Recycled asphalt mixture tensile and compressive fatigue characteristic prediction method, device, and medium

Abstract

The present invention relates to the technical field of analysis of recycled asphalt mixtures. Disclosed are a recycled asphalt mixture tensile and compressive fatigue characteristic prediction method, a device, and a medium. The method comprises: constructing a target tensile dynamic modulus principal curve of a target asphalt mixture; extracting a target tensile effective elastic ratio on the basis of the target tensile dynamic modulus principal curve; inputting the target tensile effective elastic ratio into a pre-constructed viscoelasticity-tensile fatigue curve to generate a target tensile fatigue characteristic; constructing a target compressive dynamic modulus principal curve of the target asphalt mixture; extracting a target compressive effective elastic ratio on the basis of the target compressive dynamic modulus principal curve; and inputting the target compressive effective elastic ratio into a pre-constructed first viscoelasticity-compressive fatigue curve to generate a target compressive fatigue characteristic. By applying the present invention, the fatigue characteristic prediction precision can be greatly improved, and the fatigue testing amount and time can be reduced.

Description

Prediction method, equipment and medium for tensile and compressive fatigue characteristics of recycled asphalt mixture Technical Field

[0001] The present invention relates to the technical field of analysis of recycled asphalt mixtures, and in particular to a method, equipment and medium for predicting tensile and compressive fatigue characteristics of recycled asphalt mixtures. Background Art

[0002] The extensive application of hot recycled asphalt mixture (HRAM) not only meets the "dual carbon" requirements, but also alleviates the shortage of stone materials. However, the choice of its fatigue performance evaluation method has always been controversial.

[0003] At present, researchers mainly predict its fatigue performance through test methods such as three-point bending, four-point bending and indirect tensile fatigue. Among them, the three-point bending, four-point bending and indirect tensile fatigue test methods all assume that HRAM is an elastomer, while asphalt mixture is actually a viscoelastic material. Therefore, the three-point bending, four-point bending and indirect tensile fatigue test methods often lead to the conclusion that the ranking of fatigue test results of different HRAM dosages is inconsistent with common sense.

[0004] In summary, in order to clearly and effectively distinguish the fatigue performance of HRAM, a new fatigue prediction method needs to be constructed. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a method, equipment and medium for predicting the tensile and compressive fatigue properties of recycled asphalt mixture, which can greatly improve the prediction accuracy of fatigue properties and reduce the amount and time of fatigue testing.

[0006] In order to solve the above technical problems, the present invention provides a method, equipment and medium for predicting the tensile and compressive fatigue characteristics of recycled asphalt mixture, including: constructing a target tensile dynamic modulus master curve of the target asphalt mixture; extracting a target tensile effective elastic ratio based on the target tensile dynamic modulus master curve; inputting the target tensile effective elastic ratio into a pre-constructed viscoelastic-tensile fatigue curve to generate a target tensile fatigue characteristic; constructing a target compression dynamic modulus master curve of the target asphalt mixture; extracting a target compression effective elastic ratio based on the target compression dynamic modulus master curve; inputting the target compression effective elastic ratio into a pre-constructed first viscoelastic-compression fatigue curve to generate a target compression fatigue characteristic.

[0007] As an improvement of the above scheme, the target tensile effective elasticity ratio is the ratio of the sum of the elastic interval and the viscoelastic front section to the sum of the elastic interval and the viscoelastic interval in the target tensile dynamic modulus master curve; the target compression effective elasticity ratio is the ratio of the sum of the elastic interval and the viscoelastic front section to the sum of the elastic interval and the viscoelastic interval in the target compression dynamic modulus master curve.

[0008] As an improvement of the above-mentioned scheme, the method for predicting the tensile and compressive fatigue characteristics of recycled asphalt mixture also includes: extracting a target compression effective viscoelastic ratio based on the target compression dynamic modulus master curve, the target compression effective viscoelastic ratio being the proportion of the viscoelastic front section to the viscoelastic interval in the target compression dynamic modulus master curve; inputting the target compression effective viscoelastic ratio into a pre-constructed second viscoelastic-compression fatigue curve to generate target compression fatigue characteristics.

[0009] As an improvement of the above-mentioned scheme, the method for constructing the viscoelastic-tensile fatigue curve includes: constructing a baseline tensile dynamic modulus master curve of a baseline asphalt mixture; extracting a baseline tensile effective elastic ratio based on the baseline tensile dynamic modulus master curve; performing a direct tensile fatigue test on the baseline asphalt mixture to generate a baseline tensile fatigue characteristic; and generating a viscoelastic-tensile fatigue curve based on the relationship between the baseline tensile effective elastic ratio and the baseline tensile fatigue characteristic.

[0010] As an improvement of the above-mentioned scheme, the method for constructing the first viscoelastic-compression fatigue curve includes: constructing a baseline compression dynamic modulus master curve of a baseline asphalt mixture; extracting a baseline compression effective elastic ratio based on the baseline compression dynamic modulus master curve; performing a direct compression fatigue test on the baseline asphalt mixture to generate a baseline compression fatigue characteristic; and generating a first viscoelastic-compression fatigue curve based on the relationship between the baseline compression effective elastic ratio and the baseline compression fatigue characteristic.

[0011] As an improvement of the above-mentioned scheme, the method for constructing the second viscoelastic-compression fatigue curve includes: constructing a baseline compression dynamic modulus master curve of a baseline asphalt mixture; extracting a baseline compression effective viscoelastic ratio based on the baseline compression dynamic modulus master curve; performing a direct compression fatigue test on the baseline asphalt mixture to generate a baseline compression fatigue characteristic; and generating a second viscoelastic-compression fatigue curve based on the relationship between the baseline compression effective viscoelastic ratio and the baseline compression fatigue characteristic.

[0012] As an improvement of the above-mentioned scheme, the method for predicting the tensile and compressive fatigue characteristics of the recycled asphalt mixture also includes: extracting evaluation indicators based on the target dynamic modulus master curve, the target dynamic modulus master curve includes the target tensile dynamic modulus master curve and the target compressive dynamic modulus master curve; based on the relationship between the evaluation indicators, predicting the viscoelastic properties of the target asphalt mixture.

[0013] As an improvement of the above scheme, the evaluation indicators include time indicators, interval indicators and ratio indicators; the time indicators include stress relaxation start time, maximum flow time and ultimate stiffness time; the interval indicators include viscoelastic interval, viscoelastic front section and viscoelastic back section; the ratio indicators include elasticity proportion, effective elasticity ratio and effective viscoelastic ratio.

[0014] Accordingly, the present invention also provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein the processor implements the steps of the above-mentioned method for predicting the tensile and compressive fatigue characteristics of recycled asphalt mixture when executing the computer program.

[0015] Accordingly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of the above-mentioned method for predicting the tensile and compressive fatigue characteristics of recycled asphalt mixture are implemented.

[0016] The implementation of the present invention has the following beneficial effects:

[0017] The present invention clarifies the potential relationship between the effective elastic ratio and fatigue properties through pre-calculation, thereby constructing a targeted viscoelastic-tensile fatigue curve and a first viscoelastic-compression fatigue curve. The viscoelastic-tensile fatigue curve and the first viscoelastic-compression fatigue curve can be used to quickly predict the tensile and compressive fatigue properties of the target recycled asphalt mixture, greatly improving the fatigue property prediction accuracy and reducing the fatigue test volume and time.

[0018] At the same time, the present invention also introduces a second viscoelastic-compression fatigue curve to predict the target compression fatigue characteristics through a multi-curve method to ensure the accuracy of the target compression fatigue characteristics;

[0019] In addition, the present invention also extracts evaluation indicators to construct an HRAM viscoelasticity evaluation system, which effectively predicts the viscoelastic properties of the target asphalt mixture based on the viscoelastic nature, thereby providing a basis for the HRAM tensile and compressive fatigue characteristics and characterization. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] 1 is a flow chart of a first embodiment of a method for predicting tensile and compressive fatigue properties of recycled asphalt mixtures according to the present invention;

[0021] FIG2 is a schematic diagram of a dynamic modulus master curve in the present invention;

[0022] 3 is a flow chart of a second embodiment of a method for predicting tensile and compressive fatigue properties of recycled asphalt mixtures according to the present invention;

[0023] 4 is a flow chart of a third embodiment of a method for predicting tensile and compressive fatigue properties of recycled asphalt mixtures according to the present invention;

[0024] FIG5 is a schematic diagram of a compression dynamic modulus master curve in the present invention;

[0025] FIG6 is a schematic diagram of a master curve of tensile dynamic modulus in the present invention;

[0026] FIG7 is a double logarithmic coordinate diagram of direct tensile fatigue times and strain in the present invention;

[0027] FIG8 is a schematic diagram showing the relationship between the direct compression fatigue times and the compression effective elasticity ratio and the compression effective viscoelastic ratio in the present invention;

[0028] FIG9 is a schematic diagram showing the relationship between the direct stretching fatigue times and the stretching effective elasticity ratio in the present invention. DETAILED DESCRIPTION

[0029] In order to make the objectives, technical solutions and advantages of the present invention more clear, the present invention will be described in further detail below with reference to the accompanying drawings.

[0030] Referring to FIG1 , FIG1 shows a flow chart of a first embodiment of a method for predicting tensile and compressive fatigue properties of recycled asphalt mixtures according to the present invention, which includes:

[0031] S101, constructing a target tensile dynamic modulus master curve of a target asphalt mixture;

[0032] The target tensile dynamic modulus master curve of the target asphalt mixture was constructed according to the dynamic modulus master curve construction method described in "ZHANG Jinxi, JIANG Fan, WANG Chao et al. Evaluation of dynamic modulus of indoor and outdoor aged asphalt mixtures[J]. Journal of Construction Materials, 2017, 20(06): 937-942."

[0033] S102, extracting a target tensile effective elasticity ratio according to a target tensile dynamic modulus master curve;

[0034] As shown in Figure 2, E* represents the dynamic modulus, t r Indicates the reduction time, the dynamic modulus master curve can be divided into the elastic range W e , viscoelastic range W ve , viscosity interval W vd , viscoelastic front section W veq and viscoelastic posterior segment W veh ;

[0035] Among them, the target tensile effective elasticity ratio R eve The elastic range W in the target tensile dynamic modulus master curve is e With viscoelastic front section W veq The sum and elastic range W e and viscoelastic range W ve The ratio of the sum, that is: R eve=(W e +W veq ) / (W e +W ve )

[0036] S103, inputting the target tensile effective elasticity ratio into a previously constructed viscoelastic-tensile fatigue curve to generate a target tensile fatigue characteristic;

[0037] Furthermore, the method for constructing the viscoelastic-tensile fatigue curve includes:

[0038] (1) Constructing the master curve of the benchmark tensile dynamic modulus of the benchmark asphalt mixture;

[0039] (2) extracting the benchmark tensile effective elasticity ratio based on the benchmark tensile dynamic modulus master curve;

[0040] (3) Conducting direct tensile fatigue tests on a benchmark asphalt mixture to generate benchmark tensile fatigue properties;

[0041] Direct tensile fatigue testing of the target asphalt mixture was carried out according to the EU EN12697-26 Annex D test method to generate benchmark tensile fatigue properties.

[0042] (4) Based on the relationship between the baseline tensile effective elasticity ratio and the baseline tensile fatigue characteristics, a viscoelastic-tensile fatigue curve is generated.

[0043] It should be noted that there is a good relationship between the baseline tensile effective elasticity ratio and the baseline tensile fatigue properties at different strain levels. Therefore, a viscoelastic-tensile fatigue curve can be constructed based on the relationship between the baseline tensile effective elasticity ratio and the baseline tensile fatigue properties.

[0044] Accordingly, when constructing the relationship between the baseline tensile effective elastic ratio and the baseline tensile fatigue properties, the effective elastic ratio and fatigue properties must be placed in the same compressive or tensile state to ensure consistent directions. For example, the baseline tensile effective elastic ratio must correspond to the baseline tensile fatigue properties, and the baseline compressive effective elastic ratio must correspond to the baseline compressive fatigue properties.

[0045] Therefore, the target tensile fatigue characteristics of the target asphalt mixture can be generated by inputting the target tensile effective elastic ratio into the viscoelastic-tensile fatigue curve.

[0046] S104, constructing a target compression dynamic modulus master curve of the target asphalt mixture;

[0047] S105, extracting a target compression effective elastic ratio according to a target compression dynamic modulus master curve;

[0048] The target compression effective elasticity ratio is the ratio of the sum of the elastic interval and the viscoelastic front segment to the sum of the elastic interval and the viscoelastic interval in the target compression dynamic modulus master curve.

[0049] S106 , inputting the target compressive effective elasticity ratio into a pre-constructed first viscoelastic-compression fatigue curve to generate a target compressive fatigue characteristic.

[0050] Furthermore, the method for constructing the first viscoelastic-compression fatigue curve includes:

[0051] (1) Construct the benchmark compression dynamic modulus master curve of the benchmark asphalt mixture;

[0052] (2) Extracting the benchmark compression effective elasticity ratio based on the benchmark compression dynamic modulus master curve;

[0053] (3) Conduct direct compression fatigue tests on the benchmark asphalt mixture to generate benchmark compression fatigue properties;

[0054] Direct compression fatigue testing of the target asphalt mixture was carried out according to the American AASHTO T378-17 (TP79) test method to generate benchmark compression fatigue properties.

[0055] In order to compare with the direct tensile fatigue test method, the loading waveform, frequency, and test temperature are consistent with those of the direct tensile fatigue test. The strain control mode is also adopted, and the test is terminated when the vertical strain rate of the specimen is greater than 2.0 for five consecutive cycles during the fatigue process.

[0056] (4) Generate a first viscoelastic-compression fatigue curve based on the relationship between the baseline compression effective elastic ratio and the baseline compression fatigue characteristics.

[0057] It should be noted that there is a good relationship between the baseline compression effective elasticity ratio and the baseline compression fatigue characteristics. Therefore, a first viscoelastic-compression fatigue curve can be constructed based on the relationship between the baseline compression effective elasticity ratio and the baseline compression fatigue characteristics.

[0058] Therefore, the target compression fatigue characteristics of the target asphalt mixture can be generated by inputting the target compression effective elastic ratio into the first viscoelastic-compression fatigue curve.

[0059] Accordingly, accurate prediction of the tensile and compressive fatigue characteristics can be achieved by combining the target tensile fatigue characteristics generated in step S103 and the target compressive fatigue characteristics generated in step S106.

[0060] Unlike the prior art, the present invention clarifies the potential relationship between the effective elastic ratio and fatigue characteristics through pre-calculation, thereby constructing targeted viscoelastic-tensile fatigue curves and first viscoelastic-compression fatigue curves, and characterizes the relationship between the effective elastic ratio and tensile fatigue and compression fatigue through the viscoelastic-tensile fatigue curves and the first viscoelastic-compression fatigue curves. Therefore, the tensile and compressive fatigue characteristics of similar recycled asphalt mixtures can be quickly predicted through the viscoelastic-tensile fatigue curves and the first viscoelastic-compression fatigue curves, without the need for a large number of fatigue tests again, greatly improving the prediction accuracy of fatigue characteristics and reducing the amount and time of fatigue tests.

[0061] 3 , which shows a flow chart of a second embodiment of a method for predicting tensile and compressive fatigue properties of recycled asphalt mixtures according to the present invention, comprising:

[0062] S201, constructing a target tensile dynamic modulus master curve of a target asphalt mixture;

[0063] S202, extracting a target tensile effective elasticity ratio according to a target tensile dynamic modulus master curve;

[0064] S203, inputting the target tensile effective elasticity ratio into a previously constructed viscoelastic-tensile fatigue curve to generate a target tensile fatigue characteristic;

[0065] S204, constructing a target compression dynamic modulus master curve of the target asphalt mixture;

[0066] S205, extracting a target compression effective elastic ratio and a target compression effective viscoelastic ratio according to a target compression dynamic modulus master curve;

[0067] S206 , inputting the target compressive effective elastic ratio into a pre-constructed first viscoelastic-compressive fatigue curve to generate a target compressive fatigue characteristic.

[0068] S207, extracting a target compressive effective viscoelastic ratio according to a target compressive dynamic modulus master curve;

[0069] As shown in Figure 2, the target compressive effective viscoelastic ratio R vee In the target compression dynamic modulus master curve, the viscoelastic front section W veq Occupies viscoelastic range W ve The ratio, that is: R vee =W veq / W ve

[0070] S208 : Input the target compressive effective viscoelastic ratio into a pre-constructed second viscoelastic-compression fatigue curve to generate a target compressive fatigue characteristic.

[0071] Accordingly, the method for constructing the second viscoelastic-compression fatigue curve includes:

[0072] (1) Construct the benchmark compression dynamic modulus master curve of the benchmark asphalt mixture;

[0073] (2) Extracting the benchmark compression effective viscoelastic ratio based on the benchmark compression dynamic modulus master curve;

[0074] (3) Conduct direct compression fatigue tests on the benchmark asphalt mixture to generate benchmark compression fatigue properties;

[0075] (4) A second viscoelastic-compression fatigue curve is generated based on the relationship between the baseline compression effective viscoelastic ratio and the baseline compression fatigue characteristics.

[0076] It should be noted that there is a good relationship between the baseline compression effective viscoelastic ratio and the baseline compression fatigue characteristics. Therefore, a second viscoelastic-compression fatigue curve can be constructed based on the relationship between the baseline compression effective viscoelastic ratio and the baseline compression fatigue characteristics.

[0077] However, since the correlation between the baseline compression effective elasticity ratio and the baseline compression fatigue characteristics is higher than the correlation between the baseline compression effective viscoelastic ratio and the baseline compression fatigue characteristics, when determining the target compression fatigue characteristics, the results of the first viscoelastic-compression fatigue curve are mainly used, and the results of the second viscoelastic-compression fatigue curve are supplemented. The target compression fatigue characteristics are verified from multiple perspectives to ensure the accuracy of the target compression fatigue characteristics.

[0078] 4 , which shows a flow chart of a third embodiment of a method for predicting tensile and compressive fatigue properties of recycled asphalt mixtures according to the present invention, comprising:

[0079] S301, constructing a target tensile dynamic modulus master curve of a target asphalt mixture;

[0080] S302, extracting a target tensile effective elasticity ratio according to a target tensile dynamic modulus master curve;

[0081] S303, inputting the target tensile effective elasticity ratio into a previously constructed viscoelastic-tensile fatigue curve to generate a target tensile fatigue characteristic;

[0082] S304, constructing a target compression dynamic modulus master curve of the target asphalt mixture;

[0083] S305, extracting a target compression effective elastic ratio and a target compression effective viscoelastic ratio according to a target compression dynamic modulus master curve;

[0084] S306 , inputting the target compressive effective elastic ratio into a pre-constructed first viscoelastic-compression fatigue curve to generate a target compressive fatigue characteristic.

[0085] S307, extracting evaluation indicators based on the target dynamic modulus master curve;

[0086] The target dynamic modulus master curve includes a target tensile dynamic modulus master curve and a target compressive dynamic modulus master curve; the evaluation indicators include time indicators, interval indicators and ratio indicators.

[0087] As shown in Figure 2, the dynamic modulus master curve contains rich viscoelastic information. The dynamic modulus master curve can be divided into three major intervals: elasticity, viscoelasticity, and viscosity. By extracting the key points on the dynamic modulus master curve, three major categories of indicators can be constructed: time indicators, interval indicators, and ratio indicators.

[0088] 1. Time indicators

[0089] Time-related indicators include ultimate elastic time t0, stress relaxation starting time t s1 , maximum flow time t c and ultimate stiffness time t e Four indicators.

[0090] in:

[0091] t0 takes a fixed value of 10 -5 s;

[0092] t s1 is the dividing point between elastic deformation and delayed elastic deformation of asphalt mixture. Delayed elasticity characterizes the relaxation characteristics of the mixture. s1 is the stress relaxation starting time;

[0093] t c It is the inflection point where the rate of change of asphalt mixture stiffness changes from fast to slow;

[0094] t e It is the turning point of asphalt mixture transition from elastic zone to viscoelastic zone. -5 , lgE*) and point (lgt c , lgE*) are respectively drawn as tangents to the main curve of the dynamic modulus, and the horizontal coordinate of the intersection of the two straight lines is t e .

[0095] 2. Interval Indicators

[0096] Interval indicators include elastic interval W e , viscoelastic range W ve , viscosity interval W vd , viscoelastic front section W veq and viscoelastic posterior segment W veh .

[0097] Among them, [t0, t e ] is W e ,[t e , t c ] is W ve ,[t c, t d ] is W vd ,[t e , t s1 ] is W veq ,[t s1 , t c ] is W veh , and W ve =W veq +W veh .

[0098] 3. Ratio indicators

[0099] Ratio indicators include elasticity ratio R e , effective elastic ratio R eve and effective viscoelastic ratio R vee .

[0100] in:

[0101] R e W e Account for (W e +W ve ) ratio, then 1-R e is the viscoelastic ratio;

[0102] R eve Indicates (W e +W veq ) accounts for (W e +W ve ) ratio;

[0103] R vee W veq W ve proportion.

[0104] The specific calculation formula is as follows: R e =W e / (W e +W ve )=(t e -t0) / (t c -t0) R eve =(W e +W veq ) / (W e +W ve )=(t s1 -t0) / (t c -t0) R vee =W veq / W ve =(t s1 -t e ) / (t c -t e )

[0105] Among the 12 indicators proposed above, t0 takes a fixed value, t e With W e Synonymous, t c With W vd Therefore, the 12 indicators are simplified into 9 indicators, namely, the time indicators include the stress relaxation starting time, the maximum flow time and the ultimate stiffness time; the interval indicators include the viscoelastic interval, the viscoelastic front section and the viscoelastic back section; the ratio indicators include the elastic proportion, the effective elastic ratio and the effective viscoelastic ratio.

[0106] S308: Predict the viscoelastic properties of the target asphalt mixture based on the relationship between the evaluation indicators.

[0107] From the definitions of each indicator, it can be seen that the time-type indicator is the core of the dynamic modulus master curve, the interval-type indicator is a derivative indicator of the time-type indicator, and the ratio-type indicator is a derivative indicator of the interval-type indicator; the time-type indicator reflects the inherent viscoelastic properties of asphalt mixture, and the interval-type indicator and ratio-type indicator are a supplement and extension of the inherent properties; by comparing various indicators of different materials, the viscoelastic properties of the materials can be distinguished.

[0108] Accordingly, the present invention further discloses a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein when the processor executes the computer program, the steps of the aforementioned method for predicting the tensile and compressive fatigue properties of a recycled asphalt mixture are implemented. Furthermore, the present invention further discloses a computer-readable storage medium storing the computer program, wherein when the processor executes the computer program, the steps of the aforementioned method for predicting the tensile and compressive fatigue properties of a recycled asphalt mixture are implemented.

[0109] Therefore, the present invention constructs a targeted viscoelastic-tensile fatigue curve and a first viscoelastic-compression fatigue curve, and the tensile and compressive fatigue properties of the recycled asphalt mixture can be quickly predicted through the viscoelastic-tensile fatigue curve and the first viscoelastic-compression fatigue curve, greatly reducing the amount and time of fatigue testing; at the same time, the present invention also introduces a second viscoelastic-compression fatigue curve, and predicts the target compression fatigue properties through a multi-curve method to ensure the accuracy of the target compression fatigue properties; in addition, the present invention also extracts evaluation indicators to construct an HRAM viscoelastic evaluation system, starting from the viscoelastic nature, and effectively predicts the viscoelastic properties of the target asphalt mixture, thereby providing a basis for HRAM tensile and compressive fatigue properties and characterization.

[0110] The present invention is further described in detail below with reference to specific embodiments:

[0111] Step (1): Baseline asphalt mixture

[0112] The base asphalt adopts the commonly used domestic 70# road petroleum asphalt, and its basic properties are: 25℃ needle penetration is 66.5 (0.1mm), softening point is 47.5℃, 10℃ elongation is 32cm; after film oven aging, the 25℃ needle penetration ratio is 69, and the 10℃ elongation is 7.5cm;

[0113] The aggregate is limestone from Xinhui District, Jiangmen City. After hot screening, the specifications are 23-32mm, 17-23mm, 11-17mm, 6-11mm, 3.5-6mm and 0-3.5mm;

[0114] After crushing and screening, the reclaimed asphalt pavement (RAP) was divided into three grades: 0-10 mm, 10-15 mm, and 15-25 mm. The asphalt contents were 5.30%, 2.53%, and 3.30%, respectively. The basic properties of the RAP-extracted asphalt were: a needle penetration of 16.2 (0.1 mm) at 25°C, a softening point of 70.6°C, and a Brookfield viscosity of 2.95 Pa˙s at 135°C.

[0115] The research object was AC-25 recycled asphalt mixture, with RAP content of 0%, 30%, 45%, and 60%, respectively, referred to as R-0, R-30, R-45, and R-60. Among them, R-60 was mixed with FBK rejuvenator, and the rejuvenator dosage was 5% of the old asphalt mass in RAP, and the rejuvenator dosage was included in the asphalt content. The technical parameters of the four groups of HRAM are shown in Table 1:

[0116] Table 1

[0117] Step (2), constructing a dynamic modulus master curve of a benchmark asphalt mixture;

[0118] The dynamic modulus master curve construction method was used to obtain the compression dynamic modulus master curves (see Figure 5) and the tension dynamic modulus master curves (see Figure 6) of four groups of asphalt mixtures. The parameters are shown in Table 2:

[0119] Table 2

[0120] Correspondingly, by taking the derivative of the dynamic modulus master curve function y = f(t), it is found that the third-order derivative function of the compression dynamic modulus master curve has two zero points, while the number of zero points of the third-order derivative function of the tension dynamic modulus master curve is not uniform, and the derivative function has two zero points and only one zero point. When the third-order derivative function has two zero points, the values ​​of the derivative function in each interval are shown in Table 3; when there is only one zero point, the values ​​are shown in Table 4.

[0121] When the third-order derivative function of the dynamic modulus master curve has two zeros, f'(t)<0, the master curve decreases monotonically; f"(tc )=0,t c is the concave and convex inflection point of the main curve; f"'(t s1 )=0 and f″'(t s2 )=0,t s1 and t s2 is the inflection point of the derivative function f'(t); when there is only one zero point, as shown in Table 4, f'(t) < 0, the main curve decreases monotonically; f" (t c )=0,(t c is the concave and convex inflection point of the main curve; f"'(t s1 )=0,t s1 It is the inflection point of the derivative function f'(t).

[0122] Table 3

[0123] Table 4

[0124] Step (3), extracting the effective elastic ratio and / or the effective viscoelastic ratio based on the dynamic modulus master curve;

[0125] The values ​​of various indicators extracted from the dynamic modulus master curve are shown in Table 5 and Table 6:

[0126] Table 5 - Values ​​of various indicators of the compression dynamic modulus master curve

[0127] Table 6 - Values ​​of various indicators of the main curve of tensile dynamic modulus

[0128] Accordingly, the compression effective elastic ratio R corresponding to the compression dynamic modulus master curve is extracted. eve and compression effective viscoelastic ratio R vee , and extract the tensile effective elastic ratio R corresponding to the tensile dynamic modulus master curve eve .

[0129] In addition, the comprehensive values ​​of various indicators show that:

[0130] (1) In the commonly used service time domain, the third-order derivative of the main curve of the compression dynamic modulus of the four groups of mixtures is t s1 , t s2 Both exist, the third derivative zero point of the R-0 tensile dynamic modulus master curve t s1 , t s2 There is only one zero point t in the third derivative of the main curve of the tensile dynamic modulus of R-30, R-45, and R-60. s1 , no t s2; In compression mode, the four groups of asphalt mixtures all have elastic, viscoelastic and viscous responses; in tension mode, R-0 has elastic, viscoelastic and viscous responses, while the three groups of recycled asphalt mixtures R-30, R-45 and R-60 only have elastic and viscoelastic responses, and no viscous response.

[0131] (2) Under compression mode, the time index (t e , t s1 , t c ) overall rightward shift, interval index W ve All decrease, ratio index R e increased, indicating that the elastic range of asphalt mortar becomes larger, the elastic proportion increases, and the viscoelastic range becomes smaller; with the increase of RAP content, W veh 、W veq Both decrease first and then increase, indicating that the ratio of the viscoelastic front and back segments in the viscoelastic range changes; R eve and R vee The effective elasticity and effective viscoelasticity of asphalt mixture increased; under compression mode, the overall W ve becomes smaller, but R eve and R vee The proportion increases; W veq The reason for the change in W is related to the stress characteristics of the asphalt mixture material system. Under compression mode, the asphalt mixture relies on the asphalt and aggregate system to resist external loads, including bonding force, mineral skeleton embedding force, etc. The asphalt in RAP ages and hardens, and the coupling effect of the increase in asphalt mortar bonding force and aggregate embedding force causes W to change. ve Smaller, R eve and R vee The proportion increased; it can be seen that under compression mode, compared with new asphalt mixture, the recycled mixture is "elastic but not viscoelastic enough, but viscoelastic enough to be effective."

[0132] (3) Under the tensile mode, the three groups of recycled asphalt mixtures had no viscous response. Compared with the new asphalt mixture, the recycled mixture was “elastic but not sticky”. Under the tensile mode, the mixture mainly relied on the bonding force between the asphalt mortar and the aggregate to resist the external load. When approaching the maximum flow time, under the compression mode, the mixture system had sufficient strength reserve to resist the external force, while under the tensile mode, the bonding force between the asphalt mortar and the aggregate was insufficient to resist the external load. It can be seen that the different resistance modes of the mixture system resulted in significant differences in the viscoelastic response under different compression and tensile stress modes.

[0133] (4) Based on the viscoelastic response characteristics of recycled asphalt mixtures under tensile mode, a comparative analysis of three groups of recycled asphalt mixtures was conducted; with the increase of RAP content, the three major indicators except R veeExcept for the RAP content, the other eight indicators showed a trend of decreasing first and then increasing. In addition, under the tensile mode, with the increase of RAP content, R vee The index has been decreasing. Although it has good adaptability in compression mode, it has poor adaptability in tension mode.

[0134] (5) Under compression mode, the time index, interval index and ratio index of R-60 are generally between R-30 and R-45. Under tension mode, the time index and ratio index of R-60 are generally between R-30 and R-45, indicating that the elasticity and viscoelasticity are restored after adding the regeneration agent.

[0135] Step (4): Perform direct compression fatigue test and direct tensile fatigue test on the benchmark asphalt mixture to generate benchmark tensile fatigue properties. The specific test method is shown in Table 7 below.

[0136] Table 7

[0137] It should be noted that the direct compression test time is too long. In order to compare with the direct tensile test, only the direct compression test with a strain level of 100με was carried out. Three specimens were used for each strain level. The direct compression test results are shown in Table 8:

[0138] Table 8

[0139] It can be seen from Table 8 that the direct compression fatigue life of the four groups of 100με mixtures is ranked as follows: R-45>R-60>R-30>R-0.

[0140] As shown in Figure 7, in the direct tensile test, at each strain level, the direct tensile fatigue life of the four groups of mixtures is ranked as follows: R-0>R-30>R-60>R-45; at the same time, within the strain level range of the present invention, the upper and lower limits of the strain level do not exceed 100με, but the fatigue times span two orders of magnitude, indicating that the direct tensile times are sensitive to the strain level.

[0141] Step (5): constructing a first viscoelastic-compression fatigue curve, a second viscoelastic-compression fatigue curve, and a viscoelastic-tensile fatigue curve.

[0142] According to the relationship between the compression effective elasticity ratio and the compression fatigue characteristics, the first viscoelastic-compression fatigue curve is generated: y=0.31x-1.0948 (see Figure 8), where y is the compression effective elasticity ratio, Nf is the compression fatigue characteristics, and x=lg(Nf).

[0143] According to the relationship between the compression effective viscoelastic ratio and the compression fatigue characteristics, a second viscoelastic-compression fatigue curve is generated: y = 0.3091x-1.4746 (see Figure 8), where y is the compression effective viscoelastic ratio, Nf is the compression fatigue characteristics, and x = lg(Nf).

[0144] According to the relationship between the tensile effective elasticity ratio and the tensile fatigue characteristics, the viscoelastic-tensile fatigue curve is generated: y = 0.0826x + 0.4423, y = 0.0456x + 0.5302, y = 0.0827x + 0.4365 (see Figure 9), where y is the tensile effective elasticity ratio, Nf is the tensile fatigue characteristic, and x = lg(Nf).

[0145] Step (six), referring to step (two), constructing a compression dynamic modulus master curve and a tension dynamic modulus master curve of the target asphalt mixture;

[0146] Step (seven), referring to step (three), extracts the compression effective elastic ratio, compression effective viscoelastic ratio, tensile effective elastic ratio and evaluation indexes according to the compression dynamic modulus master curve and the tensile dynamic modulus master curve, and predicts the viscoelastic properties of the target asphalt mixture based on the relationship between the evaluation indexes.

[0147] Step (eight): Substitute the compression effective elasticity ratio into the first viscoelastic-compression fatigue curve y = 0.31x-1.0948 to calculate the compression fatigue characteristics, substitute the compression effective viscoelastic ratio into the second viscoelastic-compression fatigue curve y = 0.3091x-1.4746 to verify the compression fatigue characteristics, and substitute the tensile effective elasticity ratio into the corresponding viscoelastic-tensile fatigue curve (y = 0.0826x + 0.4423, y = 0.0456x + 0.5302 or y = 0.0827x + 0.4365) to calculate the tensile fatigue characteristics.

[0148] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for predicting the tensile and compressive fatigue characteristics of recycled asphalt mixture, characterized in that, include: Constructing the target tensile dynamic modulus master curve of the target asphalt mixture; extracting a target tensile effective elasticity ratio according to the target tensile dynamic modulus master curve; Inputting the target tensile effective elasticity ratio into a pre-constructed viscoelastic-tensile fatigue curve to generate target tensile fatigue characteristics; Constructing the target compression dynamic modulus master curve of the target asphalt mixture; extracting a target compression effective elastic ratio according to the target compression dynamic modulus master curve; The target compressive effective elastic ratio is input into a first viscoelastic-compression fatigue curve constructed in advance to generate target compressive fatigue characteristics.

2. The method for predicting the tensile and compressive fatigue properties of recycled asphalt mixture according to claim 1, characterized in that: The target tensile effective elasticity ratio is the ratio of the sum of the elastic interval and the viscoelastic front segment to the sum of the elastic interval and the viscoelastic interval in the target tensile dynamic modulus master curve; The target compressive effective elasticity ratio is the ratio of the sum of the elastic interval and the viscoelastic front segment to the sum of the elastic interval and the viscoelastic interval in the target compressive dynamic modulus master curve.

3. The method for predicting the tensile and compressive fatigue characteristics of recycled asphalt mixture according to claim 1, wherein, Also includes: Extracting a target compressive effective viscoelastic ratio according to the target compressive dynamic modulus master curve, wherein the target compressive effective viscoelastic ratio is the ratio of the viscoelastic front segment to the viscoelastic interval in the target compressive dynamic modulus master curve; The target compressive effective viscoelastic ratio is input into a pre-constructed second viscoelastic-compression fatigue curve to generate target compressive fatigue characteristics.

4. The prediction method for the tensile and compressive fatigue characteristics of recycled asphalt mixture according to claim 1, characterized in that, The method for constructing the viscoelastic-tensile fatigue curve includes: Constructing a master curve of the benchmark tensile dynamic modulus of the benchmark asphalt mixture; extracting a reference tensile effective elasticity ratio according to the reference tensile dynamic modulus master curve; performing a direct tensile fatigue test on the benchmark asphalt mixture to generate a benchmark tensile fatigue property; A viscoelastic-tensile fatigue curve is generated according to the relationship between the reference tensile effective elasticity ratio and the reference tensile fatigue property.

5. The method for predicting the tensile and compressive fatigue characteristics of recycled asphalt mixture according to claim 1, characterized in that, The method for constructing the first viscoelastic-compression fatigue curve includes: Constructing a master curve of the benchmark compression dynamic modulus of the benchmark asphalt mixture; extracting a reference compression effective elastic ratio according to the reference compression dynamic modulus master curve; performing a direct compression fatigue test on the benchmark asphalt mixture to generate benchmark compression fatigue properties; A first viscoelastic-compression fatigue curve is generated according to the relationship between the reference compression effective elasticity ratio and the reference compression fatigue characteristic.

6. The method for predicting the tensile and compressive fatigue characteristics of recycled asphalt mixture according to claim 3, characterized in that, The method for constructing the second viscoelastic-compression fatigue curve includes: Constructing a master curve of the benchmark compression dynamic modulus of the benchmark asphalt mixture; extracting a reference compression effective viscoelastic ratio according to the reference compression dynamic modulus master curve; performing a direct compression fatigue test on the benchmark asphalt mixture to generate benchmark compression fatigue properties; A second viscoelastic-compression fatigue curve is generated according to the relationship between the reference compression effective viscoelastic ratio and the reference compression fatigue characteristic.

7. The method for predicting the tensile and compressive fatigue properties of recycled asphalt mixture according to claim 1, wherein: Also includes: Extracting evaluation indicators according to the target dynamic modulus master curve, wherein the target dynamic modulus master curve includes the target tensile dynamic modulus master curve and the target compressive dynamic modulus master curve; The viscoelastic properties of the target asphalt mixture are predicted based on the relationship between the evaluation indicators.

8. The method for predicting the tensile and compressive fatigue characteristics of recycled asphalt mixture according to claim 7, wherein, The evaluation indicators include time indicators, interval indicators and ratio indicators; The time-based indicators include the stress relaxation start time, the maximum flow time, and the ultimate stiffness time; The interval-based indicators include the viscoelastic interval, the pre-viscoelastic segment, and the post-viscoelastic segment; The ratio-based indicators include the elastic proportion, the effective elastic ratio, and the effective viscoelastic ratio.

9. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method described in any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the method described in any one of claims 1 to 8.

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