Road fatigue performance evaluation method based on dynamic modulus

Abstract

This application relates to the field of pavement maintenance technology, and in particular to a method for evaluating road fatigue performance based on dynamic modulus. The method includes: constructing a correlation curve representing the mapping relationship between the dynamic modulus, which characterizes pavement rigidity, and the fatigue life of the pavement; setting a critical fatigue life threshold for judging fatigue performance; determining the ultimate modulus boundary in the correlation curve based on the critical fatigue life threshold; obtaining core samples of the in-service pavement; measuring the measured dynamic modulus at a preset evaluation frequency; and judging the pavement condition based on the positional relationship between the measured dynamic modulus and the ultimate modulus boundary. This application improves the timeliness of fatigue performance evaluation of recycled asphalt mixtures.

Description

Technical Field

[0001] This application relates to the field of road maintenance technology, and in particular to a method for evaluating road fatigue performance based on dynamic modulus. Background Technology

[0002] Reclaimed asphalt technology is an important technical approach in road engineering for reusing old asphalt pavement materials. By incorporating reclaimed asphalt pavement (RAP) back into fresh asphalt mixtures, material recycling and reduced material consumption can be achieved, thus leading to its continued application in highway maintenance and reconstruction projects. During the long-term service of recycled asphalt pavements, the mixture gradually deteriorates under vehicle loads, temperature changes, and environmental conditions. Fatigue cracking is one of the key factors affecting pavement durability. When the fatigue performance of recycled asphalt mixtures decreases, the pavement structure is more prone to cracking under repeated loads, thereby affecting the road's service life.

[0003] In existing technologies, the evaluation of the fatigue performance of recycled asphalt mixtures typically relies on laboratory fatigue tests. For example, cyclic loading tests, such as semi-circular bending tests, four-point bending tests, or similar cyclic loading tests, apply periodic loads to pavement material specimens under laboratory conditions. The fatigue life is determined by recording the number of loading cycles at which the pavement material specimens fail, thus evaluating the material's fatigue resistance. These testing methods can reflect the fatigue failure characteristics of materials under cyclic loading to a certain extent, and are therefore used in materials research and mix design stages.

[0004] The aforementioned evaluation methods still have certain limitations. On the one hand, fatigue testing typically requires long loading times and complex test conditions, resulting in a lengthy testing cycle and low detection efficiency, making it difficult to implement quickly in engineering inspections or pavement service condition assessments. On the other hand, these methods usually rely on specially prepared pavement material specimens and laboratory loading equipment, making it difficult to directly reflect the performance changes of actual road structures during long-term service. When it is necessary to assess the service condition of existing recycled asphalt pavements, relying solely on traditional fatigue testing often fails to provide timely evaluation results, thus affecting the timeliness of road maintenance decisions. Summary of the Invention

[0005] To improve the timeliness of fatigue performance evaluation of recycled asphalt mixtures, this application provides a road fatigue performance evaluation method based on dynamic modulus.

[0006] Firstly, this application provides a road fatigue performance evaluation method based on dynamic modulus, employing the following technical solution: The road fatigue performance evaluation method based on dynamic modulus includes: constructing a correlation curve that maps the dynamic modulus characterizing pavement rigidity to the fatigue life of the pavement. Set a critical life threshold for fatigue life to determine the quality of fatigue performance. Determine the limiting modulus boundary from the correlation curve based on the critical lifetime threshold; Obtain core samples of the service road surface; measure its measured dynamic modulus at a preset evaluation frequency; and determine the road surface condition based on the positional relationship between the measured dynamic modulus and the limit modulus boundary.

[0007] First, a correlation curve between dynamic modulus and fatigue life is constructed to establish a quantifiable mapping relationship between material stiffness indices and durability performance. Further, by setting a critical fatigue life threshold, the material's fatigue performance is divided into identifiable critical intervals, improving the consistency and comparability of evaluation results. Then, based on the dynamic moduli corresponding to the critical life thresholds in the correlation curve, the ultimate modulus boundary is determined, thereby establishing an ultimate modulus evaluation benchmark that reflects the material's failure risk. Finally, by acquiring core samples of the in-service pavement and measuring their measured dynamic modulus at a preset evaluation frequency, the positional relationship between the mechanical state of the actual pavement material and the ultimate modulus boundary can be compared to determine whether the pavement structure is within its safe service range.

[0008] In summary, this application transforms destructive fatigue testing into a rapid evaluation method based on modulus testing, which not only significantly shortens the testing cycle but also enables direct condition assessment of existing road structures, thereby solving the problems of long fatigue testing cycles, low testing efficiency, and difficulty in rapidly assessing the fatigue performance of existing pavements in the prior art.

[0009] Optionally, a correlation curve is constructed to characterize the dynamic modulus of pavement rigidity and the fatigue life of pavement, including: obtaining multiple groups of pavement material specimens with different RAP contents; measuring the dynamic modulus of each group of pavement material specimens within a set loading frequency range; measuring the fatigue life of each group of specimens; and fitting the dynamic modulus of multiple groups of pavement material specimens with different RAP contents at the same loading frequency to obtain the correlation curve.

[0010] Since the mechanical properties of recycled asphalt mixtures are significantly correlated with the RAP content, and different RAP contents correspond to different degrees of material aging, constructing specimens with different RAP contents can simulate the entire process of material performance changes from the initial state to the severely aged state. This allows the obtained data to cover the main performance stages within the material's service life. Furthermore, compared to directly obtaining pavement materials at different service times, this method is more controllable and convenient, and easier to obtain data in a laboratory environment. Further, fitting the dynamic modulus of specimens with different RAP contents under the same loading frequency conditions yields the correlation curve between dynamic modulus and fatigue life.

[0011] Optionally, a critical life threshold for fatigue life is set to determine the quality of fatigue performance, including: using the fatigue life of a pavement material specimen without RAP as a reference life, and setting a value within a preset proportion range of the reference life as the critical life threshold.

[0012] Since different test conditions, material ratios, and environmental factors all affect the absolute value of fatigue life, directly using absolute life as the evaluation criterion can easily lead to a lack of comparability in evaluation results under different test environments. This step uses the life of the material without RAP as a benchmark value and normalizes it into a unified reference standard. Then, it determines the key life threshold according to a preset ratio, transforming the evaluation of material fatigue performance from an absolute value into a relative performance index, thereby reducing the impact of environmental differences on the evaluation results.

[0013] Optionally, the limiting modulus boundary is determined in the correlation curve based on the critical lifetime threshold, including: extracting the dynamic modulus at different loading frequencies corresponding to the critical lifetime threshold from the correlation curve, and fitting the dynamic modulus to obtain the limiting modulus boundary.

[0014] Extracting the dynamic modulus corresponding to the critical life threshold allows us to obtain the stiffness characteristics of the material under critical fatigue conditions. The limiting modulus boundary obtained by fitting these data constitutes the criterion for judging the material's fatigue performance. When the dynamic modulus obtained from field testing exceeds this limiting boundary, it can be determined that the material is approaching or has reached a fatigue failure state. This technical feature transforms the complex problem of fatigue life evaluation into a simple modulus comparison problem, not only reducing experimental steps but also enabling unified evaluation under different loading frequencies, thus improving the applicability of the evaluation method.

[0015] Optionally, a log-linear function can be used to fit the dynamic modulus at different loading frequencies corresponding to the key lifetime threshold extracted from the correlation curve.

[0016] Asphalt mixtures are typical viscoelastic materials, and their mechanical response exhibits nonlinear characteristics as the loading frequency changes. If a simple linear function is used for fitting, it is difficult to accurately describe the trend of stiffness variation. This scheme employs a logarithmic linear function for fitting, incorporating the loading frequency in logarithmic form into the calculation, thereby better describing the nonlinear characteristics of stiffness variation under low and high frequency conditions.

[0017] Optionally, the measured dynamic modulus at a preset evaluation frequency is determined, and the pavement condition is judged based on the positional relationship between the measured dynamic modulus and the limit modulus boundary, including: determining the corresponding dynamic modulus in the limit modulus boundary according to the evaluation frequency, comparing the measured dynamic modulus with the corresponding dynamic modulus in the limit modulus boundary, and confirming pavement health in response to the measured dynamic modulus being less than or equal to the corresponding dynamic modulus in the limit modulus boundary.

[0018] The ultimate modulus boundary represents the boundary between rigid failure and non-rigid failure of pavement materials. By comparing the measured modulus of the core sample with this boundary, the state of the pavement can be quickly determined.

[0019] Optionally, multiple evaluation frequencies can be set, and the measured dynamic modulus at multiple evaluation frequencies can be compared with the corresponding dynamic modulus in the boundary of the limit modulus to determine the pavement state.

[0020] By setting multiple evaluation frequencies and comparing the measured dynamic modulus with the ultimate modulus boundary at each frequency, the reliability of pavement fatigue performance evaluation results can be improved. Optionally, the measured dynamic modulus at multiple evaluation frequencies is compared with the corresponding dynamic modulus in the boundary of the ultimate modulus to determine the pavement condition. This includes: calculating the difference between the dynamic modulus in the boundary of the ultimate modulus at a unified evaluation frequency and the measured dynamic modulus; using the weighted sum of multiple differences as the modulus deviation; and confirming pavement health in response to the modulus deviation being greater than a preset value.

[0021] Optionally, in the process of weighted summation of multiple differences, the sum of the weights of the multiple differences is 1.

[0022] Optionally, constructing a correlation curve that characterizes the dynamic modulus of pavement rigidity and the fatigue life of pavement further includes: obtaining multiple sets of pavement material specimens with different RAP dosages, and then subjecting the pavement material specimens to environmental simulation treatment, wherein the environmental simulation treatment includes thermo-oxidative aging treatment and dynamic water erosion treatment.

[0023] By subjecting the specimens to thermo-oxidative aging treatment and dynamic water erosion treatment, the performance degradation process of asphalt mixtures under the influence of environmental factors such as high temperature, oxidation and water erosion during long-term service can be simulated, thus making the test samples closer to the actual road material state.

[0024] This application has the following technical effects: By simulating the aging and hardening process of the mixture throughout its entire life cycle using different gradient RAP dosages, a mathematical mapping model between dynamic modulus and fatigue life was successfully constructed. Furthermore, the ultimate modulus boundary below the failure threshold was derived, enabling rapid quantitative assessment of the health status of existing pavements by simply testing the dynamic modulus of core samples and comparing it with the boundary. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of the road fatigue performance evaluation method based on dynamic modulus in this application embodiment.

[0026] Figure 2 This is a schematic diagram of step S1 in the road fatigue performance evaluation method based on dynamic modulus in the proposed implementation.

[0027] Figure 3 This is a schematic diagram of the correlation curve in the road fatigue performance evaluation method based on dynamic modulus in the proposed implementation.

[0028] Figure 4 This is a schematic diagram comparing the actual dynamic modulus and the limit modulus boundary of different core samples in the road fatigue performance evaluation method based on dynamic modulus in the application specification. Detailed Implementation

[0029] This application discloses a road fatigue performance evaluation method based on dynamic modulus. It extracts stiffness characterization parameters (i.e., dynamic modulus) at different loading frequencies and durability characterization parameters (i.e., fatigue life / fatigue life) at a specific loading frequency, constructing a mathematical mapping relationship (correlation curve) between the two. Subsequently, by normalizing the durability characterization parameters, a red line threshold for key performance degradation is determined, and the corresponding dynamic modulus characteristic baseline is derived. Finally, measured stiffness data from actual service pavement core samples are substituted into a comparison model to achieve a quantitative assessment of the pavement structure's health status and remaining service life. This scheme transforms destructive fatigue testing into non-destructive or low-destructive dynamic modulus testing, providing a scientific basis for preventative maintenance decisions.

[0030] Reference Figure 1 The road fatigue performance evaluation method based on dynamic modulus includes steps S1-S4.

[0031] S1: Construct a correlation curve to map the relationship between the dynamic modulus characterizing pavement rigidity and the fatigue life of the pavement.

[0032] Reference Figure 2 Step S1 includes steps S11-S13.

[0033] S11: Obtain multiple sets of pavement material specimens with different RAP content.

[0034] In a laboratory setting, it's difficult to accurately capture the true condition of a road after 1, 5, or 10 years of service. However, research has found that increasing the amount of recycled asphalt (RAP) can physically simulate the aging and hardening process of asphalt very well.

[0035] Therefore, in this embodiment, in order to construct the performance evolution law covering the entire life cycle of the mixture, a method of step-by-step replacement was used to prepare pavement material specimens with different RAP content.

[0036] As a preferred approach, the RAP (Raponic Acid) content gradient is set to 0%, 25%, 50%, 75%, and 100%. These different RAP contents simulate different service times of highways. For example, 0% represents the baseline state of virgin, unaged asphalt mixtures, indicating a highway in its unused state. 100% represents the extreme aging, high-hardness limit state, where all aggregates in the pavement material specimens are recycled materials from old pavements, representing a decommissioned old pavement. By setting an arithmetic gradient of 25%, the complete evolution trajectory of the material's internal structure from flexible to brittle can be effectively and smoothly captured. The optimal asphalt content for each content is determined using the Marshall design method. For example, when the RAP content is 0%, 25%, 50%, 75%, and 100%, the corresponding optimal asphalt contents are preferably 5.0%, 5.2%, 5.5%, 5.7%, and 6.0%, respectively.

[0037] After preparing the pavement material specimens, it is necessary to simulate the effects of environmental media. These effects mainly include two categories: thermo-oxidative aging and dynamic water erosion. For thermo-oxidative aging, the treatment is carried out according to the requirements of the "Test Procedures for Asphalt and Asphalt Mixtures in Highway Engineering" (JTGE20) T0734. For dynamic water erosion, the Moisture Induced Sensitivity Test (MIST) is used for simulation. In this embodiment, the MIST water bath temperature is preferably set to 60℃, the pressure is preferably set to 276 kPa, and the number of dynamic water circulation cycles is set to 3500. The physical significance of setting the temperature at 60℃ is to simulate the extreme high-temperature working environment of asphalt pavement in summer; if the temperature is too low, the viscous flow characteristics of asphalt cannot be activated, and if the temperature is too high, asphalt will be lost. Therefore, 60℃ can best reflect the destructive effect of water intrusion into the internal pores of the material.

[0038] S12: Measure the dynamic modulus of each group of pavement material specimens within the set loading frequency range; measure the fatigue life of each group of specimens; and fit the dynamic modulus of multiple groups of pavement material specimens with different RAP dosages at the same loading frequency to obtain the correlation curve.

[0039] In this embodiment, specifically, for each type of RAP content pavement material specimen, it is necessary to obtain two key evaluation indicators: fatigue life and dynamic modulus.

[0040] For the extraction of dynamic modulus: the dynamic modulus of the road material specimens was measured at different loading frequency nodes. In this embodiment, the loading frequency nodes mainly include six discrete loading frequency nodes: 25Hz, 10Hz, 5Hz, 1Hz, 0.5Hz, and 0.1Hz.

[0041] It is understandable that different loading frequencies correspond to different vehicle speeds experienced by the actual road surface (higher frequency means faster vehicle speed). For any RAP content category, it corresponds to a set (6) of dynamic modulus values.

[0042] For example, the dynamic modulus of pavement material specimens with different PAP contents at different loading frequency nodes is as follows:

[0043] For fatigue life determination, a semi-circular tensile test was used for quantification. The pavement material specimen was machined into a semi-circle with a thickness of 50 mm and a radius of 75 mm, with a 20 mm slit pre-made at the center of its bottom to induce stress concentration. The test loading temperature was set at 20℃, the stress ratio at 0.5, the loading waveform at a half-sine wave, and the loading frequency at 1 Hz. The number of loading cycles until the pavement material specimen completely fractured was defined as the fatigue life (fatigue life) at that dosage level.

[0044] The experimental results exemplarily show that the fatigue life corresponding to 0% doping is 3785 cycles, while the fatigue life corresponding to 100% doping drops sharply to 707 cycles. Simultaneously, at the same loading frequency, the dynamic modulus gradually increases as the fatigue life decreases.

[0045] For example, the fatigue life of pavement material specimens with different PAP contents after a semi-circular tensile test:

[0046] Combination Figure 3 Through the above steps, for any pavement material specimen, there are six sets of dynamic modulus data and one set of fatigue life data. Each set of dynamic modulus and fatigue life data constitutes a sample dataset. This sample dataset is used as input for curve fitting. In the figure, the horizontal axis represents the dynamic modulus value, and the vertical axis represents fatigue life. Discrete data points under different loading frequency categories are plotted in a two-dimensional coordinate system, and the least squares method is used to fit the trend of data points under the same frequency category, generating multiple correlation curves.

[0047] S2: Set the critical life threshold for fatigue life used to judge the quality of fatigue performance.

[0048] The fatigue life of pavement material specimens without RAP is used as the baseline life, and the value within a preset ratio range of the baseline life is set as the critical life threshold.

[0049] To eliminate the fluctuations in absolute values ​​under different test environments and to construct a unified judgment scale, fatigue life under different PAP dosages is normalized. The normalization method can be any commonly used normalization method (Max-Min normalization, Z-score normalization).

[0050] For example, the fatigue life of a pavement material specimen without added RAP can be defined as the baseline life, and its value can be forcibly calibrated to a baseline constant of 1. As the RAP ratio increases, the proportion of aged asphalt inside the mixture increases, leading to material embrittlement and a gradual decrease in its fatigue life. Drawing on the general termination criteria of the four-point beam bending fatigue test, this embodiment sets a threshold value at which the fatigue-resistant mechanical structure of the mixture is deemed to have failed and can no longer meet the road safety service requirements when the normalized fatigue life decreases to a preset proportion of the baseline life. The corresponding fatigue life is then used as the critical life threshold. In this embodiment, the preset proportion is 50%. In other embodiments, it can be set according to the experience of those skilled in the art. This proportion is mainly for evaluation personnel to refer to in order to determine the health of the road.

[0051] S3: Determine the limiting modulus boundary in the correlation curve based on the critical lifetime threshold.

[0052] The dynamic modulus corresponding to the critical lifetime threshold is extracted from the correlation curve as the critical modulus; the limit modulus boundary is obtained by fitting the critical modulus at different loading frequencies.

[0053] To address the technical challenge of directly and quickly determining fatigue life during on-site construction, it is necessary to project and transform the "critical life threshold" obtained in step S2 into the dynamic modulus evaluation domain.

[0054] First, in the correlation mapping system established in step S1, the horizontal tangent line with the critical life threshold as the vertical axis is locked, and the intersection of the tangent line with the mapping curves of different loading frequency nodes is extracted, so as to obtain the dynamic modulus corresponding to the fatigue life at various loading frequencies from 0.1Hz to 25Hz corresponding to the critical life threshold, and these dynamic moduli are used as critical moduli.

[0055] Subsequently, in order to express the discrete array in a continuous mathematical form, the logarithmic value of the loading frequency was used as the independent variable and the critical dynamic modulus value was used as the dependent variable. The logarithmic linear fitting algorithm was then used to calculate the limit modulus boundary at different loading frequencies.

[0056] Specifically, the formula for calculating the limit modulus boundary can be expressed as: ; In the formula, This represents the limit modulus boundary that the hybrid material is allowed to reach at the critical lifetime threshold. The frequency of loading applied to the material structure is represented, and its effective computational domain is limited to... Within the interval. Constant The frequency sensitivity coefficient characterizes the rate at which the material stiffness hardens as the vehicle's speed (frequency) increases; a constant. The fundamental modulus intercept reflects the material's underlying stiffness at extremely low frequencies; constant and In this embodiment, the characteristic coefficients are obtained by linear regression fitting of multiple sets of loading frequencies and corresponding dynamic moduli under the critical fatigue life threshold. Set as , Set as .

[0057] Assuming the evaluation equipment applies a detection load of 10Hz in the field, the failure baseline at this point needs to be calculated. Substituting into the above formula: First step: Calculate the logarithmic term: The second step is to perform multiplication and addition operations: MPa. Therefore, if the measured modulus of the road surface exceeds 4357.5 MPa under a simulated vehicle speed of 10 Hz, it is determined that the road surface has low fatigue durability and a short service life.

[0058] Asphalt mixtures are typical viscoelastic fluid materials. Their modulus exhibits a non-linear logarithmic growth trend with increasing frequency. A logarithmic linear equation can be used to accurately fit the data with the fewest parameters.

[0059] S4: Obtain core samples of the service road surface, measure its measured dynamic modulus at a preset evaluation frequency, and determine the road surface condition based on the positional relationship between the measured dynamic modulus and the limit modulus boundary.

[0060] In the actual evaluation of road surfaces, core samples are first obtained from newly constructed and existing road surfaces in service using on-site core drilling technology, and their actual dynamic modulus at a specific loading frequency is obtained. The actual dynamic modulus is then spatially compared with the limit modulus boundary to obtain the modulus deviation.

[0061] In one embodiment, a loading frequency can be selected as the evaluation frequency. The actual dynamic modulus is obtained at the evaluation frequency. Then, the difference between the actual dynamic modulus and the limiting modulus boundary is compared to obtain the deviation modulus.

[0062] Specifically, the formula for calculating the modulus deviation can be expressed as: In the formula, This indicates the modulus deviation between the core sample obtained from on-site sampling and the road material specimen; The measured dynamic modulus of the core sample at a specified frequency; This represents the measured dynamic modulus of a pavement material specimen at a specified frequency.

[0063] When the decision function If the measured dynamic modulus is less than the limiting modulus boundary at the evaluation frequency, the material has not shown severe hardening and embrittlement, and is judged to have excellent fatigue performance; otherwise, if If the measured dynamic modulus is greater than the limit modulus boundary corresponding to the evaluation frequency, then the fatigue performance is judged to be poor, and the larger the negative value of the deviation, the shorter the residual structural life is predicted.

[0064] For example, core sample 1 from a newly constructed recycled asphalt pavement that has been in service for only two months is selected for analysis. The fitted formula for its measured dynamic modulus is as follows: Substituting the calculation into the verification scenario: extracting frequency nodes. An evaluation is performed. At this point, the baseline limit value is... MPa. The measured value of the pavement material specimen after 2 months was [value missing]. MPa. Calculate the difference function. MPa. Since the result is much greater than 0, it proves that the material in this section is still in its high-elasticity service life and has extremely excellent fatigue performance.

[0065] In another embodiment, multiple loading frequencies can be selected as evaluation frequencies to obtain the measured dynamic modulus at multiple evaluation frequencies and compare it with the corresponding limiting modulus boundary to obtain the modulus deviation.

[0066] Specifically, the formula for calculating the modulus deviation can be expressed as: ; In the formula, The total number of nodes selected for the sampling frequency; To correspond to the weight of the evaluation frequency, the sum of the weights corresponding to multiple evaluation frequencies is 1; different road sections have different sensitivities to vehicle speed. Indicates the core sample at the first Measured dynamic modulus at each evaluation frequency; This indicates that the pavement material specimen was in the core sample at the first... Measured dynamic modulus at each evaluation frequency; This indicates the number of evaluation frequencies. For example, on heavily loaded uphill sections, deformation resistance at low frequencies (low speeds) is more important; therefore, a lower evaluation frequency (e.g., ...) is assigned to such road sections. Assign higher weights to highways to achieve differentiated maintenance.

[0067] Combination Figure 4 In the figure, the horizontal axis represents the evaluation frequency, or the loading frequency during the dynamic modulus testing process, and the vertical axis represents the measured dynamic modulus value. Core samples 1, 2, and 3 were obtained by core sampling from the pavement. Core sample 1 originated from a newly constructed recycled asphalt pavement with a service life of 2 months; core sample 2 originated from a recycled asphalt pavement with a service life of 5 years; and core sample 3 originated from a recycled asphalt pavement with a service life of 7 years. Dynamic modulus tests were conducted on core samples 1, 2, and 3 at different evaluation frequencies, and the corresponding dynamic modulus variation curves were obtained. In the figure, the dynamic modulus curve of core sample 1, with a service life of 2 months, is basically below the ultimate modulus boundary, indicating that the pavement corresponding to this core sample has excellent fatigue life. The dynamic modulus curves of core samples 2 and 3 are both above the ultimate modulus boundary, indicating that their fatigue performance gradually deteriorates and their residual fatigue life decreases.

[0068] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A road fatigue performance evaluation method based on dynamic modulus, characterized in that, include: Construct a correlation curve between the dynamic modulus characterizing pavement rigidity and the fatigue life of the pavement. Set a critical life threshold for fatigue life to determine the quality of fatigue performance. Determine the limiting modulus boundary from the correlation curve based on the critical lifetime threshold; Core samples of the service road surface are obtained, and their measured dynamic modulus at a preset evaluation frequency is determined. The road surface condition is judged based on the positional relationship between the measured dynamic modulus and the limit modulus boundary.

2. The road fatigue performance evaluation method based on dynamic modulus according to claim 1, characterized in that, To construct a correlation curve that characterizes the dynamic modulus of pavement rigidity and the fatigue life of pavement, the following steps are taken: obtaining multiple sets of pavement material specimens with different RAP contents; measuring the dynamic modulus of each set of pavement material specimens within a set loading frequency range; measuring the fatigue life of each set of specimens; and fitting the dynamic modulus of multiple sets of pavement material specimens with different RAP contents at the same loading frequency to obtain the correlation curve.

3. The road fatigue performance evaluation method based on dynamic modulus according to claim 1, characterized in that, Setting a critical life threshold for fatigue life to judge the quality of fatigue performance includes: taking the fatigue life of a pavement material specimen without RAP as the reference life, and setting the value within a preset proportion range of the reference life as the critical life threshold.

4. The road fatigue performance evaluation method based on dynamic modulus according to claim 1, characterized in that, Based on the critical lifetime threshold, the limiting modulus boundary is determined in the correlation curve, including: extracting the dynamic modulus at different loading frequencies corresponding to the critical lifetime threshold from the correlation curve, and fitting the dynamic modulus to obtain the limiting modulus boundary.

5. The road fatigue performance evaluation method based on dynamic modulus according to claim 4, characterized in that, A log-linear function was used to fit the dynamic modulus at different loading frequencies corresponding to the key lifetime threshold extracted from the correlation curve.

6. The road fatigue performance evaluation method based on dynamic modulus according to claim 1, characterized in that, The measured dynamic modulus at a preset evaluation frequency is determined, and the pavement condition is judged based on the positional relationship between the measured dynamic modulus and the limit modulus boundary. This includes: determining the corresponding dynamic modulus in the limit modulus boundary according to the evaluation frequency, comparing the measured dynamic modulus with the corresponding dynamic modulus in the limit modulus boundary, and confirming pavement health in response to the measured dynamic modulus being less than or equal to the corresponding dynamic modulus in the limit modulus boundary.

7. The road fatigue performance evaluation method based on dynamic modulus according to claim 1, characterized in that, Multiple evaluation frequencies are set, and the measured dynamic modulus at multiple evaluation frequencies is compared with the corresponding dynamic modulus in the boundary of the limit modulus to determine the road surface condition.

8. The road fatigue performance evaluation method based on dynamic modulus according to claim 7, characterized in that, The measured dynamic modulus at multiple evaluation frequencies is compared with the corresponding dynamic modulus at the limit modulus boundary to determine the pavement condition. This includes: calculating the difference between the dynamic modulus at the limit modulus boundary and the measured dynamic modulus at a unified evaluation frequency; using the weighted sum of multiple differences as the modulus deviation; and confirming pavement health in response to the modulus deviation being greater than a preset value.

9. The road fatigue performance evaluation method based on dynamic modulus according to claim 8, characterized in that, In the process of weighted summation of multiple differences, the sum of the weights of the multiple differences is 1.

10. The road fatigue performance evaluation method based on dynamic modulus according to claim 2, characterized in that, Constructing a correlation curve that characterizes the dynamic modulus of pavement rigidity and the fatigue life of pavement also includes: obtaining multiple sets of pavement material specimens with different RAP content, and then performing environmental simulation treatment on the pavement material specimens, the environmental simulation treatment including thermo-oxidative aging treatment and dynamic water erosion treatment.

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