard sieve aperture size for the next grade of ore, in mm;

[0094] c k —— The percentage of residue on the sieve is calculated based on the sieve aperture.

[0095] For continuous dense-gradation AC type asphalt concrete, the standard sieve size ranges of the aggregate include: 31.5mm, 26.5mm, 19mm, 16mm, 13.2mm, 9.5mm, 4.75mm, 2.36mm, 1.18mm, 0.6mm, 0.3mm, 0.15mm, and 0.075mm; if but

[0096] Step 4: Obtain CA ratio and FA C FA f The EPSR score and weighting include the following steps:

[0097] Step 41: Obtain the score and weight of the CA ratio, specifically as follows:

[0098] First, obtain the CA ratio score:

[0099] Step two mentions that the CA ratio is mainly used to evaluate the high and low temperature performance of asphalt mixtures with different gradations, but the value range of the CA ratio is different from that of the FA ratio. C and FA f The value range of CA ratios is not uniform, making comparison and calculation inconvenient. Therefore, this invention utilizes the membership function in fuzzy mathematics to construct a functional relationship between CA ratios and their evaluation scores. The membership function determined by this invention is as follows: Figure 1 As shown. When the CA ratio is equal to 0.4, the high and low temperature comprehensive performance of the mixture is considered optimal, and the membership function takes the maximum value of 1. When the CA ratio is equal to the minimum CA ratio obtained by using the above 4455 gradations (taking AC-13 as an example, the same below) (denoted as CA), the performance is considered optimal. min When the CA ratio is equal to 0.8, the membership function takes the minimum value of 0. When the CA ratio is equal to 0.8, the membership function takes the value of 0.5. When the CA ratio is equal to the maximum value of the CA ratio obtained by solving the above 4455 gradations (denoted as CA), the membership function takes the minimum value of 0. max When the CA ratio is zero, the membership function value is 0. For the other CA ratios, the membership function values ​​are linearly interpolated between the known points using the CA ratio as the independent variable. The calculation formula is shown below:

[0100]

[0101] Among them, CA min It is the minimum CA ratio among all gradations in the gradation curve library, CA max It is the maximum value among all gradation CA ratios in the gradation curve library.

[0102] Then, obtain the weights of the CA ratio:

[0103] Because the high and low temperature performance of asphalt mixtures exhibits a high degree of consistency with the CA ratio when evaluating the road performance of gradation, meaning that the high and low temperature performance parameters of the mixture change in a consistent manner with the CA ratio, this invention proposes using the annual extreme temperature difference of a region (the highest temperature of the year minus the lowest temperature, calculated using the average of historical climate data from the three years preceding the year in which the gradation design is performed) to simultaneously characterize the high and low temperature characteristics of a given area. This reflects the region's demand for the high and low temperature performance of asphalt mixtures, further determining the weight of the CA ratio in evaluating the road performance of asphalt mixtures using gradation parameters. The mathematical method employed still references membership functions in fuzzy mathematics (such as...). Figure 2 ).

[0104] First, the database of annual extreme temperature ranges is defined, including the total sample of annual extreme temperature ranges nationwide. The weight of the CA ratio (denoted as ω) is determined when the annual extreme temperature range (ATE) is 0. CA The value is 0, meaning the temperature is constant under these conditions. There's no need to consider high or low temperature performance; only other indicators are needed: stability and volumetric properties at the optimal oil-stone ratio, and FA. C and FA f The water stability performance and other characteristics must meet the requirements. The annual extreme temperature difference is defined as the national average (ATE). av When the CA ratio is set to 0.5, it indicates that the temperature variation in this area is moderate, and then the annual extreme temperature range is the largest (ATE). max The calculation of the CA ratio weight for the region is based on the annual extreme temperature difference as the independent variable, and linear interpolation using the membership function values ​​at points 0 and 0.5 and their independent variables as reference points. The calculation formula is as follows:

[0105]

[0106] In the formula: ω CA —The weighting of the CA ratio;

[0107] ATE i —Annual extreme temperature range (°C) in a certain region;

[0108] ATE av —The average annual extreme temperature difference (°C) for all regions across the country.

[0109] Step 42: Obtain FA C and FA f Score and weighting:

[0110] FA C The proportion of the finer aggregate (the second fine aggregate, which can pass through a 2.36mm sieve in AC-13) within the fine aggregate (the aggregate that can pass through a 0.6mm sieve in AC-13) is represented by FA. fThe ratio of fine sand (aggregate that can pass through a 0.15mm sieve in AC-13) to the finer aggregate in the fine aggregate is a characteristic that reflects the ability of fine aggregate to fill voids in the gradation. According to experimental data, both are consistent in reflecting the water stability and volumetric properties of asphalt mixtures, i.e., FA. C and FA f Within the range of 0.35 to 0.5, the water stability and compaction properties are the best, and the closer to 0.5, the better the overall performance. Therefore, this invention uses the average of the two as an indicator to evaluate the water stability performance of the mixture. Furthermore, since the test indicators for water stability performance in the specifications include the residual stability obtained from the immersion Marshall test and the residual strength ratio obtained from the freeze-thaw splitting test, considering that the indicators with the greatest correlation between regional environmental factors and the above two test indicators include precipitation and the number of freeze-thaw cycles, this invention uses "regional annual precipitation (mm)" to characterize the precipitation factor, and the average historical precipitation of the three years prior to the year in which the gradation design of the region is taken during the calculation; for the number of freeze-thaw cycles factor, the "freeze-thaw cycle index (days)" of asphalt mixture is proposed. This index is defined as the number of days in a year in a certain region where the daily temperature simultaneously exists above zero and below zero, and the average historical climate data of the three years prior to the year in which the gradation design of the region is taken during the calculation.

[0111] First, obtain FA C and FA f Average score:

[0112] Construct membership functions, such as Figure 3 As shown, when FA C and FA f Average (denoted as FA) av When FA is 0.5, the membership function takes its maximum value of 1; when the average of the two is 0.35, the membership function takes its median value of 0.5; when FA... C and FA f The average values ​​are the minimum values ​​among the 4455 gradations (denoted as FA). avmin ) and maximum value (denoted as FA) avmax When ), the membership function takes the minimum value of 0, and the rest are FA. av The corresponding membership function values ​​between the above known points are defined by FA. av For linear interpolation of the independent variable, the calculation formula is as follows:

[0113]

[0114] Among them, FA av Is FA C and FA f Average value, FA avmin It is the FA of all gradations in the gradation curve library. C and FA fThe minimum value among the averages, FA avmax It is the FA of all gradations in the gradation curve library. C and FA f The maximum value among the averages;

[0115] Then, obtain FA. C and FA f Weights:

[0116] The weights are divided into two parts: the scores of the region’s annual precipitation and the number of freeze-thaw cycles of asphalt mixtures, and then a new membership function is proposed to assign weights to the two.

[0117] First, the membership function calibration value is determined by referring to the CA ratio method. As mentioned above, when the annual extreme temperature difference is defined as the national average, the CA ratio weight is taken as 0.5. Similarly, when the regional annual rainfall and asphalt mixture freeze-thaw cycle index are defined as the national average, the FA... C and FA f When evaluating road performance, an additional weight of 0.5 is applied, meaning that on average, the sum of the two weights is 1. In this case, FA... C and FA f Internal precipitation and asphalt mixture freeze-thaw cycle index are each assigned a weight of 0.25, and these are then used as a calibration to determine how to allocate these two weights under other conditions.

[0118] For precipitation weight (denoted as ω) AR Construct membership functions, such as Figure 4 As shown, the annual rainfall (AR) of the specified region is the national average (AR). av When the annual precipitation is zero, the membership function value is 0.25; when the annual precipitation is zero, the membership function value is 0. This is the extreme case. If a place experiences no rainfall throughout the year, then water damage caused by precipitation does not need to be considered. The annual precipitation is at its maximum (AR). max The calculation of the weights corresponding to precipitation in the region is performed with precipitation as the independent variable, and linear interpolation is performed using the membership function values ​​at points 0 and 0.25 and their independent variables as reference points. The calculation formula is as follows:

[0119]

[0120] In the formula: ω AR —Weight of precipitation;

[0121] AR i —Annual precipitation (mm) in a certain region;

[0122] AR av —National average precipitation (mm).

[0123] Construct a membership function for the freeze-thaw cycle index of asphalt mixtures. Figure 5 When the freeze-thaw cycle index (FCI) of asphalt mixture is equal to the national average (FCI... av When the freeze-thaw cycle index (FCI) of the asphalt mixture is 0, the membership function value is 0.25. When the FCI of the asphalt mixture is 0, the function value is 0, which is the extreme case. Assuming that a region does not have sub-zero temperatures throughout the year, water damage caused by freeze-thaw cycles does not need to be considered. The FCI of the asphalt mixture is at its maximum. max The calculation of the weights corresponding to the freeze-thaw cycle index for a given region uses the freeze-thaw cycle index as the independent variable and linear interpolation with the membership function values ​​at points 0 and 0.25 and their independent variables as reference points. The calculation formula is as follows:

[0124]

[0125] In the formula: ω FCI —Weight of the freeze-thaw cycle index;

[0126] FCI i —Freeze-thaw cycle index of a certain region;

[0127] FCI av —Average freeze-thaw cycle index for all regions of China.

[0128] Step 43: Weight the CA ratio and FA. C and FA f The weights of precipitation and freeze-thaw cycle index are normalized to obtain the normalized weights of the evaluation indicators:

[0129]

[0130] In the formula: ω j These are the original weights of the evaluation indicators; including annual extreme temperature difference indicators for high and low temperature performance, precipitation indicators for water stability performance, and freeze-thaw cycle index, ω' j These are the normalized weights of the evaluation indicators, j = 1, 2, or 3 are the indicator labels, and ω1 = ω CA , ω2=ω AR ,ω3=ω FCI ;

[0131] Step 44: Obtain the EPSR score and weight, specifically as follows:

[0132] First, obtain the EPSR score:

[0133] Using EPSR as an indicator to evaluate the degree of discontinuity in gradation and indirectly assess the workability of asphalt mixtures, this invention proposes that the equivalent particle size ratio score should be dynamically adjusted based on the nominal maximum particle size of the gradation, taking the minimum equivalent particle size ratio (EPSR) among 4455 gradations. min ) to average (EPSR) av The membership function value is 1, and the maximum equivalent particle size ratio (EPSR) is... max The membership function value of ) is 0, and the scores of other equivalent particle size ratios are linearly interpolated within this interval, such as Figure 6 The calculation method is as follows:

[0134]

[0135] Among them, EPSR min It is the minimum equivalent particle size ratio (EPSR) of all gradations in the gradation curve library. av It is the average equivalent particle size ratio (EPSR) of all gradations in the gradation curve library. max It is the maximum value of the equivalent particle size ratio (EPSR) for all gradations in the gradation curve library;

[0136] Then, obtain the weight of EPSR:

[0137] When the equivalent particle size ratio is the maximum value among the 4455 gradations, workability is considered the most important factor to consider, and the workability evaluation index is assigned a weight of 1. When the equivalent particle size ratio is the minimum value among the 4455 gradations, the weight is 0. For the other gradations, the weight allocation of the equivalent particle size ratio uses the equivalent particle size ratio as the independent variable and linear interpolation is performed using the membership function values ​​at points 0 and 1 and their independent variables as reference points. Figure 7 As shown, the calculation formula is as follows:

[0138]

[0139] Where, ω EPSR The equivalent particle size ratio is the weight.

[0140] Step 5: Utilize CA ratio and FA C FA f The total score S for each gradation is obtained by combining the EPSR score and weights. The gradation with the largest S value is the optimal gradation. S is calculated as follows:

[0141] S=ω'1U(CA)+(ω'2+ω'3)U(FA av )+ω EPSR U(EPSR)

[0142] Example: To verify the beneficial effects of the present invention, the following examples were calculated:

[0143] Example 1:

[0144] Given that the annual extreme temperature difference in Changchun City is 60℃, the annual precipitation is 210mm, and the freeze-thaw cycle index is 69 days, the optimal gradation of AC type asphalt concrete with a nominal maximum particle size of 13.2mm in this region is obtained using the method proposed in this invention.

[0145] Based on the known conditions, the optimal gradation for this region can be calculated as shown in the table below:

[0146] Table 1

[0147]

[0148] The CA ratio of this gradation is 0.38, the CA ratio score is U(CA) = 0.82, and the weight is ω'1 = 0.58; FA av It is 0.49, FA av The score is U(FA) av )=0.98, ω FAav =ω'2+ω'3=0.42; the equivalent particle size ratio (ESPR) of coarse and fine aggregates is 18.7, which is less than the average of 18.8, U(ESPR)=1.00, and the weight is ω ESPR =0.35, with a total score of 1.23.

[0149] Example 2:

[0150] Given that Zhengzhou has an annual extreme temperature range of 49℃, an annual precipitation of 354.4mm, and a freeze-thaw cycle index of 76 days, the optimal gradation of AC type asphalt concrete with a nominal maximum particle size of 13.2mm is obtained using the method proposed in this invention.

[0151] Based on the known conditions, the optimal gradation for this region can be calculated as shown in the table below:

[0152] Table 2

[0153]

[0154] The CA ratio of this gradation is 0.37, the CA ratio score is U(CA) = 0.77, the weight is ω'1 = 0.49, and the FA... av FA is 0.50. av The score is U(FA) av ) = 1.00, weight is ω(FA) av )=ω'2+ω'3=0.51; the equivalent particle size ratio (ESPR) of coarse and fine aggregates is 19.1, U(ESPR)=0.97, ω EPSR =0.37, with a total score of 1.25.

Claims

1. A method for designing and selecting asphalt mixture gradation based on performance characteristics, characterized in that... The method includes the following steps: Step 1: Construct a gradation curve library; The gradation curves are constructed based on the mineral gradation determination method using a three-control-point hyperbola; all gradation curves constitute a gradation curve library. Among them, the discontinuity of the three control points is 0.22 times the nominal maximum particle size, and the discontinuity passing rate is the gradation range of the corresponding discontinuity sieve size in the "Technical Specification for Construction of Highway Asphalt Pavement". Step 2: Obtain the high and low temperature performance evaluation index CA ratio and the water stability performance evaluation index FA of the corresponding asphalt mixture based on the gradation curve parameters. C FA f ; The CA ratio, a high and low temperature performance evaluation index, is given by the following formula: in, This is the throughput for particles with a diameter of 0.5 times the nominal maximum particle size. It is the throughput of the first control sieve aperture; The first control sieve aperture is 0.22 times the nominal maximum particle size; The water stability performance evaluation index FA C FA f As shown in the following formula: in, It is the throughput of the second control sieve aperture. It is the throughput of the third control sieve aperture; The second control sieve aperture is 0.22 times that of the first control sieve aperture; The third control sieve aperture is 0.22 times that of the second control sieve aperture; Step 3: Obtain the corresponding workability evaluation index of asphalt mixture based on the gradation curve parameters. ; Step 4: Using the high and low temperature performance evaluation index CA ratio and the water stability performance evaluation index FA obtained in Steps 2 and 3. C FA f The workability evaluation index EPSR is used to obtain the CA ratio score and CA ratio weight, FA C with FA f The average score, precipitation weight, freeze-thaw cycle index weight, Scoring and weighting; Step 5: Normalize the CA ratio weight, precipitation weight, and freeze-thaw cycle index weight respectively. Use the normalized CA ratio weight, normalized precipitation weight, and normalized freeze-thaw cycle index weight... Weights and CA ratio scores, FA C with FA f average score The total score S is obtained by scoring, and the gradation with the largest S value in the gradation curve library is the optimal gradation. The CA ratio score is obtained using the following formula: Among them, CA min It is the minimum CA ratio among all gradations in the gradation curve library, CA max It is the maximum CA ratio among all gradations in the gradation curve library; The FA C with FA f The average score is obtained using the following formula: Among them, FA av Is FA C and FA f Average value, FA avmin It is the FA of all gradations in the gradation curve library. C and FA f The minimum value among the averages, FA avmax It is the FA of all gradations in the gradation curve library. C and FA f The maximum value among the averages.

2. The method for designing and selecting asphalt mixture gradation based on performance, as described in claim 1, is characterized in that: The workability evaluation index of the corresponding asphalt mixture is obtained based on the gradation curve parameters. It can be obtained through the following formula: Where D is the equivalent particle size of the mineral. It is the equivalent particle size of coarse aggregate. It is the equivalent particle size of fine aggregate. This is the standard sieve aperture size for the k-th grade of ore. yes The standard screen aperture size for the next grade of ore is... > , yes The percentage of residue on the sieve is calculated based on the sieve aperture.

3. The method for designing and selecting asphalt mixture gradation based on performance, as described in claim 2, is characterized in that: The CA ratio weight is obtained using the following formula: in, It is the annual extreme temperature range of region i. It is the average annual extreme temperature difference for all regions in the country.

4. The method for designing and selecting asphalt mixture gradation based on performance, as described in claim 3, is characterized in that: The precipitation weight is obtained using the following formula: in, This is the annual precipitation in region i. It is the average precipitation in all regions of the country.

5. The method for designing and selecting asphalt mixture gradation based on performance, as described in claim 4, is characterized in that: The weight of the freeze-thaw cycle index is obtained using the following formula: in, It is the freeze-thaw cycle index of region i. It is the average value of the freeze-thaw cycle index for all regions in the country.

6. The method for designing and selecting asphalt mixture gradation based on performance, as described in claim 5, is characterized in that: The The score and weight are obtained using the following formula: in, yes Weight, It is the equivalent particle size ratio of all gradations in the gradation curve library. The maximum value, It is the equivalent particle size ratio of all gradations in the gradation curve library. The average value, It is the equivalent particle size ratio of all gradations in the gradation curve library. The minimum value.

7. The method for designing and selecting asphalt mixture gradation based on performance, as described in claim 6, is characterized in that: The normalized CA ratio weight, normalized precipitation weight, and normalized freeze-thaw cycle index weight are obtained using the following formulas: Where j = 1, 2, or 3, , , , These are the normalized weights.

8. The method for designing and selecting asphalt mixture gradation based on performance, as described in claim 7, is characterized in that: The normalized CA ratio weight, normalized precipitation weight, and normalized freeze-thaw cycle index weight are used. Weights and CA ratio scores, FA C with FA f average score The total score S is obtained using the following formula: in, It is the normalized CA ratio weight. It is the normalized precipitation weight. It is the normalized freeze-thaw cycle index weight.

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